Source code for ax.models.random.uniform
#!/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
import numpy as np
import numpy.typing as npt
from ax.models.random.base import RandomModel
[docs]
class UniformGenerator(RandomModel):
"""This class specifies a uniform random generation algorithm.
As a uniform generator does not make use of a model, it does not implement
the fit or predict methods.
See base `RandomModel` for a description of model attributes.
"""
def __init__(
self,
deduplicate: bool = True,
seed: int | None = None,
init_position: int = 0,
generated_points: npt.NDArray | None = None,
fallback_to_sample_polytope: bool = False,
) -> None:
super().__init__(
deduplicate=deduplicate,
seed=seed,
init_position=init_position,
generated_points=generated_points,
fallback_to_sample_polytope=fallback_to_sample_polytope,
)
self._rs = np.random.RandomState(seed=self.seed)
if self.init_position > 0:
# Fast-forward the random state by generating & discarding samples.
self._rs.uniform(size=(self.init_position))
def _gen_samples(self, n: int, tunable_d: int) -> npt.NDArray:
"""Generate samples from the scipy uniform distribution.
Args:
n: Number of samples to generate.
tunable_d: Dimension of samples to generate.
Returns:
samples: An (n x d) array of random points.
"""
self.init_position += n * tunable_d
return self._rs.uniform(size=(n, tunable_d))