This tutorial illustrates how to add a trial-level early stopping strategy to an Ax hyper-parameter optimization (HPO) loop. The goal of trial-level early stopping is to monitor the results of expensive evaluations and terminate those that are unlikely to produce promising results, freeing up resources to explore more configurations.
Most of this tutorial is adapted from the PyTorch Ax Multiobjective NAS Tutorial. The training job is different from the original in that we do not optimize batch_size or epochs. This was done for illustrative purposes, as each validation curve now has the same number of points. The companion training file mnist_train_nas.py has also been altered to log to Tensorboard during training.
NOTE: Although the original NAS tutorial is for a multi-objective problem, this tutorial focuses on a single objective (validation accuracy) problem. Early stopping currently does not support "true" multi-objective stopping, although one can use logical compositions of early stopping strategies to target multiple objectives separately. Early stopping for the multi-objective case is currently a work in progress.
import os
import tempfile
from pathlib import Path
import torchx
from ax.core import Experiment, Objective, ParameterType, RangeParameter, SearchSpace
from ax.core.optimization_config import OptimizationConfig
from ax.early_stopping.strategies import PercentileEarlyStoppingStrategy
from ax.metrics.tensorboard import TensorboardMetric
from ax.modelbridge.dispatch_utils import choose_generation_strategy
from ax.runners.torchx import TorchXRunner
from ax.service.scheduler import Scheduler, SchedulerOptions
from ax.service.utils.report_utils import exp_to_df
from tensorboard.backend.event_processing import plugin_event_multiplexer as event_multiplexer
from torchx import specs
from torchx.components import utils
from matplotlib import pyplot as plt
%matplotlib inline
[ERROR 11-12 06:43:46] ax.storage.sqa_store.encoder: ATTENTION: The Ax team is considering deprecating SQLAlchemy storage. If you are currently using SQLAlchemy storage, please reach out to us via GitHub Issues here: https://github.com/facebook/Ax/issues/2975
SMOKE_TEST = os.environ.get("SMOKE_TEST")
Our goal is to optimize the PyTorch Lightning training job defined in mnist_train_nas.py. To do this using TorchX, we write a helper function that takes in the values of the architcture and hyperparameters of the training job and creates a TorchX AppDef with the appropriate settings.
if SMOKE_TEST:
epochs = 3
else:
epochs = 10
def trainer(
log_path: str,
hidden_size_1: int,
hidden_size_2: int,
learning_rate: float,
dropout: float,
trial_idx: int = -1,
) -> specs.AppDef:
# define the log path so we can pass it to the TorchX AppDef
if trial_idx >= 0:
log_path = Path(log_path).joinpath(str(trial_idx)).absolute().as_posix()
batch_size = 32
return utils.python(
# command line args to the training script
"--log_path",
log_path,
"--hidden_size_1",
str(hidden_size_1),
"--hidden_size_2",
str(hidden_size_2),
"--learning_rate",
str(learning_rate),
"--epochs",
str(epochs),
"--dropout",
str(dropout),
"--batch_size",
str(batch_size),
# other config options
name="trainer",
script="tutorials/early_stopping/mnist_train_nas.py",
image=torchx.version.TORCHX_IMAGE,
)
Ax’s Runner
abstraction allows writing interfaces to various backends.
Ax already comes with Runner for TorchX, so we just need to
configure it. For the purpose of this tutorial, we run jobs locally
in a fully asynchronous fashion. In order to launch them on a cluster, you can instead specify a
different TorchX scheduler and adjust the configuration appropriately.
For example, if you have a Kubernetes cluster, you just need to change the
scheduler from local_cwd to kubernetes.
The training job launched by this runner will log partial results to Tensorboard, which will then be monitored by the early stopping strategy. We will show how this is done using an Ax TensorboardMetric below.
# Make a temporary dir to log our results into
log_dir = tempfile.mkdtemp()
ax_runner = TorchXRunner(
tracker_base="/tmp/",
component=trainer,
# NOTE: To launch this job on a cluster instead of locally you can
# specify a different scheduler and adjust args appropriately.
scheduler="local_cwd",
component_const_params={"log_path": log_dir},
cfg={},
)
First, we define our search space. Ax supports both range parameters of type integer and float as well as choice parameters which can have non-numerical types such as strings. We will tune the hidden sizes, learning rate, and dropout parameters.
parameters = [
# NOTE: In a real-world setting, hidden_size_1 and hidden_size_2
# should probably be powers of 2, but in our simple example this
# would mean that num_params can't take on that many values, which
# in turn makes the Pareto frontier look pretty weird.
RangeParameter(
name="hidden_size_1",
lower=16,
upper=128,
parameter_type=ParameterType.INT,
log_scale=True,
),
RangeParameter(
name="hidden_size_2",
lower=16,
upper=128,
parameter_type=ParameterType.INT,
log_scale=True,
),
RangeParameter(
name="learning_rate",
lower=1e-4,
upper=1e-2,
parameter_type=ParameterType.FLOAT,
log_scale=True,
),
RangeParameter(
name="dropout",
lower=0.0,
upper=0.5,
parameter_type=ParameterType.FLOAT,
),
]
search_space = SearchSpace(
parameters=parameters,
# NOTE: In practice, it may make sense to add a constraint
# hidden_size_2 <= hidden_size_1
parameter_constraints=[],
)
Ax has the concept of a Metric that defines properties of outcomes and how observations are obtained for these outcomes. This allows e.g. encodig how data is fetched from some distributed execution backend and post-processed before being passed as input to Ax.
We will optimize the validation accuracy, which is a TensorboardMetric that points to the logging directory assigned above. Note that we have set is_available_while_running, allowing for the metric to be queried as the trial progresses. This is critical for the early stopping strategy to monitor partial results.
class MyTensorboardMetric(TensorboardMetric):
# NOTE: We need to tell the new Tensorboard metric how to get the id /
# file handle for the tensorboard logs from a trial. In this case
# our convention is to just save a separate file per trial in
# the pre-specified log dir.
def _get_event_multiplexer_for_trial(self, trial):
mul = event_multiplexer.EventMultiplexer(max_reload_threads=20)
mul.AddRunsFromDirectory(Path(log_dir).joinpath(str(trial.index)).as_posix(), None)
mul.Reload()
return mul
# This indicates whether the metric is queryable while the trial is
# still running. This is required for early stopping to monitor the
# progress of the running trial.ArithmeticError
@classmethod
def is_available_while_running(cls):
return True
val_acc = MyTensorboardMetric(
name="val_acc",
tag="val_acc",
lower_is_better=False,
)
The OptimizationConfig specifies the objective for Ax to optimize.
opt_config = OptimizationConfig(
objective=Objective(
metric=val_acc,
minimize=False,
)
)
A PercentileEarlyStoppingStrategy is a simple method that stops a trial if its performance falls below a certain percentile of other trials at the same step (e.g., when percentile_threshold is 50, at a given point in time, if a trial ranks in the bottom 50% of trials, it is stopped).
normalize_progressions which normalizes the progression column (e.g. timestamp, epochs, training data used) to be in [0, 1]. This is useful because one doesn't need to know the maximum progression values of the curve (which might be, e.g., the total number of data points in the training dataset).min_progression parameter specifies that trials should only be considered for stopping if the latest progression value is greater than this threshold.min_curves parameter specifies the minimum number of completed curves (i.e., fully completed training jobs) before early stopping will be considered. This should be larger than zero if normalize_progression is used. In general, we want a few completed curves to have a baseline for comparison.Note that PercentileEarlyStoppingStrategy does not make use of learning curve modeling or prediction. More sophisticated model-based methods will be available in future versions of Ax.
percentile_early_stopping_strategy = PercentileEarlyStoppingStrategy(
# stop if in bottom 70% of runs at the same progression
percentile_threshold=70,
# the trial must have passed `min_progression` steps before early stopping is initiated
# note that we are using `normalize_progressions`, so this is on a scale of [0, 1]
min_progression=0.3,
# there must be `min_curves` completed trials and `min_curves` trials reporting data in
# order for early stopping to be applicable
min_curves=5,
# specify, e.g., [0, 1] if the first two trials should never be stopped
trial_indices_to_ignore=None,
# check for new data every 10 seconds
seconds_between_polls=10,
normalize_progressions=True,
)
In Ax, the Experiment object is the object that stores all the information about the problem setup.
experiment = Experiment(
name="torchx_mnist",
search_space=search_space,
optimization_config=opt_config,
runner=ax_runner,
)
A GenerationStrategy is the abstract representation of how we would like to perform the optimization. While this can be customized (if you’d like to do so, see this tutorial), in most cases Ax can automatically determine an appropriate strategy based on the search space, optimization config, and the total number of trials we want to run.
Typically, Ax chooses to evaluate a number of random configurations before starting a model-based Bayesian Optimization strategy.
We remark that in Ax, generation strategies and early stopping strategies are separate, a design decision motivated by ease-of-use. However, we should acknowledge that jointly considering generation and stopping using a single strategy would likely be the "proper" formulation.
if SMOKE_TEST:
total_trials = 6
else:
total_trials = 15 # total evaluation budget
gs = choose_generation_strategy(
search_space=experiment.search_space,
optimization_config=experiment.optimization_config,
num_trials=total_trials,
)
[INFO 11-12 06:43:47] ax.modelbridge.dispatch_utils: Using Models.BOTORCH_MODULAR since there is at least one ordered parameter and there are no unordered categorical parameters.
[INFO 11-12 06:43:47] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=4 num_trials=15 use_batch_trials=False
[INFO 11-12 06:43:47] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=5
[INFO 11-12 06:43:47] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=5
[INFO 11-12 06:43:47] ax.modelbridge.dispatch_utils: `verbose`, `disable_progbar`, and `jit_compile` are not yet supported when using `choose_generation_strategy` with ModularBoTorchModel, dropping these arguments.
[INFO 11-12 06:43:47] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+BoTorch', steps=[Sobol for 5 trials, BoTorch for subsequent trials]). Iterations after 5 will take longer to generate due to model-fitting.
The Scheduler acts as the loop control for the optimization.
It communicates with the backend to launch trials, check their status, retrieve (partial) results, and importantly for this tutorial, calls the early stopping strategy. If the early stopping strategy suggests a trial to be the stopped, the Scheduler communicates with the backend to terminate the trial.
The Scheduler requires the Experiment and the GenerationStrategy.
