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