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.

# Returns:

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