A set of options can be passed in via SchedulerOptions. Here, we
configure the number of total evaluations as well as max_pending_trials,
the maximum number of trials that should run concurrently. In our
local setting, this is the number of training jobs running as individual
processes, while in a remote execution setting, this would be the number
of machines you want to use in parallel.
scheduler = Scheduler(
experiment=experiment,
generation_strategy=gs,
options=SchedulerOptions(
total_trials=total_trials,
max_pending_trials=5,
early_stopping_strategy=percentile_early_stopping_strategy,
),
)
[INFO 11-12 06:43:47] Scheduler: `Scheduler` requires experiment to have immutable search space and optimization config. Setting property immutable_search_space_and_opt_config to `True` on experiment.
%%time
scheduler.run_all_trials()
[INFO 11-12 06:43:47] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:43:47] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/modelbridge/cross_validation.py:464: UserWarning: Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.
warn("Encountered exception in computing model fit quality: " + str(e))
[INFO 11-12 06:43:47] Scheduler: Running trials [0]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/modelbridge/cross_validation.py:464: UserWarning: Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.
warn("Encountered exception in computing model fit quality: " + str(e))
[INFO 11-12 06:43:48] Scheduler: Running trials [1]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/modelbridge/cross_validation.py:464: UserWarning: Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.
warn("Encountered exception in computing model fit quality: " + str(e))
[INFO 11-12 06:43:49] Scheduler: Running trials [2]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/modelbridge/cross_validation.py:464: UserWarning: Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.
warn("Encountered exception in computing model fit quality: " + str(e))
[INFO 11-12 06:43:50] Scheduler: Running trials [3]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/modelbridge/cross_validation.py:464: UserWarning: Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.
warn("Encountered exception in computing model fit quality: " + str(e))
[INFO 11-12 06:43:51] Scheduler: Running trials [4]...
[WARNING 11-12 06:43:52] Scheduler: Both `init_seconds_between_polls` and `early_stopping_strategy supplied. `init_seconds_between_polls=1` will be overrridden by `early_stopping_strategy.seconds_between_polls=10` and polling will take place at a constant rate.
[INFO 11-12 06:43:52] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:43:52] Scheduler: Fetching data for trials: 0 - 4 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:43:52] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf10f0>")
[INFO 11-12 06:43:52] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf09a0>")
[INFO 11-12 06:43:52] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0940>")
[INFO 11-12 06:43:52] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0280>")
[INFO 11-12 06:43:52] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0670>")
[ERROR 11-12 06:43:52] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf10f0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:43:52] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf09a0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:43:52] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0940>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:43:52] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0280>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:43:52] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0670>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:43:52] Scheduler: Failed to fetch val_acc for trial 0, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf10f0>").
[INFO 11-12 06:43:52] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 0 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:43:52] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf09a0>").
[INFO 11-12 06:43:52] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:43:52] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0940>").
[INFO 11-12 06:43:52] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:43:52] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0280>").
[INFO 11-12 06:43:52] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:43:52] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0670>").
[INFO 11-12 06:43:52] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:43:52] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
[INFO 11-12 06:43:52] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:44:02] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:44:02] Scheduler: Fetching data for trials: 1 - 4 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:44:02] Scheduler: Retrieved FAILED trials: [0].
[INFO 11-12 06:44:02] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0b50>")
[INFO 11-12 06:44:02] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1810>")
[INFO 11-12 06:44:02] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1b10>")
[INFO 11-12 06:44:02] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf17e0>")
[ERROR 11-12 06:44:02] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0b50>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:02] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1810>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:02] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1b10>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:02] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf17e0>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:44:02] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0b50>").
[INFO 11-12 06:44:02] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:02] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1810>").
[INFO 11-12 06:44:02] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:02] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1b10>").
[INFO 11-12 06:44:02] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:02] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf17e0>").
[INFO 11-12 06:44:02] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:44:02] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/modelbridge/cross_validation.py:464: UserWarning: Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.
warn("Encountered exception in computing model fit quality: " + str(e))
[INFO 11-12 06:44:02] Scheduler: Running trials [5]...
[WARNING 11-12 06:44:03] Scheduler: Both `init_seconds_between_polls` and `early_stopping_strategy supplied. `init_seconds_between_polls=1` will be overrridden by `early_stopping_strategy.seconds_between_polls=10` and polling will take place at a constant rate.
[INFO 11-12 06:44:03] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:44:03] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:44:03] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1690>")
[INFO 11-12 06:44:03] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0d30>")
[INFO 11-12 06:44:03] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0c70>")
[INFO 11-12 06:44:03] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1720>")
[INFO 11-12 06:44:03] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf10f0>")
[ERROR 11-12 06:44:03] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1690>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:03] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0d30>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:03] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0c70>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:03] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1720>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:03] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf10f0>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:44:03] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1690>").
[INFO 11-12 06:44:03] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:03] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0d30>").
[INFO 11-12 06:44:03] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:03] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0c70>").
[INFO 11-12 06:44:03] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:03] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1720>").
[INFO 11-12 06:44:03] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:03] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf10f0>").
[INFO 11-12 06:44:03] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:44:03] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
[INFO 11-12 06:44:03] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:44:13] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:44:13] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:44:13] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3cd0>")
[INFO 11-12 06:44:13] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2980>")
[INFO 11-12 06:44:13] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2dd0>")
[INFO 11-12 06:44:13] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2d10>")
[INFO 11-12 06:44:14] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3790>")
[ERROR 11-12 06:44:14] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3cd0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:14] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2980>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:14] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2dd0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:14] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2d10>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:14] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3790>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:44:14] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3cd0>").
[INFO 11-12 06:44:14] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:14] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2980>").
[INFO 11-12 06:44:14] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:14] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2dd0>").
[INFO 11-12 06:44:14] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:14] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2d10>").
[INFO 11-12 06:44:14] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:14] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3790>").
[INFO 11-12 06:44:14] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:44:14] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
[INFO 11-12 06:44:14] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:44:24] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:44:24] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:44:24] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2890>")
[INFO 11-12 06:44:24] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf39a0>")
[INFO 11-12 06:44:24] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3040>")
[INFO 11-12 06:44:24] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2a40>")
[INFO 11-12 06:44:24] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3b50>")
[ERROR 11-12 06:44:24] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2890>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:24] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf39a0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:24] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3040>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:24] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2a40>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:24] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3b50>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:44:24] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2890>").
[INFO 11-12 06:44:24] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:24] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf39a0>").
[INFO 11-12 06:44:24] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:24] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3040>").
[INFO 11-12 06:44:24] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:24] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2a40>").
[INFO 11-12 06:44:24] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:24] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3b50>").
[INFO 11-12 06:44:24] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:44:24] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
[INFO 11-12 06:44:24] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:44:34] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:44:34] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:44:34] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2680>")
[INFO 11-12 06:44:34] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3580>")
[INFO 11-12 06:44:34] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3100>")
[INFO 11-12 06:44:34] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2a40>")
[INFO 11-12 06:44:34] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0580>")
[ERROR 11-12 06:44:34] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2680>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:34] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3580>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:34] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3100>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:34] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2a40>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:34] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0580>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:44:34] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2680>").
[INFO 11-12 06:44:34] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:34] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3580>").
[INFO 11-12 06:44:34] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:34] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3100>").
[INFO 11-12 06:44:34] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:34] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2a40>").
[INFO 11-12 06:44:34] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:34] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0580>").
[INFO 11-12 06:44:34] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:44:34] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
[INFO 11-12 06:44:34] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:44:44] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:44:44] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:44:44] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf30a0>")
[INFO 11-12 06:44:44] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3d90>")
[INFO 11-12 06:44:44] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2530>")
[INFO 11-12 06:44:44] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2f20>")
[INFO 11-12 06:44:44] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2e90>")
[ERROR 11-12 06:44:44] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf30a0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:44] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3d90>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:44] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2530>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:44] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2f20>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:44] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2e90>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:44:44] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf30a0>").
[INFO 11-12 06:44:44] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:44] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3d90>").
[INFO 11-12 06:44:44] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:44] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2530>").
[INFO 11-12 06:44:44] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:44] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2f20>").
[INFO 11-12 06:44:44] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:44] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2e90>").
[INFO 11-12 06:44:44] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:44:44] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
[INFO 11-12 06:44:44] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:44:54] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:44:54] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:44:54] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1b70>")
[INFO 11-12 06:44:54] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1ab0>")
[INFO 11-12 06:44:54] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3280>")
[INFO 11-12 06:44:54] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0580>")
[INFO 11-12 06:44:54] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf18d0>")
[ERROR 11-12 06:44:54] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1b70>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:54] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1ab0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:54] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3280>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:54] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0580>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:44:54] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf18d0>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:44:54] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1b70>").
[INFO 11-12 06:44:54] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:54] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1ab0>").
[INFO 11-12 06:44:54] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:54] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3280>").
[INFO 11-12 06:44:54] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:54] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0580>").
[INFO 11-12 06:44:54] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:44:54] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf18d0>").
[INFO 11-12 06:44:54] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:44:54] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
[INFO 11-12 06:44:54] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:45:04] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:45:04] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:45:04] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3a30>")
[INFO 11-12 06:45:04] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3940>")
[INFO 11-12 06:45:04] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2320>")
[INFO 11-12 06:45:04] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3820>")
[INFO 11-12 06:45:04] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3190>")
[ERROR 11-12 06:45:04] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3a30>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:04] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3940>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:04] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2320>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:04] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3820>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:04] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3190>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:45:04] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3a30>").
[INFO 11-12 06:45:04] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:04] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3940>").
[INFO 11-12 06:45:04] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:04] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2320>").
[INFO 11-12 06:45:04] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:04] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3820>").
[INFO 11-12 06:45:04] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:04] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3190>").
[INFO 11-12 06:45:04] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:45:04] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
[INFO 11-12 06:45:04] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:45:14] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:45:14] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:45:14] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3dc0>")
[INFO 11-12 06:45:14] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0250>")
[INFO 11-12 06:45:14] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf30a0>")
[INFO 11-12 06:45:14] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3f40>")
[INFO 11-12 06:45:14] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2950>")
[ERROR 11-12 06:45:14] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3dc0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:14] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0250>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:14] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf30a0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:14] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3f40>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:14] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2950>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:45:14] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3dc0>").
[INFO 11-12 06:45:14] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:14] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0250>").
[INFO 11-12 06:45:14] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:14] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf30a0>").
[INFO 11-12 06:45:14] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:14] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3f40>").
[INFO 11-12 06:45:14] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:14] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2950>").
[INFO 11-12 06:45:14] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:45:14] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
[INFO 11-12 06:45:14] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:45:24] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:45:24] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:45:24] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3cd0>")
[INFO 11-12 06:45:24] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2aa0>")
[INFO 11-12 06:45:24] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2950>")
[INFO 11-12 06:45:24] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3070>")
[INFO 11-12 06:45:24] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2e90>")
[ERROR 11-12 06:45:24] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3cd0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:24] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2aa0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:24] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2950>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:24] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3070>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:24] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2e90>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:45:24] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3cd0>").
