tensorflow:: ops:: DynamicPartition

Partitions data into num_partitions tensors using indices from partitions .

Summary

For each index tuple js of size partitions.ndim , the slice data[js, ...] becomes part of outputs[partitions[js]] . The slices with partitions[js] = i are placed in outputs[i] in lexicographic order of js , and the first dimension of outputs[i] is the number of entries in partitions equal to i . In detail,

    outputs[i].shape = [sum(partitions == i)] + data.shape[partitions.ndim:]

    outputs[i] = pack([data[js, ...] for js if partitions[js] == i])

data.shape must start with partitions.shape .

For example:

    # Scalar partitions.
    partitions = 1
    num_partitions = 2
    data = [10, 20]
    outputs[0] = []  # Empty with shape [0, 2]
    outputs[1] = [[10, 20]]

    # Vector partitions.
    partitions = [0, 0, 1, 1, 0]
    num_partitions = 2
    data = [10, 20, 30, 40, 50]
    outputs[0] = [10, 20, 50]
    outputs[1] = [30, 40]

See dynamic_stitch for an example on how to merge partitions back.

Args:

• scope: A Scope object
• partitions: Any shape. Indices in the range [0, num_partitions) .
• num_partitions: The number of partitions to output.

Returns:

• OutputList : The outputs tensor.

Public attributes

Operation operation

::tensorflow::OutputList outputs

Public functions

 DynamicPartition(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input data,
  ::tensorflow::Input partitions,
  int64 num_partitions
)

::tensorflow::Output operator[](
  size_t index
) const