mindspore.ops.dsplit

mindspore.ops.dsplit(input, indices_or_sections)[source]

Splits a tensor into multiple sub-tensors along the 3rd axis. It is equivalent to ops.tensor_split with \(axis=2\) .

Parameters

input (Tensor) – A Tensor to be divided.
indices_or_sections (Union[int, tuple(int), list(int)]) – See argument in mindspore.ops.tensor_split().

Returns

A list of sub-tensors.

Supported Platforms:: Ascend GPU CPU

Examples

>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> input_x = np.arange(6).reshape((1, 2, 3)).astype('float32')
>>> output = ops.dsplit(Tensor(input_x), 3)
>>> print(output)
(Tensor(shape=[1, 2, 1], dtype=Float32, value=[[[ 0.00000000e+00], [ 3.00000000e+00]]]),
 Tensor(shape=[1, 2, 1], dtype=Float32, value=[[[ 1.00000000e+00], [ 4.00000000e+00]]]),
 Tensor(shape=[1, 2, 1], dtype=Float32, value=[[[ 2.00000000e+00], [ 5.00000000e+00]]]))