113 lines
4.1 KiB
Python
113 lines
4.1 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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import io
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import platform
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import os
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from distutils.version import LooseVersion
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from typing import Union
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from pathlib import Path
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from urllib.parse import urlparse
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import torch
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import tensorboard
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from pytorch_lightning import _logger as log
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# we want this for tf.io.gfile, which if tf is installed gives full tf,
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# otherwise gives a pruned down version which works for some file backends but
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# not all
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from tensorboard.compat import tf
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gfile = tf.io.gfile
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pathlike = Union[Path, str]
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# older version of tensorboard had buggy gfile compatibility layers
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# only support remote cloud paths if newer
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def load(path_or_url: str, map_location=None):
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if urlparse(path_or_url).scheme == '' or Path(path_or_url).drive: # no scheme or with a drive letter
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return torch.load(path_or_url, map_location=map_location)
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return torch.hub.load_state_dict_from_url(path_or_url, map_location=map_location)
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def is_remote_path(path: pathlike):
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"""Determine if a path is a local path or a remote path like s3://bucket/path
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This should catch paths like s3:// hdfs:// and gcs://
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"""
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return "://" in str(path)
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def modern_gfile():
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"""Check the version number of tensorboard.
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Cheking to see if it has the gfile compatibility layers needed for remote
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file operations
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"""
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tb_version = LooseVersion(tensorboard.version.VERSION)
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modern_gfile = tb_version >= LooseVersion("2.0")
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return modern_gfile
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def cloud_open(path: pathlike, mode: str, newline: str = None):
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if platform.system() == "Windows":
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log.debug(
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"gfile does not handle newlines correctly on windows so remote files are not"
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" supported falling back to normal local file open."
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)
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return open(path, mode, newline=newline)
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if not modern_gfile():
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log.debug(
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"tenosrboard.compat gfile does not work on older versions "
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"of tensorboard for remote files, using normal local file open."
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)
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return open(path, mode, newline=newline)
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try:
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return gfile.GFile(path, mode)
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except NotImplementedError as e:
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# minimal dependencies are installed and only local files will work
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return open(path, mode, newline=newline)
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def makedirs(path: pathlike):
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if hasattr(gfile, "makedirs") and modern_gfile():
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if not gfile.exists(str(path)):
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return gfile.makedirs(str(path))
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# otherwise minimal dependencies are installed and only local files will work
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return os.makedirs(path, exist_ok=True)
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def atomic_save(checkpoint, filepath: str):
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"""Saves a checkpoint atomically, avoiding the creation of incomplete checkpoints.
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Args:
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checkpoint: The object to save.
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Built to be used with the ``dump_checkpoint`` method, but can deal with anything which ``torch.save``
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accepts.
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filepath: The path to which the checkpoint will be saved.
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This points to the file that the checkpoint will be stored in.
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"""
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bytesbuffer = io.BytesIO()
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# Can't use the new zipfile serialization for 1.6.0 because there's a bug in
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# torch.hub.load_state_dict_from_url() that prevents it from loading the new files.
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# More details can be found here: https://github.com/pytorch/pytorch/issues/42239
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if LooseVersion(torch.__version__).version[:3] == [1, 6, 0]:
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torch.save(checkpoint, bytesbuffer, _use_new_zipfile_serialization=False)
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else:
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torch.save(checkpoint, bytesbuffer)
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with cloud_open(filepath, 'wb') as f:
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f.write(bytesbuffer.getvalue())
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