[INFO 11-12 06:45:24] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:24] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2aa0>").
[INFO 11-12 06:45:24] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:24] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2950>").
[INFO 11-12 06:45:24] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:24] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3070>").
[INFO 11-12 06:45:24] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:24] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2e90>").
[INFO 11-12 06:45:24] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:45:25] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
[INFO 11-12 06:45:25] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:45:35] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:45:35] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:45:35] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2f50>")
[INFO 11-12 06:45:35] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1000>")
[INFO 11-12 06:45:35] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2a40>")
[INFO 11-12 06:45:35] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3c40>")
[INFO 11-12 06:45:35] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0250>")
[ERROR 11-12 06:45:35] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2f50>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:35] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1000>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:35] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2a40>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:35] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3c40>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:35] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0250>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 06:45:35] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2f50>").
[INFO 11-12 06:45:35] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:35] Scheduler: Failed to fetch val_acc for trial 2, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf1000>").
[INFO 11-12 06:45:35] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 2 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:35] Scheduler: Failed to fetch val_acc for trial 3, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2a40>").
[INFO 11-12 06:45:35] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 3 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:35] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3c40>").
[INFO 11-12 06:45:35] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:35] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf0250>").
[INFO 11-12 06:45:35] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
[INFO 11-12 06:45:35] ax.early_stopping.strategies.base: PercentileEarlyStoppingStrategy received empty data. Not stopping any trials.
[INFO 11-12 06:45:35] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:45:45] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:45:45] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:45:45] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2170>")
[INFO 11-12 06:45:45] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3220>")
[INFO 11-12 06:45:45] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3cd0>")
[ERROR 11-12 06:45:45] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2170>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:45] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3220>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:45] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3cd0>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 06:45:45] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf2170>").
[INFO 11-12 06:45:45] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:45] Scheduler: Failed to fetch val_acc for trial 4, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3220>").
[INFO 11-12 06:45:45] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 4 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:45] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3cd0>").
[INFO 11-12 06:45:45] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:45:45] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:45:45] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:45:55] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:45:55] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
[INFO 11-12 06:45:55] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3520>")
[INFO 11-12 06:45:55] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf05b0>")
[ERROR 11-12 06:45:55] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3520>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 06:45:55] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf05b0>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 06:45:55] Scheduler: Failed to fetch val_acc for trial 1, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf3520>").
[INFO 11-12 06:45:55] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 1 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 06:45:55] Scheduler: Failed to fetch val_acc for trial 5, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf98bf05b0>").
[INFO 11-12 06:45:55] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 5 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:45:55] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:45:55] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:46:05] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:46:05] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:46:05] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:46:05] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:46:15] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:46:15] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:46:15] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:46:16] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:46:26] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:46:26] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:46:26] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:46:26] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:46:36] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:46:36] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:46:36] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:46:36] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:46:46] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:46:46] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:46:46] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:46:46] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:46:56] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:46:56] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:46:57] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:46:57] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:47:07] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:47:07] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:47:07] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:47:07] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:47:17] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:47:17] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:47:17] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:47:17] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:47:27] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:47:27] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:47:27] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:47:27] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:47:37] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:47:37] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:47:37] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:47:37] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:47:47] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:47:47] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:47:48] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:47:48] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:47:58] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:47:58] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:47:58] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:47:58] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:48:08] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:48:08] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:48:08] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:48:08] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:48:18] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:48:18] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:48:18] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:48:18] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:48:28] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:48:28] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:48:29] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:48:29] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:48:39] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:48:39] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:48:39] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:48:39] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:48:49] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:48:49] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:48:49] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:48:49] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:48:59] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:48:59] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:48:59] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:48:59] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:49:09] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:49:09] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:49:10] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:49:10] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:49:20] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:49:20] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:49:20] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:49:20] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:49:30] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:49:30] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:49:30] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:49:30] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:49:40] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:49:40] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:49:40] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:49:40] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:49:50] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:49:50] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:49:51] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:49:51] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:50:01] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:50:01] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:50:01] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:50:01] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:50:11] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:50:11] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:50:11] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:50:11] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:50:21] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:50:21] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:50:21] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:50:21] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:50:31] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:50:31] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:50:32] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:50:32] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:50:42] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:50:42] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:50:42] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:50:42] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:50:52] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:50:52] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:50:52] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:50:52] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:51:02] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:51:02] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:51:02] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:51:02] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:51:12] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:51:12] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:51:13] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:51:13] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:51:23] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:51:23] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:51:23] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:51:23] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:51:33] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:51:33] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:51:33] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:51:33] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:51:43] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:51:43] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:51:43] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:51:43] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:51:53] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:51:53] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:51:54] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:51:54] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:52:04] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:52:04] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:52:04] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:52:04] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:52:14] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:52:14] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:52:14] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:52:14] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:52:24] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:52:24] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:52:24] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:52:24] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:52:34] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:52:34] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:52:35] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:52:35] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:52:45] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:52:45] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:52:45] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:52:45] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:52:55] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:52:55] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:52:55] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:52:55] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:53:05] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:53:05] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:53:05] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:53:05] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:53:15] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:53:15] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:53:16] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:53:16] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:53:26] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:53:26] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:53:26] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:53:26] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:53:36] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:53:36] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:53:36] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:53:36] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:53:46] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:53:46] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:53:46] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:53:46] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:53:56] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:53:56] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:53:57] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:53:57] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:54:07] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:54:07] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:54:07] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:54:07] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:54:17] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:54:17] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:54:17] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:54:17] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:54:27] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:54:27] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:54:27] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:54:27] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:54:37] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:54:37] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:54:37] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:54:37] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:54:48] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:54:48] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:54:48] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:54:48] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:54:58] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:54:58] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:54:58] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:54:58] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:55:08] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:55:08] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:55:08] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:55:08] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:55:18] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:55:18] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:55:19] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:55:19] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:55:29] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:55:29] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:55:29] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:55:29] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:55:39] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:55:39] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:55:39] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:55:39] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:55:49] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:55:49] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:55:49] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:55:49] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:55:59] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:55:59] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:56:00] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:56:00] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:56:10] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:56:10] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:56:10] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:56:10] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:56:20] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:56:20] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:56:20] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:56:20] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:56:30] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:56:30] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:56:30] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:56:30] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:56:40] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:56:40] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:56:41] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:56:41] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:56:51] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:56:51] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:56:51] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:56:51] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:57:01] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:57:01] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:57:01] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:57:01] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:57:11] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:57:11] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:57:11] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:57:11] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:57:21] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:57:21] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:57:22] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:57:22] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:57:32] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:57:32] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:57:32] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:57:32] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:57:42] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:57:42] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:57:42] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:57:42] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:57:52] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:57:52] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:57:53] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:57:53] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:58:03] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:58:03] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:58:03] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:58:03] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:58:13] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:58:13] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:58:13] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:58:13] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:58:23] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:58:23] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:58:24] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:58:24] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:58:34] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:58:34] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:58:34] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:58:34] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:58:44] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:58:44] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:58:44] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:58:44] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:58:54] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:58:54] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:58:54] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:58:54] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:59:04] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:59:04] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:59:05] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:59:05] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:59:15] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:59:15] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:59:15] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:59:15] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:59:25] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:59:25] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:59:25] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:59:25] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:59:35] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:59:35] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:59:35] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[WARNING 11-12 06:59:35] Scheduler: Both `init_seconds_between_polls` and `early_stopping_strategy supplied. `init_seconds_between_polls=1` will be overrridden by `early_stopping_strategy.seconds_between_polls=10` and polling will take place at a constant rate.
[INFO 11-12 06:59:35] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:59:35] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:59:36] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:59:36] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:59:46] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:59:46] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 06:59:46] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:59:46] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 06:59:56] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 06:59:56] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 06:59:56] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 06:59:56] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:00:06] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:00:06] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:00:06] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:00:06] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:00:16] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:00:16] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:00:17] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:00:17] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:00:27] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:00:27] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:00:27] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:00:27] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:00:37] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:00:37] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:00:37] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:00:37] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:00:47] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:00:47] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:00:48] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:00:48] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:00:58] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:00:58] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:00:58] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:00:58] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:01:08] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:01:08] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:01:08] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:01:08] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:01:18] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:01:18] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:01:18] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:01:18] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:01:28] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:01:28] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:01:29] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:01:29] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:01:39] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:01:39] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:01:39] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:01:39] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:01:49] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:01:49] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:01:49] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:01:49] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:01:59] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:01:59] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:01:59] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:01:59] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:02:09] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:02:09] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:02:10] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:02:10] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:02:20] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:02:20] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:02:20] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:02:20] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:02:30] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:02:30] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:02:30] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:02:30] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:02:40] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:02:40] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:02:40] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:02:40] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:02:50] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:02:50] Scheduler: Fetching data for trials: 1 - 5 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:02:51] ax.early_stopping.strategies.base: The number of completed trials (0) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:02:51] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 5).
[INFO 11-12 07:03:01] Scheduler: Fetching data for newly completed trials: [2].
[INFO 11-12 07:03:01] Scheduler: Fetching data for trials: [1, 3, 4, 5] because some metrics on experiment are available while trials are running.
[INFO 11-12 07:03:01] Scheduler: Retrieved COMPLETED trials: [2].
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:03:01] ax.early_stopping.strategies.base: The number of completed trials (1) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[WARNING 11-12 07:03:01] Scheduler: Both `init_seconds_between_polls` and `early_stopping_strategy supplied. `init_seconds_between_polls=1` will be overrridden by `early_stopping_strategy.seconds_between_polls=10` and polling will take place at a constant rate.
[INFO 11-12 07:03:01] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:03:01] Scheduler: Fetching data for trials: [1, 3, 4, 5] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:03:01] ax.early_stopping.strategies.base: The number of completed trials (1) is less than the minimum number of curves needed for early stopping (5). Not early stopping.
[INFO 11-12 07:03:01] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 4).
[INFO 11-12 07:03:11] Scheduler: Fetching data for newly completed trials: [1, 3, 4, 5].
[INFO 11-12 07:03:11] Scheduler: Retrieved COMPLETED trials: [1, 3, 4, 5].
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:03:12] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.
[INFO 11-12 07:03:12] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:03:12] Scheduler: Running trials [6]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:03:14] Scheduler: Running trials [7]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:03:17] Scheduler: Running trials [8]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:03:18] Scheduler: Generated all trials that can be generated currently. Max parallelism currently reached.
[WARNING 11-12 07:03:18] Scheduler: Both `init_seconds_between_polls` and `early_stopping_strategy supplied. `init_seconds_between_polls=1` will be overrridden by `early_stopping_strategy.seconds_between_polls=10` and polling will take place at a constant rate.
