Source code for ax.exceptions.generation_strategy

#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.

# pyre-strict


from ax.exceptions.core import AxError, OptimizationComplete


[docs] class AxGenerationException(AxError): """Raised when there is an issue with the generation strategy.""" pass
[docs] class MaxParallelismReachedException(AxGenerationException): """Special exception indicating that maximum number of trials running in parallel set on a given step (as `GenerationStep.max_parallelism`) has been reached. Upon getting this exception, users should wait until more trials are completed with data, to generate new trials. """ def __init__( self, model_name: str, num_running: int, step_index: int | None = None, node_name: str | None = None, ) -> None: if node_name is not None: msg_start = ( f"Maximum parallelism for generation node #{node_name} ({model_name})" ) else: msg_start = ( f"Maximum parallelism for generation step #{step_index} ({model_name})" ) super().__init__( msg_start + f" has been reached: {num_running} trials are currently 'running'. Some " "trials need to be completed before more trials can be generated. See " "https://ax.dev/docs/bayesopt.html to understand why limited parallelism " "improves performance of Bayesian optimization." )
[docs] class GenerationStrategyCompleted(OptimizationComplete): """Special exception indicating that the generation strategy has been completed. """ pass
[docs] class GenerationStrategyRepeatedPoints(GenerationStrategyCompleted): """Special exception indicating that the generation strategy is repeatedly suggesting previously sampled points. """ pass
[docs] class GenerationStrategyMisconfiguredException(AxGenerationException): """Special exception indicating that the generation strategy is misconfigured.""" def __init__(self, error_info: str | None) -> None: super().__init__( "This GenerationStrategy was unable to be initialized properly. Please " + "check the documentation, and adjust the configuration accordingly. " + f"{error_info}" )
[docs] class OptimizationConfigRequired(ValueError): """Error indicating that candidate generation cannot be completed because an optimization config was not provided.""" pass