wehub-resource-sync
54 lines
2.1 KiB
Python
54 lines
2.1 KiB
Python
# Copyright 2020 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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"""Experimental impl for GradientTape using unified APIs, for testing only."""
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from tensorflow.python.framework.experimental import _tape
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from tensorflow.python.framework.experimental import context_stack
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from tensorflow.python.framework.experimental import gradient_registry
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from tensorflow.python.util import nest
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class GradientTape(object):
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"""GradientTape using the unified API."""
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def __init__(self, persistent=False):
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self._c_tape = _tape.Tape(persistent)
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ctx = context_stack.get_default()
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self._tape_context = _tape.TapeContext(
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ctx, self._c_tape, gradient_registry.get_global_registry())
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self._ctx_manager = None
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def watch(self, t):
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self._c_tape.Watch(t)
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# TODO(srbs): Add support for unconnected_gradients.
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def gradient(self, targets, sources, output_gradients=None):
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ctx = context_stack.get_default()
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flat_targets = nest.flatten(targets)
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flat_sources = nest.flatten(sources)
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out_grads = self._c_tape.ComputeGradient(ctx, flat_targets, flat_sources,
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output_gradients or [])
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return nest.pack_sequence_as(sources, out_grads)
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def __enter__(self):
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"""Enters a context inside which operations are recorded on this tape."""
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self._ctx_manager = context_stack.set_default(self._tape_context)
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self._ctx_manager.__enter__()
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return self
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def __exit__(self, typ, value, traceback):
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self._ctx_manager.__exit__(typ, value, traceback)
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self._ctx_manager = None
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