tf.dynamic_partition()

• 2019 年 11 月 27 日
• 筆記

Defined in generated file: python/ops/gen_data_flow_ops.py

Partitions data into num_partitions tensors using indices from partitions.

Aliases:

• tf.compat.v1.dynamic_partition
• tf.compat.v2.dynamic_partition

tf.dynamic_partition(      data,      partitions,      num_partitions,      name=None  )

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:

• data: A Tensor.
• partitions: A Tensor of type int32. Any shape. Indices in the range [0, num_partitions).
• num_partitions: An int that is >= 1. The number of partitions to output.
• name: A name for the operation (optional).

Returns:

A list of num_partitions Tensor objects with the same type as data.