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| import os | |
| from distutils.version import LooseVersion | |
| import pkg_resources | |
| from mlagents.torch_utils import cpu_utils | |
| from mlagents.trainers.settings import TorchSettings | |
| from mlagents_envs.logging_util import get_logger | |
| logger = get_logger(__name__) | |
| def assert_torch_installed(): | |
| # Check that torch version 1.6.0 or later has been installed. If not, refer | |
| # user to the PyTorch webpage for install instructions. | |
| torch_pkg = None | |
| try: | |
| torch_pkg = pkg_resources.get_distribution("torch") | |
| except pkg_resources.DistributionNotFound: | |
| pass | |
| assert torch_pkg is not None and LooseVersion(torch_pkg.version) >= LooseVersion( | |
| "1.6.0" | |
| ), ( | |
| "A compatible version of PyTorch was not installed. Please visit the PyTorch homepage " | |
| + "(https://pytorch.org/get-started/locally/) and follow the instructions to install. " | |
| + "Version 1.6.0 and later are supported." | |
| ) | |
| assert_torch_installed() | |
| # This should be the only place that we import torch directly. | |
| # Everywhere else is caught by the banned-modules setting for flake8 | |
| import torch # noqa I201 | |
| torch.set_num_threads(cpu_utils.get_num_threads_to_use()) | |
| os.environ["KMP_BLOCKTIME"] = "0" | |
| _device = torch.device("cpu") | |
| def set_torch_config(torch_settings: TorchSettings) -> None: | |
| global _device | |
| if torch_settings.device is None: | |
| device_str = "cuda" if torch.cuda.is_available() else "cpu" | |
| else: | |
| device_str = torch_settings.device | |
| _device = torch.device(device_str) | |
| if _device.type == "cuda": | |
| torch.set_default_tensor_type(torch.cuda.FloatTensor) | |
| else: | |
| torch.set_default_tensor_type(torch.FloatTensor) | |
| logger.debug(f"default Torch device: {_device}") | |
| # Initialize to default settings | |
| set_torch_config(TorchSettings(device=None)) | |
| nn = torch.nn | |
| def default_device(): | |
| return _device | |