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86 lines
2.3 KiB
Python
86 lines
2.3 KiB
Python
# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
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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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# ==============================================================================
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"""Context for saving checkpoint."""
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import contextlib
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import threading
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class PreemptionSaveContext(threading.local):
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"""A context for saving checkpoint upon preemption."""
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def __init__(self):
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super().__init__()
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self._in_preemption_save_context = False
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def enter_preemption_save_context(self):
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self._in_preemption_save_context = True
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def exit_preemption_save_context(self):
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self._in_preemption_save_context = False
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def in_preemption_save_context(self):
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return self._in_preemption_save_context
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_preemption_save_context = PreemptionSaveContext()
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@contextlib.contextmanager
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def preemption_save_context():
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_preemption_save_context.enter_preemption_save_context()
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try:
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yield
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finally:
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_preemption_save_context.exit_preemption_save_context()
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def in_preemption_save_context():
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return _preemption_save_context.in_preemption_save_context()
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class AsyncMetricsContext(threading.local):
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"""A context for controlling metrics recording when async checkpoint is used.
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"""
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def __init__(self):
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super().__init__()
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self._in_async_metrics_context = False
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def enter_async_metrics_context(self):
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self._in_async_metrics_context = True
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def exit_async_metrics_context(self):
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self._in_async_metrics_context = False
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def in_async_metrics_context(self):
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return self._in_async_metrics_context
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_async_metrics_context = AsyncMetricsContext()
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@contextlib.contextmanager
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def async_metrics_context():
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_async_metrics_context.enter_async_metrics_context()
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try:
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yield
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finally:
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_async_metrics_context.exit_async_metrics_context()
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def in_async_metrics_context():
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return _async_metrics_context.in_async_metrics_context()
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