def variable_accessed(variable):
"""Notifies all tapes in the stack that a variable has been accessed.
Args:
variable: variable to be watched.
"""
strategy = distribution_strategy_context.get_distribution_strategy()
if distribution_strategy_context.get_replica_context():
variables = [strategy.value_container(variable)]
else:
variables = strategy.unwrap(variable)
for var in variables:
pywrap_tensorflow.TFE_Py_TapeVariableAccessed(var)
def variable_accessed(variable):
"""Notifies all tapes in the stack that a variable has been accessed.
Args:
variable: variable to be watched.
"""
strategy, context = (
distribution_strategy_context.get_strategy_and_replica_context())
if context:
variables = [strategy.extended.value_container(variable)]
else:
variables = strategy.experimental_local_results(variable)
for var in variables:
pywrap_tensorflow.TFE_Py_TapeVariableAccessed(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.
"""
strategy, context = (
distribution_strategy_context.get_strategy_and_replica_context())
accessed = []
if context:
accessed = [strategy.extended.value_container(variable)
for variable in variables if variable.trainable]
else:
for variable in variables:
if variable.trainable:
accessed.extend(strategy.experimental_local_results(variable))
for var in accessed:
pywrap_tensorflow.TFE_Py_TapeVariableAccessed(var)
def variable_accessed(variable):
"""Notifies all tapes in the stack that a variable has been accessed."""
pywrap_tensorflow.TFE_Py_TapeVariableAccessed(variable)