Source code for ax.utils.testing.torch_stubs

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

from __future__ import annotations

from typing import Dict

import torch


[docs]def get_optimizer_kwargs() -> Dict[str, int]: return {"num_restarts": 2, "raw_samples": 2, "maxiter": 2, "batch_limit": 1}
[docs]def get_torch_test_data( dtype=torch.float, cuda=False, constant_noise=True, task_features=None, offset=0.0 ): device = torch.device("cuda") if cuda else torch.device("cpu") Xs = [ torch.tensor( [ [1.0 + offset, 2.0 + offset, 3.0 + offset], [2.0 + offset, 3.0 + offset, 4.0 + offset], ], dtype=dtype, device=device, ) ] Ys = [torch.tensor([[3.0 + offset], [4.0 + offset]], dtype=dtype, device=device)] Yvars = [torch.tensor([[0.0 + offset], [2.0 + offset]], dtype=dtype, device=device)] if constant_noise: Yvars[0].fill_(1.0) bounds = [ (0.0 + offset, 1.0 + offset), (1.0 + offset, 4.0 + offset), (2.0 + offset, 5.0 + offset), ] feature_names = ["x1", "x2", "x3"] task_features = [] if task_features is None else task_features metric_names = ["y", "r"] return Xs, Ys, Yvars, bounds, task_features, feature_names, metric_names