[INFO 11-12 07:03:18] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:03:18] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:03:18] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95866bc0>")
[INFO 11-12 07:03:18] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958675b0>")
[INFO 11-12 07:03:18] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958675b0>")
[ERROR 11-12 07:03:18] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95866bc0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:03:18] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958675b0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:03:18] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958675b0>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 07:03:18] Scheduler: Failed to fetch val_acc for trial 8, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95866bc0>").
[INFO 11-12 07:03:18] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 8 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:03:18] Scheduler: Failed to fetch val_acc for trial 6, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958675b0>").
[INFO 11-12 07:03:18] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 6 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:03:18] Scheduler: Failed to fetch val_acc for trial 7, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958675b0>").
[INFO 11-12 07:03:18] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 7 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:03:18] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.
[INFO 11-12 07:03:18] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:03:18] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:03:28] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:03:28] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:03:28] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a79360>")
[INFO 11-12 07:03:28] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a95c00>")
[INFO 11-12 07:03:28] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a7bd90>")
[ERROR 11-12 07:03:28] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a79360>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:03:28] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a95c00>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:03:28] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a7bd90>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 07:03:28] Scheduler: Failed to fetch val_acc for trial 8, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a79360>").
[INFO 11-12 07:03:28] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 8 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:03:28] Scheduler: Failed to fetch val_acc for trial 6, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a95c00>").
[INFO 11-12 07:03:28] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 6 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:03:28] Scheduler: Failed to fetch val_acc for trial 7, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a7bd90>").
[INFO 11-12 07:03:28] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 7 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:03:28] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.
[INFO 11-12 07:03:28] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:03:28] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:03:38] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:03:38] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:03:38] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95898fa0>")
[INFO 11-12 07:03:38] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95898fa0>")
[INFO 11-12 07:03:38] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>")
[ERROR 11-12 07:03:38] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95898fa0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:03:38] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95898fa0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:03:38] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 07:03:38] Scheduler: Failed to fetch val_acc for trial 8, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95898fa0>").
[INFO 11-12 07:03:38] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 8 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:03:38] Scheduler: Failed to fetch val_acc for trial 6, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95898fa0>").
[INFO 11-12 07:03:38] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 6 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:03:38] Scheduler: Failed to fetch val_acc for trial 7, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>").
[INFO 11-12 07:03:38] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 7 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:03:38] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.
[INFO 11-12 07:03:38] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:03:38] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:03:48] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:03:48] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:03:48] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>")
[INFO 11-12 07:03:48] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>")
[INFO 11-12 07:03:48] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>")
[ERROR 11-12 07:03:48] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:03:48] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:03:48] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 07:03:48] Scheduler: Failed to fetch val_acc for trial 8, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>").
[INFO 11-12 07:03:48] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 8 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:03:48] Scheduler: Failed to fetch val_acc for trial 6, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>").
[INFO 11-12 07:03:48] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 6 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:03:48] Scheduler: Failed to fetch val_acc for trial 7, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958666b0>").
[INFO 11-12 07:03:48] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 7 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:03:48] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.
[INFO 11-12 07:03:48] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:03:48] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:03:58] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:03:58] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:03:58] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a7bd90>")
[INFO 11-12 07:03:58] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958ac760>")
[ERROR 11-12 07:03:58] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a7bd90>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:03:58] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958ac760>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:03:58] Scheduler: Failed to fetch val_acc for trial 8, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a7bd90>").
[INFO 11-12 07:03:58] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 8 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:03:58] Scheduler: Failed to fetch val_acc for trial 7, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958ac760>").
[INFO 11-12 07:03:58] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 7 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:03:58] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.09994666666666667.
[INFO 11-12 07:03:58] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:03:58] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:04:08] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:04:08] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:04:08] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589a140>")
[ERROR 11-12 07:04:08] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589a140>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:04:08] Scheduler: Failed to fetch val_acc for trial 8, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589a140>").
[INFO 11-12 07:04:08] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 8 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:04:08] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.09994666666666667.
[INFO 11-12 07:04:08] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:04:08] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:04:18] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:04:18] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:04:18] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.09994666666666667.
[INFO 11-12 07:04:18] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:04:18] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:04:28] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:04:28] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:04:29] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.09994666666666667.
[INFO 11-12 07:04:29] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:04:29] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:04:39] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:04:39] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:04:39] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.09994666666666667.
[INFO 11-12 07:04:39] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:04:39] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:04:49] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:04:49] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:04:49] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.19994666666666666.
[INFO 11-12 07:04:49] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:04:49] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:04:59] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:04:59] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:04:59] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.19994666666666666.
[INFO 11-12 07:04:59] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:04:59] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:05:09] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:05:09] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:05:09] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.19994666666666666.
[INFO 11-12 07:05:09] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:05:09] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:05:19] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:05:19] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:05:19] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.19994666666666666.
[INFO 11-12 07:05:19] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:05:19] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:05:29] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:05:29] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:05:29] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:05:29] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:05:29] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:05:39] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:05:39] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:05:39] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:05:39] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:05:39] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:05:49] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:05:49] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:05:50] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:05:50] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:05:50] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:06:00] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:06:00] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:06:00] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:06:00] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:06:00] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:06:10] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:06:10] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:06:10] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:06:10] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:06:10] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:06:20] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:06:20] Scheduler: Fetching data for trials: 6 - 8 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:06:20] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.3999466666666667.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.percentile: Considering trial 8 for early stopping.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.base: Last progression of Trial 8 is 0.3999466666666667.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.percentile: Early stopping decision for 8: True. Reason: Trial objective value 0.9492431735170299 is worse than 70.0-th percentile (0.9536788960102155) across comparable trials.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.percentile: Considering trial 6 for early stopping.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.base: Last progression of Trial 6 is 0.3999466666666667.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.percentile: Early stopping decision for 6: True. Reason: Trial objective value 0.9516955282300563 is worse than 70.0-th percentile (0.9536788960102155) across comparable trials.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.3999466666666667.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:06:20] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9576470464321192 is better than 70.0-th percentile (0.9536788960102155) across comparable trials.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:06:23] Scheduler: Running trials [9]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:06:25] Scheduler: Running trials [10]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:06:25] Scheduler: Generated all trials that can be generated currently. Max parallelism currently reached.
[WARNING 11-12 07:06:25] Scheduler: Both `init_seconds_between_polls` and `early_stopping_strategy supplied. `init_seconds_between_polls=1` will be overrridden by `early_stopping_strategy.seconds_between_polls=10` and polling will take place at a constant rate.
[INFO 11-12 07:06:25] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:06:25] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
[INFO 11-12 07:06:25] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bfe20>")
[INFO 11-12 07:06:25] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bfe20>")
[ERROR 11-12 07:06:25] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bfe20>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:06:25] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bfe20>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:06:25] Scheduler: Failed to fetch val_acc for trial 9, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bfe20>").
[INFO 11-12 07:06:25] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 9 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:06:25] Scheduler: Failed to fetch val_acc for trial 10, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bfe20>").
[INFO 11-12 07:06:25] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 10 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:06:25] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.3999466666666667.
[INFO 11-12 07:06:25] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:06:25] ax.early_stopping.strategies.base: There is not yet any data associated with trial 9 and metric val_acc. Not early stopping this trial.
[INFO 11-12 07:06:25] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:06:25] ax.early_stopping.strategies.base: There is not yet any data associated with trial 10 and metric val_acc. Not early stopping this trial.
[INFO 11-12 07:06:25] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:06:25] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.3999466666666667.
[INFO 11-12 07:06:25] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:06:25] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9576470464321192 is better than 70.0-th percentile (0.9536788960102155) across comparable trials.
[INFO 11-12 07:06:25] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:06:35] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:06:35] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
[INFO 11-12 07:06:35] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589ad10>")
[INFO 11-12 07:06:35] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589ad10>")
[ERROR 11-12 07:06:35] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589ad10>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:06:35] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589ad10>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:06:35] Scheduler: Failed to fetch val_acc for trial 9, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589ad10>").
[INFO 11-12 07:06:35] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 9 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:06:35] Scheduler: Failed to fetch val_acc for trial 10, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589ad10>").
[INFO 11-12 07:06:35] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 10 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:06:35] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.3999466666666667.
[INFO 11-12 07:06:35] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:06:35] ax.early_stopping.strategies.base: There is not yet any data associated with trial 9 and metric val_acc. Not early stopping this trial.
[INFO 11-12 07:06:35] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:06:35] ax.early_stopping.strategies.base: There is not yet any data associated with trial 10 and metric val_acc. Not early stopping this trial.
[INFO 11-12 07:06:35] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:06:35] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.3999466666666667.
[INFO 11-12 07:06:35] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:06:35] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9576470464321192 is better than 70.0-th percentile (0.9536788960102155) across comparable trials.
[INFO 11-12 07:06:35] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:06:45] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:06:45] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
[INFO 11-12 07:06:45] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a95630>")
[INFO 11-12 07:06:45] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589a2c0>")
[ERROR 11-12 07:06:45] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a95630>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:06:45] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589a2c0>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:06:45] Scheduler: Failed to fetch val_acc for trial 9, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf94a95630>").
[INFO 11-12 07:06:45] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 9 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:06:45] Scheduler: Failed to fetch val_acc for trial 10, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf9589a2c0>").
[INFO 11-12 07:06:45] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 10 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:06:45] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.3999466666666667.
[INFO 11-12 07:06:45] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:06:45] ax.early_stopping.strategies.base: There is not yet any data associated with trial 9 and metric val_acc. Not early stopping this trial.
[INFO 11-12 07:06:45] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:06:45] ax.early_stopping.strategies.base: There is not yet any data associated with trial 10 and metric val_acc. Not early stopping this trial.
[INFO 11-12 07:06:45] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:06:45] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.3999466666666667.
[INFO 11-12 07:06:45] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:06:45] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9576470464321192 is better than 70.0-th percentile (0.9536788960102155) across comparable trials.
[INFO 11-12 07:06:45] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:06:55] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:06:55] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
[INFO 11-12 07:06:55] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf4f0>")
[INFO 11-12 07:06:55] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf4f0>")
[ERROR 11-12 07:06:55] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf4f0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:06:55] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf4f0>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:06:55] Scheduler: Failed to fetch val_acc for trial 9, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf4f0>").
[INFO 11-12 07:06:55] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 9 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:06:55] Scheduler: Failed to fetch val_acc for trial 10, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf4f0>").
[INFO 11-12 07:06:55] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 10 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:06:55] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.3999466666666667.
