3RNN/Lib/site-packages/tensorflow/python/eager/tape.py
2024-05-26 19:49:15 +02:00

110 lines
3.4 KiB
Python

# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Gradient tape utilities."""
from tensorflow.python import pywrap_tfe
class Tape(object):
"""Represents a gradient propagation trace."""
__slots__ = ["_tape"]
def __init__(self, tape):
self._tape = tape
def watched_variables(self):
return pywrap_tfe.TFE_Py_TapeWatchedVariables(self._tape)
def push_new_tape(persistent=False, watch_accessed_variables=True):
"""Pushes a new tape onto the tape stack."""
tape = pywrap_tfe.TFE_Py_TapeSetNew(persistent, watch_accessed_variables)
return Tape(tape)
def push_tape(tape):
"""Pushes an existing tape onto the tape stack."""
pywrap_tfe.TFE_Py_TapeSetAdd(tape._tape) # pylint: disable=protected-access
def watch(tape, tensor):
"""Marks this tensor to be watched by the given tape."""
pywrap_tfe.TFE_Py_TapeWatch(tape._tape, tensor) # pylint: disable=protected-access
def default_get_variables(variable):
return [variable]
# Gets a list of changed variables. Can be overriden using
# register_variables_override. An example of overriding is for getting the
# varibles within a distributed context.
_variables_override = default_get_variables
def register_watched_variable_resolver(resolver):
"""Registers the resolver to be used to get the list of variables to watch.
Args:
resolver: callable, takes a Variable and returns a list of Variables that
shall be watched.
"""
global _variables_override
assert _variables_override is default_get_variables
_variables_override = resolver
def watch_variable(tape, variable):
"""Marks this variable to be watched by the given tape."""
variables = _variables_override(variable)
for var in variables:
pywrap_tfe.TFE_Py_TapeWatchVariable(tape._tape, var) # pylint: disable=protected-access
pywrap_tfe.TFE_Py_VariableWatcherVariableAccessed(var)
def variable_accessed(variable):
"""Notifies all tapes in the stack that a variable has been accessed.
Args:
variable: variable to be watched.
"""
variables = _variables_override(variable)
for var in variables:
pywrap_tfe.TFE_Py_TapeVariableAccessed(var)
pywrap_tfe.TFE_Py_VariableWatcherVariableAccessed(var)
def variables_accessed(variables):
"""Notifies all tapes in the stack that variables have been accessed.
Only trainable variables are marked as accessed.
Args:
variables: iterable of variables to mark as accessed.
"""
accessed = []
for variable in variables:
if variable.trainable:
accessed.extend(_variables_override(variable))
for var in accessed:
pywrap_tfe.TFE_Py_TapeVariableAccessed(var)
pywrap_tfe.TFE_Py_VariableWatcherVariableAccessed(var)
def pop_tape(tape):
"""Pops the given tape in the stack."""
pywrap_tfe.TFE_Py_TapeSetRemove(tape._tape) # pylint: disable=protected-access