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tf.distribute.experimental.partitioners.MaxSizePartitioner

Partitioner that keeps shards below max_shard_bytes.

Inherits From: Partitioner

This partitioner ensures each shard has at most max_shard_bytes, and tries to allocate as few shards as possible, i.e., keeping shard size as large as possible.

If the partitioner hits the max_shards limit, then each shard may end up larger than max_shard_bytes. By default max_shards equals None and no limit on the number of shards is enforced.

Examples:

partitioner = MaxSizePartitioner(max_shard_bytes=4)
partitions = partitioner(tf.TensorShape([6, 1]), tf.float32)
[6, 1]
partitioner = MaxSizePartitioner(max_shard_bytes=4, max_shards=2)
partitions = partitioner(tf.TensorShape([6, 1]), tf.float32)
[2, 1]
partitioner = MaxSizePartitioner(max_shard_bytes=1024)
partitions = partitioner(tf.TensorShape([6, 1]), tf.float32)
[1, 1]

# use in ParameterServerStrategy
# strategy = tf.distribute.experimental.ParameterServerStrategy(
#   cluster_resolver=cluster_resolver, variable_partitioner=partitioner)

max_shard_bytes The maximum size any given shard is allowed to be.
max_shards The maximum number of shards in int created taking precedence over max_shard_bytes.
bytes_per_string If the partition value is of type string, this provides an estimate of how large each string is.

Methods

__call__

View source

Partitions the given shape and returns the partition results.

Examples of a partitioner that allocates a fixed number of shards:

partitioner = FixedShardsPartitioner(num_shards=2)
partitions = partitioner(tf.TensorShape([10, 3], tf.float32), axis=0)
print(partitions) # [2, 0]

Args
shape a tf.TensorShape, the shape to partition.
dtype a tf.dtypes.Dtype indicating the type of the partition value.
axis The axis to partition along. Default: outermost axis.

Returns
A list of integers representing the number of partitions on each axis, where i-th value correponds to i-th axis.