wehub-resource-sync
85 lines
3.4 KiB
Python
85 lines
3.4 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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"""Toggle to enable/disable resource variables."""
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from tensorflow.python import tf2
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from tensorflow.python.eager import monitoring
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from tensorflow.python.platform import tf_logging as logging
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from tensorflow.python.util import deprecation
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from tensorflow.python.util.tf_export import tf_export
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_api_usage_gauge = monitoring.BoolGauge(
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"/tensorflow/api/resource_variables",
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"Whether resource_variables_toggle.enable_resource_variables() is called.")
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_DEFAULT_USE_RESOURCE = tf2.enabled()
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@tf_export(v1=["enable_resource_variables"])
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def enable_resource_variables() -> None:
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"""Creates resource variables by default.
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Resource variables are improved versions of TensorFlow variables with a
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well-defined memory model. Accessing a resource variable reads its value, and
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all ops which access a specific read value of the variable are guaranteed to
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see the same value for that tensor. Writes which happen after a read (by
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having a control or data dependency on the read) are guaranteed not to affect
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the value of the read tensor, and similarly writes which happen before a read
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are guaranteed to affect the value. No guarantees are made about unordered
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read/write pairs.
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Calling tf.enable_resource_variables() lets you opt-in to this TensorFlow 2.0
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feature.
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"""
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global _DEFAULT_USE_RESOURCE
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_DEFAULT_USE_RESOURCE = True
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logging.vlog(1, "Enabling resource variables")
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_api_usage_gauge.get_cell().set(True)
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@deprecation.deprecated(
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None, "non-resource variables are not supported in the long term")
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@tf_export(v1=["disable_resource_variables"])
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def disable_resource_variables() -> None:
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"""Opts out of resource variables.
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If your code needs tf.disable_resource_variables() to be called to work
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properly please file a bug.
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"""
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global _DEFAULT_USE_RESOURCE
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_DEFAULT_USE_RESOURCE = False
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logging.vlog(1, "Disabling resource variables")
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_api_usage_gauge.get_cell().set(False)
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@tf_export(v1=["resource_variables_enabled"])
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def resource_variables_enabled() -> bool:
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"""Returns `True` if resource variables are enabled.
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Resource variables are improved versions of TensorFlow variables with a
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well-defined memory model. Accessing a resource variable reads its value, and
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all ops which access a specific read value of the variable are guaranteed to
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see the same value for that tensor. Writes which happen after a read (by
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having a control or data dependency on the read) are guaranteed not to affect
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the value of the read tensor, and similarly writes which happen before a read
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are guaranteed to affect the value. No guarantees are made about unordered
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read/write pairs.
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Calling tf.enable_resource_variables() lets you opt-in to this TensorFlow 2.0
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feature.
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"""
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return _DEFAULT_USE_RESOURCE
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