tf.raw_ops.ReadVariableXlaSplitND

Splits resource variable input tensor across all dimensions.

tf.raw_ops.ReadVariableXlaSplitND(
    resource, T, N, num_splits, paddings=[], name=None
)

An op which splits the resource variable input tensor based on the given num_splits attribute, pads slices optionally, and returned the slices. Slices are returned in row-major order.

This op may be generated via the TPU bridge.

For example, with input tensor:

[[0, 1, 2],
 [3, 4, 5],
 [6, 7, 8]]

num_splits:

[2, 2]

and paddings:

[1, 1]

the expected outputs is:

[[0, 1],
 [3, 4]]
[[2, 0],
 [5, 0]]
[[6, 7],
 [0, 0]]
[[8, 0],
 [0, 0]]

resource A Tensor of type resource. Resource variable of input tensor to split across all dimensions. } out_arg { name: "outputs" description: <
T A tf.DType.
N An int that is >= 1.
num_splits A list of ints. Number of ways to split per dimension. Shape dimensions must be evenly divisible.
paddings An optional list of ints. Defaults to []. Optional list of right paddings per dimension of input tensor to apply before splitting. This can be used to make a dimension evenly divisible.
name A name for the operation (optional).

A list of N Tensor objects with type T.