[INFO 11-12 07:06:55] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:06:55] ax.early_stopping.strategies.base: There is not yet any data associated with trial 9 and metric val_acc. Not early stopping this trial.
[INFO 11-12 07:06:55] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:06:55] ax.early_stopping.strategies.base: There is not yet any data associated with trial 10 and metric val_acc. Not early stopping this trial.
[INFO 11-12 07:06:55] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:06:55] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.3999466666666667.
[INFO 11-12 07:06:55] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:06:55] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9576470464321192 is better than 70.0-th percentile (0.9536788960102155) across comparable trials.
[INFO 11-12 07:06:55] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:07:05] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:07:05] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
[INFO 11-12 07:07:05] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958999f0>")
[INFO 11-12 07:07:05] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95866b60>")
[ERROR 11-12 07:07:05] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958999f0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:07:05] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95866b60>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:07:06] Scheduler: Failed to fetch val_acc for trial 9, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958999f0>").
[INFO 11-12 07:07:06] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 9 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:07:06] Scheduler: Failed to fetch val_acc for trial 10, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf95866b60>").
[INFO 11-12 07:07:06] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 10 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:07:06] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.49994666666666665.
[INFO 11-12 07:07:06] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:07:06] ax.early_stopping.strategies.base: There is not yet any data associated with trial 9 and metric val_acc. Not early stopping this trial.
[INFO 11-12 07:07:06] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:07:06] ax.early_stopping.strategies.base: There is not yet any data associated with trial 10 and metric val_acc. Not early stopping this trial.
[INFO 11-12 07:07:06] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:07:06] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.49994666666666665.
[INFO 11-12 07:07:06] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935835 2 0.969378 3 0.927315 4 0.926094 5 0.959565 7 0.960080 Name: 0.49994666666666665, dtype: float64.
[INFO 11-12 07:07:06] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9600802879097622 is better than 70.0-th percentile (0.9598226058147812) across comparable trials.
[INFO 11-12 07:07:06] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:07:16] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:07:16] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:07:16] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.49994666666666665.
[INFO 11-12 07:07:16] ax.early_stopping.utils: Got exception `x and y arrays must have at least 2 entries` during interpolation. Using uninterpolated values instead.
[INFO 11-12 07:07:16] ax.early_stopping.utils: Got exception `x and y arrays must have at least 2 entries` during interpolation. Using uninterpolated values instead.
[INFO 11-12 07:07:16] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:07:16] ax.early_stopping.strategies.base: Last progression of Trial 9 is 0.09994666666666667.
[INFO 11-12 07:07:16] ax.early_stopping.strategies.base: Trial 9's most recent progression (0.09994666666666667) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:07:16] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:07:16] ax.early_stopping.strategies.base: Last progression of Trial 10 is 0.09994666666666667.
[INFO 11-12 07:07:16] ax.early_stopping.strategies.base: Trial 10's most recent progression (0.09994666666666667) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:07:16] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:07:16] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.49994666666666665.
[INFO 11-12 07:07:16] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935835 2 0.969378 3 0.927315 4 0.926094 5 0.959565 7 0.960080 Name: 0.49994666666666665, dtype: float64.
[INFO 11-12 07:07:16] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9600802879097622 is better than 70.0-th percentile (0.9598226058147812) across comparable trials.
[INFO 11-12 07:07:16] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:07:26] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:07:26] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:07:26] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.49994666666666665.
[INFO 11-12 07:07:26] ax.early_stopping.utils: Got exception `x and y arrays must have at least 2 entries` during interpolation. Using uninterpolated values instead.
[INFO 11-12 07:07:26] ax.early_stopping.utils: Got exception `x and y arrays must have at least 2 entries` during interpolation. Using uninterpolated values instead.
[INFO 11-12 07:07:26] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:07:26] ax.early_stopping.strategies.base: Last progression of Trial 9 is 0.09994666666666667.
[INFO 11-12 07:07:26] ax.early_stopping.strategies.base: Trial 9's most recent progression (0.09994666666666667) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:07:26] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:07:26] ax.early_stopping.strategies.base: Last progression of Trial 10 is 0.09994666666666667.
[INFO 11-12 07:07:26] ax.early_stopping.strategies.base: Trial 10's most recent progression (0.09994666666666667) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:07:26] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:07:26] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.49994666666666665.
[INFO 11-12 07:07:26] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935835 2 0.969378 3 0.927315 4 0.926094 5 0.959565 7 0.960080 Name: 0.49994666666666665, dtype: float64.
[INFO 11-12 07:07:26] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9600802879097622 is better than 70.0-th percentile (0.9598226058147812) across comparable trials.
[INFO 11-12 07:07:26] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:07:36] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:07:36] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:07:36] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.49994666666666665.
[INFO 11-12 07:07:36] ax.early_stopping.utils: Got exception `x and y arrays must have at least 2 entries` during interpolation. Using uninterpolated values instead.
[INFO 11-12 07:07:36] ax.early_stopping.utils: Got exception `x and y arrays must have at least 2 entries` during interpolation. Using uninterpolated values instead.
[INFO 11-12 07:07:36] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:07:36] ax.early_stopping.strategies.base: Last progression of Trial 9 is 0.09994666666666667.
[INFO 11-12 07:07:36] ax.early_stopping.strategies.base: Trial 9's most recent progression (0.09994666666666667) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:07:36] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:07:36] ax.early_stopping.strategies.base: Last progression of Trial 10 is 0.09994666666666667.
[INFO 11-12 07:07:36] ax.early_stopping.strategies.base: Trial 10's most recent progression (0.09994666666666667) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:07:36] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:07:36] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.49994666666666665.
[INFO 11-12 07:07:36] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935835 2 0.969378 3 0.927315 4 0.926094 5 0.959565 7 0.960080 Name: 0.49994666666666665, dtype: float64.
[INFO 11-12 07:07:36] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9600802879097622 is better than 70.0-th percentile (0.9598226058147812) across comparable trials.
[INFO 11-12 07:07:36] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:07:46] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:07:46] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:07:46] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.5999466666666666.
[INFO 11-12 07:07:46] ax.early_stopping.utils: Got exception `x and y arrays must have at least 2 entries` during interpolation. Using uninterpolated values instead.
[INFO 11-12 07:07:46] ax.early_stopping.utils: Got exception `x and y arrays must have at least 2 entries` during interpolation. Using uninterpolated values instead.
[INFO 11-12 07:07:46] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:07:46] ax.early_stopping.strategies.base: Last progression of Trial 9 is 0.09994666666666667.
[INFO 11-12 07:07:46] ax.early_stopping.strategies.base: Trial 9's most recent progression (0.09994666666666667) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:07:46] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:07:46] ax.early_stopping.strategies.base: Last progression of Trial 10 is 0.09994666666666667.
[INFO 11-12 07:07:46] ax.early_stopping.strategies.base: Trial 10's most recent progression (0.09994666666666667) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:07:46] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:07:46] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.5999466666666666.
[INFO 11-12 07:07:46] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935517 2 0.970626 3 0.928419 4 0.927635 5 0.963079 7 0.964297 Name: 0.5999466666666666, dtype: float64.
[INFO 11-12 07:07:46] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9642967402601785 is better than 70.0-th percentile (0.9636880459067494) across comparable trials.
[INFO 11-12 07:07:46] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:07:56] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:07:56] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:07:56] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.5999466666666666.
[INFO 11-12 07:07:57] ax.early_stopping.utils: Got exception `x and y arrays must have at least 2 entries` during interpolation. Using uninterpolated values instead.
[INFO 11-12 07:07:57] ax.early_stopping.utils: Got exception `x and y arrays must have at least 2 entries` during interpolation. Using uninterpolated values instead.
[INFO 11-12 07:07:57] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:07:57] ax.early_stopping.strategies.base: Last progression of Trial 9 is 0.09994666666666667.
[INFO 11-12 07:07:57] ax.early_stopping.strategies.base: Trial 9's most recent progression (0.09994666666666667) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:07:57] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:07:57] ax.early_stopping.strategies.base: Last progression of Trial 10 is 0.09994666666666667.
[INFO 11-12 07:07:57] ax.early_stopping.strategies.base: Trial 10's most recent progression (0.09994666666666667) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:07:57] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:07:57] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.5999466666666666.
[INFO 11-12 07:07:57] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935517 2 0.970626 3 0.928419 4 0.927635 5 0.963079 7 0.964297 Name: 0.5999466666666666, dtype: float64.
[INFO 11-12 07:07:57] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9642967402601785 is better than 70.0-th percentile (0.9636880459067494) across comparable trials.
[INFO 11-12 07:07:57] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:08:07] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:08:07] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:08:07] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.5999466666666666.
[INFO 11-12 07:08:07] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:08:07] ax.early_stopping.strategies.base: Last progression of Trial 9 is 0.19994666666666666.
[INFO 11-12 07:08:07] ax.early_stopping.strategies.base: Trial 9's most recent progression (0.19994666666666666) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:08:07] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:08:07] ax.early_stopping.strategies.base: Last progression of Trial 10 is 0.19994666666666666.
[INFO 11-12 07:08:07] ax.early_stopping.strategies.base: Trial 10's most recent progression (0.19994666666666666) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:08:07] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:08:07] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.5999466666666666.
[INFO 11-12 07:08:07] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935517 2 0.970626 3 0.928419 4 0.927635 5 0.963079 7 0.964297 Name: 0.5999466666666666, dtype: float64.
[INFO 11-12 07:08:07] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9642967402601785 is better than 70.0-th percentile (0.9636880459067494) across comparable trials.
[INFO 11-12 07:08:07] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:08:17] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:08:17] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:08:17] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.5999466666666666.
[INFO 11-12 07:08:17] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:08:17] ax.early_stopping.strategies.base: Last progression of Trial 9 is 0.19994666666666666.
[INFO 11-12 07:08:17] ax.early_stopping.strategies.base: Trial 9's most recent progression (0.19994666666666666) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:08:17] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:08:17] ax.early_stopping.strategies.base: Last progression of Trial 10 is 0.19994666666666666.
[INFO 11-12 07:08:17] ax.early_stopping.strategies.base: Trial 10's most recent progression (0.19994666666666666) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:08:17] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:08:17] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.5999466666666666.
[INFO 11-12 07:08:17] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935517 2 0.970626 3 0.928419 4 0.927635 5 0.963079 7 0.964297 Name: 0.5999466666666666, dtype: float64.
[INFO 11-12 07:08:17] ax.early_stopping.strategies.percentile: Early stopping decision for 7: False. Reason: Trial objective value 0.9642967402601785 is better than 70.0-th percentile (0.9636880459067494) across comparable trials.
[INFO 11-12 07:08:17] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:08:27] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:08:27] Scheduler: Fetching data for trials: [7, 9, 10] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:08:27] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.6999466666666667.
