Source code for ax.utils.testing.torch_stubs

#!/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 __future__ import annotations

from typing import Any, Dict, List, Optional, Tuple

import torch


[docs]def get_torch_test_data( dtype: torch.dtype = torch.float, cuda: bool = False, constant_noise: bool = True, task_features: Optional[List[int]] = None, offset: float = 0.0, ) -> Tuple[ List[torch.Tensor], List[torch.Tensor], List[torch.Tensor], List[Tuple[float, float]], List[int], List[str], List[str], ]: tkwargs: Dict[str, Any] = { "device": torch.device("cuda" if cuda else "cpu"), "dtype": dtype, } Xs = [ torch.tensor( [ [1.0 + offset, 2.0 + offset, 3.0 + offset], [2.0 + offset, 3.0 + offset, 4.0 + offset], ], **tkwargs, ) ] Ys = [torch.tensor([[3.0 + offset], [4.0 + offset]], **tkwargs)] Yvars = [torch.tensor([[0.0 + offset], [2.0 + offset]], **tkwargs)] 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"] return Xs, Ys, Yvars, bounds, task_features, feature_names, metric_names