tf.raw_ops.ReadVariableXlaSplitND | TensorFlow v2.16.1 (original) (raw)
Splits resource variable input tensor across all dimensions.
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Compat aliases for migration
SeeMigration guide for more details.
tf.compat.v1.raw_ops.ReadVariableXlaSplitND
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]]
Args | |
---|---|
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). |
Returns |
---|
A list of N Tensor objects with type T. |