117 lines
4.7 KiB
Python
117 lines
4.7 KiB
Python
# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""General utilities."""
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import importlib
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import operator
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import platform
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import sys
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from importlib.util import find_spec
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from typing import Callable
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import pkg_resources
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import torch
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from packaging.version import Version
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from pkg_resources import DistributionNotFound
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def _module_available(module_path: str) -> bool:
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"""Check if a path is available in your environment.
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>>> _module_available('os')
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True
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>>> _module_available('bla.bla')
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False
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"""
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try:
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return find_spec(module_path) is not None
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except AttributeError:
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# Python 3.6
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return False
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except ModuleNotFoundError:
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# Python 3.7+
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return False
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def _compare_version(package: str, op: Callable, version: str, use_base_version: bool = False) -> bool:
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"""Compare package version with some requirements.
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>>> _compare_version("torch", operator.ge, "0.1")
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True
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"""
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try:
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pkg = importlib.import_module(package)
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except (ModuleNotFoundError, DistributionNotFound):
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return False
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try:
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if hasattr(pkg, "__version__"):
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pkg_version = Version(pkg.__version__)
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else:
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# try pkg_resources to infer version
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pkg_version = Version(pkg_resources.get_distribution(package).version)
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except TypeError:
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# this is mocked by Sphinx, so it should return True to generate all summaries
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return True
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if use_base_version:
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pkg_version = Version(pkg_version.base_version)
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return op(pkg_version, Version(version))
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_IS_WINDOWS = platform.system() == "Windows"
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_IS_INTERACTIVE = hasattr(sys, "ps1") # https://stackoverflow.com/a/64523765
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_TORCH_GREATER_EQUAL_1_8 = _compare_version("torch", operator.ge, "1.8.0")
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_TORCH_GREATER_EQUAL_1_8_1 = _compare_version("torch", operator.ge, "1.8.1")
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_TORCH_GREATER_EQUAL_1_9 = _compare_version("torch", operator.ge, "1.9.0")
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_TORCH_GREATER_EQUAL_1_10 = _compare_version("torch", operator.ge, "1.10.0")
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# _TORCH_GREATER_EQUAL_DEV_1_11 = _compare_version("torch", operator.ge, "1.11.0", use_base_version=True)
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_APEX_AVAILABLE = _module_available("apex.amp")
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_DEEPSPEED_AVAILABLE = _module_available("deepspeed")
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_FAIRSCALE_AVAILABLE = not _IS_WINDOWS and _module_available("fairscale.nn")
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_FAIRSCALE_OSS_FP16_BROADCAST_AVAILABLE = _FAIRSCALE_AVAILABLE and _compare_version("fairscale", operator.ge, "0.3.3")
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_FAIRSCALE_FULLY_SHARDED_AVAILABLE = _FAIRSCALE_AVAILABLE and _compare_version("fairscale", operator.ge, "0.3.4")
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_GROUP_AVAILABLE = not _IS_WINDOWS and _module_available("torch.distributed.group")
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_HOROVOD_AVAILABLE = _module_available("horovod.torch")
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_HYDRA_AVAILABLE = _module_available("hydra")
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_HYDRA_EXPERIMENTAL_AVAILABLE = _module_available("hydra.experimental")
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_JSONARGPARSE_AVAILABLE = _module_available("jsonargparse") and _compare_version("jsonargparse", operator.ge, "4.0.0")
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_KINETO_AVAILABLE = _TORCH_GREATER_EQUAL_1_8_1 and torch.profiler.kineto_available()
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_NEPTUNE_AVAILABLE = _module_available("neptune")
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_NEPTUNE_GREATER_EQUAL_0_9 = _NEPTUNE_AVAILABLE and _compare_version("neptune", operator.ge, "0.9.0")
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_OMEGACONF_AVAILABLE = _module_available("omegaconf")
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_POPTORCH_AVAILABLE = _module_available("poptorch")
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_RICH_AVAILABLE = _module_available("rich") and _compare_version("rich", operator.ge, "10.2.2")
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_TORCH_QUANTIZE_AVAILABLE = bool([eg for eg in torch.backends.quantized.supported_engines if eg != "none"])
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_TORCHTEXT_AVAILABLE = _module_available("torchtext")
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_TORCHTEXT_LEGACY: bool = _TORCHTEXT_AVAILABLE and _compare_version("torchtext", operator.lt, "0.11.0")
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_TORCHVISION_AVAILABLE = _module_available("torchvision")
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_XLA_AVAILABLE: bool = _module_available("torch_xla")
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from pytorch_lightning.utilities.xla_device import XLADeviceUtils # noqa: E402
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_TPU_AVAILABLE = XLADeviceUtils.tpu_device_exists()
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if _POPTORCH_AVAILABLE:
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import poptorch
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_IPU_AVAILABLE = poptorch.ipuHardwareIsAvailable()
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else:
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_IPU_AVAILABLE = False
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# experimental feature within PyTorch Lightning.
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def _fault_tolerant_training() -> bool:
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from pytorch_lightning.utilities.enums import _FaultTolerantMode
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return _FaultTolerantMode.detect_current_mode().is_enabled
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