tf.compat.v1.Variable

Indicates how a distributed variable will be aggregated.

tf.distribute.Strategy distributes a model by making multiple copies (called "replicas") acting data-parallel on different elements of the input batch. When performing some variable-update operation, say var.assign_add(x), in a model, we need to resolve how to combine the different values for x computed in the different replicas.

NONE: This is the default, giving an error if you use a variable-update operation with multiple replicas.
SUM: Add the updates across replicas.
MEAN: Take the arithmetic mean ("average") of the updates across replicas.
ONLY_FIRST_REPLICA: This is for when every replica is performing the same update, but we only want to perform the update once. Used, e.g., for the global step counter.
ONLY_FIRST_TOWER: Deprecated alias for ONLY_FIRST_REPLICA.

Class Variables
MEAN	`tf.compat.v1.VariableAggregation`
NONE	`tf.compat.v1.VariableAggregation`
ONLY_FIRST_REPLICA	`tf.compat.v1.VariableAggregation`
SUM	`tf.compat.v1.VariableAggregation`

TensorFlow

tf.compat / v1 / v1.Variable

Class Variables

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

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tf.debugging

tf.distribute

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tf.compat / v1 / v1.Variable

Class Variables