[INFO 11-12 07:08:27] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:08:27] ax.early_stopping.strategies.base: Last progression of Trial 9 is 0.19994666666666666.
[INFO 11-12 07:08:27] ax.early_stopping.strategies.base: Trial 9's most recent progression (0.19994666666666666) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:08:27] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:08:27] ax.early_stopping.strategies.base: Last progression of Trial 10 is 0.19994666666666666.
[INFO 11-12 07:08:27] ax.early_stopping.strategies.base: Trial 10's most recent progression (0.19994666666666666) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:08:27] ax.early_stopping.strategies.percentile: Considering trial 7 for early stopping.
[INFO 11-12 07:08:27] ax.early_stopping.strategies.base: Last progression of Trial 7 is 0.6999466666666667.
[INFO 11-12 07:08:27] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935277 2 0.973356 3 0.923340 4 0.932135 5 0.965863 7 0.962080 Name: 0.6999466666666667, dtype: float64.
[INFO 11-12 07:08:27] ax.early_stopping.strategies.percentile: Early stopping decision for 7: True. Reason: Trial objective value 0.9620804046157635 is worse than 70.0-th percentile (0.9639715727952688) across comparable trials.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:08:31] Scheduler: Running trials [11]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:08:32] Scheduler: Generated all trials that can be generated currently. Max parallelism currently reached.
[WARNING 11-12 07:08:32] Scheduler: Both `init_seconds_between_polls` and `early_stopping_strategy supplied. `init_seconds_between_polls=1` will be overrridden by `early_stopping_strategy.seconds_between_polls=10` and polling will take place at a constant rate.
[INFO 11-12 07:08:32] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:08:32] Scheduler: Fetching data for trials: 9 - 11 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:08:32] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7460>")
[ERROR 11-12 07:08:32] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7460>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:08:32] Scheduler: Failed to fetch val_acc for trial 11, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7460>").
[INFO 11-12 07:08:32] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 11 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:08:32] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.19994666666666666.
[INFO 11-12 07:08:32] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:08:32] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:08:42] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:08:42] Scheduler: Fetching data for trials: 9 - 11 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:08:42] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b5ea0>")
[ERROR 11-12 07:08:42] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b5ea0>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:08:42] Scheduler: Failed to fetch val_acc for trial 11, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b5ea0>").
[INFO 11-12 07:08:42] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 11 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:08:42] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:08:42] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:08:42] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:08:52] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:08:52] Scheduler: Fetching data for trials: 9 - 11 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:08:52] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958be770>")
[ERROR 11-12 07:08:52] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958be770>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:08:52] Scheduler: Failed to fetch val_acc for trial 11, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958be770>").
[INFO 11-12 07:08:52] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 11 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:08:52] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:08:52] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:08:52] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:09:02] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:09:02] Scheduler: Fetching data for trials: 9 - 11 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:09:02] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b6c80>")
[ERROR 11-12 07:09:02] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b6c80>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:09:02] Scheduler: Failed to fetch val_acc for trial 11, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b6c80>").
[INFO 11-12 07:09:02] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 11 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:09:02] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:09:02] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:09:02] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:09:12] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:09:12] Scheduler: Fetching data for trials: 9 - 11 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:09:12] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf040>")
[ERROR 11-12 07:09:12] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf040>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:09:12] Scheduler: Failed to fetch val_acc for trial 11, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf040>").
[INFO 11-12 07:09:12] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 11 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:09:12] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:09:12] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:09:12] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:09:22] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:09:22] Scheduler: Fetching data for trials: 9 - 11 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:09:22] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:09:22] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:09:22] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:09:32] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:09:32] Scheduler: Fetching data for trials: 9 - 11 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:09:32] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.3999466666666667.
[INFO 11-12 07:09:33] ax.early_stopping.utils: Got exception `x and y arrays must have at least 2 entries` during interpolation. Using uninterpolated values instead.
[INFO 11-12 07:09:33] ax.early_stopping.strategies.percentile: Considering trial 9 for early stopping.
[INFO 11-12 07:09:33] ax.early_stopping.strategies.base: Last progression of Trial 9 is 0.3999466666666667.
[INFO 11-12 07:09:33] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 9 0.952378 10 0.947536 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:09:33] ax.early_stopping.strategies.percentile: Early stopping decision for 9: True. Reason: Trial objective value 0.9523780028808294 is worse than 70.0-th percentile (0.9528343830789839) across comparable trials.
[INFO 11-12 07:09:33] ax.early_stopping.strategies.percentile: Considering trial 10 for early stopping.
[INFO 11-12 07:09:33] ax.early_stopping.strategies.base: Last progression of Trial 10 is 0.3999466666666667.
[INFO 11-12 07:09:33] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 9 0.952378 10 0.947536 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:09:33] ax.early_stopping.strategies.percentile: Early stopping decision for 10: True. Reason: Trial objective value 0.9475357943567737 is worse than 70.0-th percentile (0.9528343830789839) across comparable trials.
[INFO 11-12 07:09:33] ax.early_stopping.strategies.percentile: Considering trial 11 for early stopping.
[INFO 11-12 07:09:33] ax.early_stopping.strategies.base: Last progression of Trial 11 is 0.09994666666666667.
[INFO 11-12 07:09:33] ax.early_stopping.strategies.base: Trial 11's most recent progression (0.09994666666666667) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:09:35] Scheduler: Running trials [12]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:09:39] Scheduler: Running trials [13]...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:09:40] Scheduler: Generated all trials that can be generated currently. Max parallelism currently reached.
[WARNING 11-12 07:09:40] Scheduler: Both `init_seconds_between_polls` and `early_stopping_strategy supplied. `init_seconds_between_polls=1` will be overrridden by `early_stopping_strategy.seconds_between_polls=10` and polling will take place at a constant rate.
[INFO 11-12 07:09:40] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:09:40] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:09:40] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf250>")
[INFO 11-12 07:09:40] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf940>")
[ERROR 11-12 07:09:40] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf250>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:09:40] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf940>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:09:40] Scheduler: Failed to fetch val_acc for trial 12, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf250>").
[INFO 11-12 07:09:40] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 12 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:09:40] Scheduler: Failed to fetch val_acc for trial 13, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bf940>").
[INFO 11-12 07:09:40] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 13 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:09:40] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.09994666666666667.
[INFO 11-12 07:09:40] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:09:40] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:09:50] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:09:50] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:09:50] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7910>")
[INFO 11-12 07:09:50] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b5b70>")
[ERROR 11-12 07:09:50] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7910>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:09:50] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b5b70>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:09:50] Scheduler: Failed to fetch val_acc for trial 12, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7910>").
[INFO 11-12 07:09:50] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 12 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:09:50] Scheduler: Failed to fetch val_acc for trial 13, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b5b70>").
[INFO 11-12 07:09:50] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 13 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:09:50] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.09994666666666667.
[INFO 11-12 07:09:50] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:09:50] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:10:00] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:10:00] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:10:00] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b59c0>")
[INFO 11-12 07:10:00] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7b50>")
[ERROR 11-12 07:10:00] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b59c0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:10:00] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7b50>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:10:00] Scheduler: Failed to fetch val_acc for trial 12, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b59c0>").
[INFO 11-12 07:10:00] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 12 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:10:00] Scheduler: Failed to fetch val_acc for trial 13, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7b50>").
[INFO 11-12 07:10:01] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 13 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:10:01] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.19994666666666666.
[INFO 11-12 07:10:01] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:10:01] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:10:11] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:10:11] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:10:11] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7e20>")
[INFO 11-12 07:10:11] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b5ab0>")
[ERROR 11-12 07:10:11] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7e20>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:10:11] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b5ab0>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:10:11] Scheduler: Failed to fetch val_acc for trial 12, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7e20>").
[INFO 11-12 07:10:11] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 12 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:10:11] Scheduler: Failed to fetch val_acc for trial 13, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b5ab0>").
[INFO 11-12 07:10:11] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 13 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:10:11] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.19994666666666666.
[INFO 11-12 07:10:11] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:10:11] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:10:21] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:10:21] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:10:21] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7fa0>")
[INFO 11-12 07:10:21] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b6da0>")
[ERROR 11-12 07:10:21] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7fa0>"). Ignoring for now -- will retry query on next call to fetch.
[ERROR 11-12 07:10:21] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b6da0>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:10:21] Scheduler: Failed to fetch val_acc for trial 12, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7fa0>").
[INFO 11-12 07:10:21] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 12 is still RUNNING continuing the experiment and retrying on next poll...
[WARNING 11-12 07:10:21] Scheduler: Failed to fetch val_acc for trial 13, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b6da0>").
[INFO 11-12 07:10:21] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 13 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:10:21] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.19994666666666666.
[INFO 11-12 07:10:21] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:10:21] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:10:31] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:10:31] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:10:31] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.19994666666666666.
[INFO 11-12 07:10:31] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:10:31] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:10:41] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:10:41] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:10:41] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.19994666666666666.
[INFO 11-12 07:10:41] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:10:41] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:10:51] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:10:51] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:10:51] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:10:51] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:10:51] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:11:01] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:11:01] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:11:01] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:11:01] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:11:01] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:11:11] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:11:11] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:11:11] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:11:11] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:11:11] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:11:21] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:11:21] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:11:22] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:11:22] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:11:22] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:11:32] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:11:32] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:11:32] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:11:32] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:11:32] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:11:42] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:11:42] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:11:42] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.3999466666666667.
[INFO 11-12 07:11:42] ax.early_stopping.strategies.percentile: Considering trial 11 for early stopping.
[INFO 11-12 07:11:42] ax.early_stopping.strategies.base: Last progression of Trial 11 is 0.3999466666666667.
[INFO 11-12 07:11:42] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 9 0.952378 10 0.947536 11 0.954991 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:11:42] ax.early_stopping.strategies.percentile: Early stopping decision for 11: False. Reason: Trial objective value 0.9549907815867456 is better than 70.0-th percentile (0.953899270208011) across comparable trials.
[INFO 11-12 07:11:42] ax.early_stopping.strategies.percentile: Considering trial 12 for early stopping.
[INFO 11-12 07:11:42] ax.early_stopping.strategies.base: Last progression of Trial 12 is 0.19994666666666666.
[INFO 11-12 07:11:42] ax.early_stopping.strategies.base: Trial 12's most recent progression (0.19994666666666666) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:11:42] ax.early_stopping.strategies.percentile: Considering trial 13 for early stopping.
[INFO 11-12 07:11:42] ax.early_stopping.strategies.base: Last progression of Trial 13 is 0.19994666666666666.
