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tf.min_max_variable_partitioner

tf.min_max_variable_partitioner(
    max_partitions=1,
    axis=0,
    min_slice_size=(256 << 10),
    bytes_per_string_element=16
)

Defined in tensorflow/python/ops/partitioned_variables.py.

See the guide: Variables > Variable Partitioners for Sharding

Partitioner to allocate minimum size per slice.

Returns a partitioner that partitions the variable of given shape and dtype such that each partition has a minimum of min_slice_size slice of the variable. The maximum number of such partitions (upper bound) is given by max_partitions.

Args:

  • max_partitions: Upper bound on the number of partitions. Defaults to 1.
  • axis: Axis along which to partition the variable. Defaults to 0.
  • min_slice_size: Minimum size of the variable slice per partition. Defaults to 256K.
  • bytes_per_string_element: If the Variable is of type string, this provides an estimate of how large each scalar in the Variable is.

Returns:

A partition function usable as the partitioner argument to variable_scope, get_variable, and get_partitioned_variable_list.

© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/min_max_variable_partitioner