tf.dynamic_partition  |  TensorFlow v2.16.1 (original) (raw)

tf.dynamic_partition

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Partitions data into num_partitions tensors using indices from partitions.

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Compat aliases for migration

SeeMigration guide for more details.

tf.compat.v1.dynamic_partition

tf.dynamic_partition(
    data: Annotated[Any, TV_DynamicPartition_T],
    partitions: Annotated[Any, _atypes.Int32],
    num_partitions: int,
    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] = iare 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.