| View source on GitHub | 
Indicates when a distributed variable will be synced.
AUTO: Indicates that the synchronization will be determined by the current DistributionStrategy (eg. With MirroredStrategy this would be ON_WRITE).NONE: Indicates that there will only be one copy of the variable, so there is no need to sync.ON_WRITE: Indicates that the variable will be updated across devices every time it is written.ON_READ: Indicates that the variable will be aggregated across devices when it is read (eg. when checkpointing or when evaluating an op that uses the variable).
Example:
>>> temp_grad=[tf.Variable([0.], trainable=False, ... synchronization=tf.VariableSynchronization.ON_READ, ... aggregation=tf.VariableAggregation.MEAN ... )]
| Class Variables | |
|---|---|
| AUTO | <VariableSynchronization.AUTO: 0> | 
| NONE | <VariableSynchronization.NONE: 1> | 
| ON_READ | <VariableSynchronization.ON_READ: 3> | 
| ON_WRITE | <VariableSynchronization.ON_WRITE: 2> | 
    © 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/VariableSynchronization