tf.dynamic_partition

Partitions data into num_partitions tensors using indices from partitions.

View aliases

Compat aliases for migration

See Migration guide for more details.

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.