tf.compat.v1.fixed_size_partitioner | TensorFlow v2.16.1 (original) (raw)

tf.compat.v1.fixed_size_partitioner

Partitioner to specify a fixed number of shards along given axis.

tf.compat.v1.fixed_size_partitioner(
    num_shards, axis=0
)

Migrate to TF2

This API is deprecated in TF2. In TF2, partitioner is no longer part of the variable declaration via tf.Variable.ParameterServer Traininghandles partitioning of variables. The corresponding TF2 partitioner class offixed_size_partitioner istf.distribute.experimental.partitioners.FixedShardsPartitioner.

Check the migration guideon the differences in treatment of variables and losses between TF1 and TF2.

Before:

  x = tf.compat.v1.get_variable(
    "x", shape=(2,), partitioner=tf.compat.v1.fixed_size_partitioner(2)
  )

After:

  partitioner = (
      tf.distribute.experimental.partitioners.FixedShardsPartitioner(
          num_shards=2)
  )
  strategy = tf.distribute.experimental.ParameterServerStrategy(
                 cluster_resolver=cluster_resolver,
                 variable_partitioner=partitioner)

  with strategy.scope():
    x = tf.Variable([1.0, 2.0])

Description

Args
num_shards	int, number of shards to partition variable.
axis	int, axis to partition on.

Returns
A partition function usable as the partitioner argument tovariable_scope and get_variable.

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Last updated 2024-04-26 UTC.