mindspore.ops.vsplit

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

Splits input with two or more dimensions, into multiple sub-tensors vertically according to indices_or_sections.

It is equivalent to ops.tensor_split with \(axis=0\) .

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(9).reshape((3, 3)).astype('float32')
>>> output = ops.vsplit(Tensor(input_x), 3)
>>> print(output)
(Tensor(shape=[1, 3], dtype=Float32, value=[[ 0.00000000e+00,  1.00000000e+00,  2.00000000e+00]]),
 Tensor(shape=[1, 3], dtype=Float32, value=[[ 3.00000000e+00,  4.00000000e+00,  5.00000000e+00]]),
 Tensor(shape=[1, 3], dtype=Float32, value=[[ 6.00000000e+00,  7.00000000e+00,  8.00000000e+00]]))