[INFO 11-12 07:11:42] ax.early_stopping.strategies.base: Trial 13's most recent progression (0.19994666666666666) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:11:42] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:11:52] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:11:52] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:11:52] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.3999466666666667.
[INFO 11-12 07:11:52] ax.early_stopping.strategies.percentile: Considering trial 11 for early stopping.
[INFO 11-12 07:11:52] ax.early_stopping.strategies.base: Last progression of Trial 11 is 0.3999466666666667.
[INFO 11-12 07:11:52] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 9 0.952378 10 0.947536 11 0.954991 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:11:52] ax.early_stopping.strategies.percentile: Early stopping decision for 11: False. Reason: Trial objective value 0.9549907815867456 is better than 70.0-th percentile (0.953899270208011) across comparable trials.
[INFO 11-12 07:11:52] ax.early_stopping.strategies.percentile: Considering trial 12 for early stopping.
[INFO 11-12 07:11:52] ax.early_stopping.strategies.base: Last progression of Trial 12 is 0.19994666666666666.
[INFO 11-12 07:11:52] ax.early_stopping.strategies.base: Trial 12's most recent progression (0.19994666666666666) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:11:52] ax.early_stopping.strategies.percentile: Considering trial 13 for early stopping.
[INFO 11-12 07:11:52] ax.early_stopping.strategies.base: Last progression of Trial 13 is 0.19994666666666666.
[INFO 11-12 07:11:52] ax.early_stopping.strategies.base: Trial 13's most recent progression (0.19994666666666666) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:11:52] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:12:02] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:12:02] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:12:02] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.3999466666666667.
[INFO 11-12 07:12:02] ax.early_stopping.strategies.percentile: Considering trial 11 for early stopping.
[INFO 11-12 07:12:02] ax.early_stopping.strategies.base: Last progression of Trial 11 is 0.3999466666666667.
[INFO 11-12 07:12:02] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 9 0.952378 10 0.947536 11 0.954991 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:12:02] ax.early_stopping.strategies.percentile: Early stopping decision for 11: False. Reason: Trial objective value 0.9549907815867456 is better than 70.0-th percentile (0.953899270208011) across comparable trials.
[INFO 11-12 07:12:02] ax.early_stopping.strategies.percentile: Considering trial 12 for early stopping.
[INFO 11-12 07:12:02] ax.early_stopping.strategies.base: Last progression of Trial 12 is 0.29994666666666664.
[INFO 11-12 07:12:02] ax.early_stopping.strategies.base: Trial 12's most recent progression (0.29994666666666664) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:12:02] ax.early_stopping.strategies.percentile: Considering trial 13 for early stopping.
[INFO 11-12 07:12:02] ax.early_stopping.strategies.base: Last progression of Trial 13 is 0.29994666666666664.
[INFO 11-12 07:12:02] ax.early_stopping.strategies.base: Trial 13's most recent progression (0.29994666666666664) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:12:02] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:12:12] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:12:12] Scheduler: Fetching data for trials: 11 - 13 because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:12:12] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.49994666666666665.
[INFO 11-12 07:12:12] ax.early_stopping.strategies.percentile: Considering trial 11 for early stopping.
[INFO 11-12 07:12:12] ax.early_stopping.strategies.base: Last progression of Trial 11 is 0.49994666666666665.
[INFO 11-12 07:12:12] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935835 2 0.969378 3 0.927315 4 0.926094 5 0.959565 7 0.960080 11 0.958255 Name: 0.49994666666666665, dtype: float64.
[INFO 11-12 07:12:12] ax.early_stopping.strategies.percentile: Early stopping decision for 11: True. Reason: Trial objective value 0.958255139632091 is worse than 70.0-th percentile (0.9596679965577926) across comparable trials.
[INFO 11-12 07:12:12] ax.early_stopping.strategies.percentile: Considering trial 12 for early stopping.
[INFO 11-12 07:12:12] ax.early_stopping.strategies.base: Last progression of Trial 12 is 0.29994666666666664.
[INFO 11-12 07:12:12] ax.early_stopping.strategies.base: Trial 12's most recent progression (0.29994666666666664) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
[INFO 11-12 07:12:12] ax.early_stopping.strategies.percentile: Considering trial 13 for early stopping.
[INFO 11-12 07:12:12] ax.early_stopping.strategies.base: Last progression of Trial 13 is 0.29994666666666664.
[INFO 11-12 07:12:12] ax.early_stopping.strategies.base: Trial 13's most recent progression (0.29994666666666664) that is available for metric val_acc falls out of the min/max_progression range (0.3, None). Not early stopping this trial.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
[INFO 11-12 07:12:21] Scheduler: Running trials [14]...
[WARNING 11-12 07:12:21] Scheduler: Both `init_seconds_between_polls` and `early_stopping_strategy supplied. `init_seconds_between_polls=1` will be overrridden by `early_stopping_strategy.seconds_between_polls=10` and polling will take place at a constant rate.
[INFO 11-12 07:12:21] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:12:21] Scheduler: Fetching data for trials: 12 - 14 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:12:21] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7400>")
[ERROR 11-12 07:12:21] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7400>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:12:21] Scheduler: Failed to fetch val_acc for trial 14, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7400>").
[INFO 11-12 07:12:21] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 14 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:12:21] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:12:21] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:12:21] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:12:31] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:12:31] Scheduler: Fetching data for trials: 12 - 14 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:12:31] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7220>")
[ERROR 11-12 07:12:31] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7220>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:12:31] Scheduler: Failed to fetch val_acc for trial 14, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958b7220>").
[INFO 11-12 07:12:31] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 14 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:12:31] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:12:31] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:12:31] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 3).
[INFO 11-12 07:12:41] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:12:41] Scheduler: Fetching data for trials: 12 - 14 because some metrics on experiment are available while trials are running.
[INFO 11-12 07:12:41] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bd390>")
[ERROR 11-12 07:12:41] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bd390>"). Ignoring for now -- will retry query on next call to fetch.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [WARNING 11-12 07:12:41] Scheduler: Failed to fetch val_acc for trial 14, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958bd390>").
[INFO 11-12 07:12:41] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 14 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:12:41] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.3999466666666667.
[INFO 11-12 07:12:41] ax.early_stopping.strategies.percentile: Considering trial 12 for early stopping.
[INFO 11-12 07:12:41] ax.early_stopping.strategies.base: Last progression of Trial 12 is 0.3999466666666667.
[INFO 11-12 07:12:41] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 9 0.952378 10 0.947536 11 0.954991 12 0.952097 13 0.947849 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:12:41] ax.early_stopping.strategies.percentile: Early stopping decision for 12: True. Reason: Trial objective value 0.9520969393805331 is worse than 70.0-th percentile (0.9529865098117021) across comparable trials.
[INFO 11-12 07:12:41] ax.early_stopping.strategies.percentile: Considering trial 13 for early stopping.
[INFO 11-12 07:12:41] ax.early_stopping.strategies.base: Last progression of Trial 13 is 0.3999466666666667.
[INFO 11-12 07:12:41] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 9 0.952378 10 0.947536 11 0.954991 12 0.952097 13 0.947849 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:12:41] ax.early_stopping.strategies.percentile: Early stopping decision for 13: True. Reason: Trial objective value 0.9478485460939078 is worse than 70.0-th percentile (0.9529865098117021) across comparable trials.
[INFO 11-12 07:12:41] ax.early_stopping.strategies.percentile: Considering trial 14 for early stopping.
[INFO 11-12 07:12:41] ax.early_stopping.strategies.base: There is not yet any data associated with trial 14 and metric val_acc. Not early stopping this trial.
[INFO 11-12 07:12:43] Scheduler: Done submitting trials, waiting for remaining 1 running trials...
[WARNING 11-12 07:12:43] Scheduler: Both `init_seconds_between_polls` and `early_stopping_strategy supplied. `init_seconds_between_polls=1` will be overrridden by `early_stopping_strategy.seconds_between_polls=10` and polling will take place at a constant rate.
[INFO 11-12 07:12:43] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:12:43] Scheduler: Fetching data for trials: [14] because some metrics on experiment are available while trials are running.
[INFO 11-12 07:12:43] ax.core.metric: MetricFetchE INFO: Initialized MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958be710>")
[ERROR 11-12 07:12:43] ax.core.experiment: Discovered Metric fetching Err while attaching data MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958be710>"). Ignoring for now -- will retry query on next call to fetch.
[WARNING 11-12 07:12:43] Scheduler: Failed to fetch val_acc for trial 14, found MetricFetchE(message="No 'scalar' data found for trial in multiplexer mul=<tensorboard.backend.event_processing.plugin_event_multiplexer.EventMultiplexer object at 0x7fcf958be710>").
[INFO 11-12 07:12:43] Scheduler: MetricFetchE INFO: Because val_acc is available_while_running and trial 14 is still RUNNING continuing the experiment and retrying on next poll...
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:12:43] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.
[INFO 11-12 07:12:43] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:12:43] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 1).
[INFO 11-12 07:12:53] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:12:53] Scheduler: Fetching data for trials: [14] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:12:53] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.09994666666666667.
[INFO 11-12 07:12:53] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:12:53] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 1).
[INFO 11-12 07:13:03] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:13:03] Scheduler: Fetching data for trials: [14] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:13:03] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.09994666666666667.
[INFO 11-12 07:13:03] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:13:03] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 1).
[INFO 11-12 07:13:13] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:13:13] Scheduler: Fetching data for trials: [14] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:13:13] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.19994666666666666.
[INFO 11-12 07:13:13] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:13:13] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 1).
[INFO 11-12 07:13:23] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:13:23] Scheduler: Fetching data for trials: [14] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:13:23] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:13:23] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:13:23] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 1).
[INFO 11-12 07:13:33] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:13:33] Scheduler: Fetching data for trials: [14] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:13:33] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.29994666666666664.
[INFO 11-12 07:13:33] ax.early_stopping.strategies.base: No trials have reached 0.3. Not stopping any trials.
[INFO 11-12 07:13:33] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 1).
[INFO 11-12 07:13:43] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:13:43] Scheduler: Fetching data for trials: [14] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:13:43] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.3999466666666667.
[INFO 11-12 07:13:43] ax.early_stopping.strategies.percentile: Considering trial 14 for early stopping.
[INFO 11-12 07:13:43] ax.early_stopping.strategies.base: Last progression of Trial 14 is 0.3999466666666667.
[INFO 11-12 07:13:43] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.936018 2 0.963520 3 0.920868 4 0.922172 5 0.953899 6 0.951696 7 0.957647 8 0.949243 9 0.952378 10 0.947536 11 0.954991 12 0.952097 13 0.947849 14 0.959987 Name: 0.3999466666666667, dtype: float64.
[INFO 11-12 07:13:43] ax.early_stopping.strategies.percentile: Early stopping decision for 14: False. Reason: Trial objective value 0.9599872322505331 is better than 70.0-th percentile (0.9540084213458845) across comparable trials.
[INFO 11-12 07:13:43] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 1).
[INFO 11-12 07:13:53] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:13:53] Scheduler: Fetching data for trials: [14] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:13:53] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.49994666666666665.
[INFO 11-12 07:13:53] ax.early_stopping.strategies.percentile: Considering trial 14 for early stopping.
[INFO 11-12 07:13:53] ax.early_stopping.strategies.base: Last progression of Trial 14 is 0.49994666666666665.
[INFO 11-12 07:13:53] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935835 2 0.969378 3 0.927315 4 0.926094 5 0.959565 7 0.960080 11 0.958255 14 0.960118 Name: 0.49994666666666665, dtype: float64.
[INFO 11-12 07:13:53] ax.early_stopping.strategies.percentile: Early stopping decision for 14: False. Reason: Trial objective value 0.9601182803497167 is better than 70.0-th percentile (0.9600287514907659) across comparable trials.
[INFO 11-12 07:13:53] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 1).
[INFO 11-12 07:14:03] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:14:03] Scheduler: Fetching data for trials: [14] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:14:03] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.49994666666666665.
[INFO 11-12 07:14:03] ax.early_stopping.strategies.percentile: Considering trial 14 for early stopping.
[INFO 11-12 07:14:03] ax.early_stopping.strategies.base: Last progression of Trial 14 is 0.49994666666666665.
[INFO 11-12 07:14:03] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935835 2 0.969378 3 0.927315 4 0.926094 5 0.959565 7 0.960080 11 0.958255 14 0.960118 Name: 0.49994666666666665, dtype: float64.
[INFO 11-12 07:14:03] ax.early_stopping.strategies.percentile: Early stopping decision for 14: False. Reason: Trial objective value 0.9601182803497167 is better than 70.0-th percentile (0.9600287514907659) across comparable trials.
[INFO 11-12 07:14:03] Scheduler: Waiting for completed trials (for 10 sec, currently running trials: 1).
[INFO 11-12 07:14:13] Scheduler: No newly completed trials; not fetching data for any.
[INFO 11-12 07:14:13] Scheduler: Fetching data for trials: [14] because some metrics on experiment are available while trials are running.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( [INFO 11-12 07:14:13] ax.early_stopping.strategies.base: Last progression of any candidate for trial stopping is 0.5999466666666666.
[INFO 11-12 07:14:13] ax.early_stopping.strategies.percentile: Considering trial 14 for early stopping.
[INFO 11-12 07:14:13] ax.early_stopping.strategies.base: Last progression of Trial 14 is 0.5999466666666666.
[INFO 11-12 07:14:13] ax.early_stopping.strategies.percentile: Early stopping objective at last progression is: 1 0.935517 2 0.970626 3 0.928419 4 0.927635 5 0.963079 7 0.964297 14 0.964122 Name: 0.5999466666666666, dtype: float64.
[INFO 11-12 07:14:13] ax.early_stopping.strategies.percentile: Early stopping decision for 14: True. Reason: Trial objective value 0.9641224907178605 is worse than 70.0-th percentile (0.9641573406263241) across comparable trials.
[WARNING 11-12 07:14:14] Scheduler: Both `init_seconds_between_polls` and `early_stopping_strategy supplied. `init_seconds_between_polls=1` will be overrridden by `early_stopping_strategy.seconds_between_polls=10` and polling will take place at a constant rate.
CPU times: user 41.5 s, sys: 1.19 s, total: 42.7 s Wall time: 30min 26s
OptimizationResult()
First, we examine the data stored on the experiment. This shows that each trial is associated with an entire learning curve, represented by the column "steps".
experiment.lookup_data().map_df.head(n=10)
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
| arm_name | metric_name | mean | sem | trial_index | step | |
|---|---|---|---|---|---|---|
| 0 | 1_0 | val_acc | 0.907128 | NaN | 1 | 1874.0 |
| 1 | 1_0 | val_acc | 0.922183 | NaN | 1 | 3749.0 |
| 2 | 1_0 | val_acc | 0.928974 | NaN | 1 | 5624.0 |
| 3 | 1_0 | val_acc | 0.936018 | NaN | 1 | 7499.0 |
| 4 | 1_0 | val_acc | 0.935835 | NaN | 1 | 9374.0 |
| 5 | 1_0 | val_acc | 0.935517 | NaN | 1 | 11249.0 |
| 6 | 1_0 | val_acc | 0.935277 | NaN | 1 | 13124.0 |
| 7 | 1_0 | val_acc | 0.940825 | NaN | 1 | 14999.0 |
| 8 | 1_0 | val_acc | 0.941027 | NaN | 1 | 16874.0 |
| 9 | 1_0 | val_acc | 0.943604 | NaN | 1 | 18749.0 |
Below is a summary of the experiment, showing that a portion of trials have been early stopped.
exp_to_df(experiment)
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
| trial_index | arm_name | trial_status | generation_method | val_acc | hidden_size_1 | hidden_size_2 | learning_rate | dropout | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 0 | 0_0 | FAILED | Sobol | NaN | 22 | 88 | 0.000106 | 0.216444 |
| 1 | 1 | 1_0 | COMPLETED | Sobol | 0.944634 | 76 | 39 | 0.003148 | 0.397904 |
| 2 | 2 | 2_0 | COMPLETED | Sobol | 0.977170 | 128 | 64 | 0.000819 | 0.106932 |
| 3 | 3 | 3_0 | COMPLETED | Sobol | 0.930248 | 37 | 19 | 0.003680 | 0.288730 |
| 4 | 4 | 4_0 | COMPLETED | Sobol | 0.936426 | 27 | 57 | 0.001193 | 0.365074 |
| 5 | 5 | 5_0 | COMPLETED | Sobol | 0.970173 | 87 | 20 | 0.000261 | 0.061528 |
| 6 | 6 | 6_0 | EARLY_STOPPED | BoTorch | 0.951696 | 128 | 128 | 0.000113 | 0.000000 |
| 7 | 7 | 7_0 | EARLY_STOPPED | BoTorch | 0.962080 | 128 | 16 | 0.002402 | 0.000000 |
| 8 | 8 | 8_0 | EARLY_STOPPED | BoTorch | 0.949243 | 128 | 128 | 0.000100 | 0.228218 |
| 9 | 9 | 9_0 | EARLY_STOPPED | BoTorch | 0.952378 | 128 | 128 | 0.000100 | 0.020933 |
| 10 | 10 | 10_0 | EARLY_STOPPED | BoTorch | 0.947536 | 128 | 128 | 0.000100 | 0.249063 |
| 11 | 11 | 11_0 | EARLY_STOPPED | BoTorch | 0.958255 | 128 | 17 | 0.002358 | 0.000000 |
| 12 | 12 | 12_0 | EARLY_STOPPED | BoTorch | 0.952097 | 128 | 128 | 0.000100 | 0.018932 |
| 13 | 13 | 13_0 | EARLY_STOPPED | BoTorch | 0.947849 | 128 | 128 | 0.000100 | 0.247012 |
| 14 | 14 | 14_0 | EARLY_STOPPED | BoTorch | 0.964122 | 128 | 16 | 0.002298 | 0.000000 |
We can give a very rough estimate of the amount of computational savings due to early stopping, by looking at the total number of steps used when early stopping is used versus the number of steps used if we ran all trials to completion. Note to do a true comparison, one should run full HPO loops with and without early stopping (as early stopping will influence the model and future points selected by the generation strategy).
map_df = experiment.lookup_data().map_df
trial_to_max_steps = map_df.groupby("trial_index")["step"].max()
completed_trial_steps = trial_to_max_steps.iloc[0]
savings = 1.0 - trial_to_max_steps.sum() / (
completed_trial_steps * len(trial_to_max_steps)
)
# TODO format nicer
print(f"A rough estimate of the computational savings is {100 * savings}%.")
A rough estimate of the computational savings is 34.28914285714286%.
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
Finally, we show a visualization of learning curves versus actual elapsed wall time. This helps to illustrate that stopped trials make room for additional trials to be run.
# helper function for getting trial start times
def time_started(row):
trial_index = row["trial_index"]
return experiment.trials[trial_index].time_run_started
# helper function for getting trial completion times
def time_completed(row):
trial_index = row["trial_index"]
return experiment.trials[trial_index].time_completed
# helper function for getting relevant data from experiment
# with early stopping into useful dfs
def early_stopping_exp_to_df(experiment):
trials_df = exp_to_df(experiment)
curve_df = experiment.lookup_data().map_df
training_row_df = (
curve_df.groupby("trial_index").max().reset_index()[["trial_index", "steps"]]
)
trials_df = trials_df.merge(training_row_df, on="trial_index")
trials_df["time_started"] = trials_df.apply(func=time_started, axis=1)
trials_df["time_completed"] = trials_df.apply(func=time_completed, axis=1)
start_time = trials_df["time_started"].min()
trials_df["time_started_rel"] = (
trials_df["time_started"] - start_time
).dt.total_seconds()
trials_df["time_completed_rel"] = (
trials_df["time_completed"] - start_time
).dt.total_seconds()
return trials_df, curve_df
def plot_curves_by_wall_time(trials_df, curve_df):
trials = set(curve_df["trial_index"])
fig, ax = plt.subplots(1, 1, figsize=(10, 6))
ax.set(xlabel="seconds since start", ylabel="validation accuracy")
for trial_index in trials:
this_trial_df = curve_df[curve_df["trial_index"] == trial_index]
start_time_rel = trials_df["time_started_rel"].iloc[trial_index]
completed_time_rel = trials_df["time_completed_rel"].iloc[trial_index]
total_steps = trials_df.loc[trial_index, "steps"]
smoothed_curve = this_trial_df["mean"].rolling(window=3).mean()
x = (
start_time_rel
+ (completed_time_rel - start_time_rel)
/ total_steps
* this_trial_df["steps"]
)
ax.plot(
x,
smoothed_curve,
label=f"trial #{trial_index}" if trial_index % 2 == 1 else None,
)
ax.legend()
# wrap in try/except in case of flaky I/O issues
try:
trials_df, curve_df = early_stopping_exp_to_df(experiment)
plot_curves_by_wall_time(trials_df, curve_df)
except Exception as e:
print(f"Encountered exception while plotting results: {e}")
Encountered exception while plotting results: "['steps'] not in index"
/tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat( /tmp/tmp.Lx6ya87xsF/Ax-main/ax/core/map_data.py:195: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. df = pd.concat(
Total runtime of script: 30 minutes, 37.78 seconds.