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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

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mindspore.numpy.split

mindspore.numpy.split(x, indices_or_sections, axis=0)

Splits a tensor into multiple sub-tensors along the given axis.

Parameters

• x (Tensor) – A Tensor to be divided.

• indices_or_sections (Union[int, tuple(int), list(int)]) – If integer, $N$, the tensor will be divided into $N$ equal tensors along axis. If tuple(int), list(int) or of sorted integers, the entries indicate where along axis the array is split. For example, $[2,3]$ would, for $axis=0$, result in three sub-tensors $x[:2]$, $x[2:3]$ and $x[3:]$. If an index exceeds the dimension of the array along axis, an empty sub-array is returned correspondingly.

• axis (int, optional) – The axis along which to split. Default: 0 .

Returns

A tuple of sub-tensors.

Raises

• TypeError – If argument indices_or_sections is not integer, tuple(int) or list(int) or argument axis is not integer.

• ValueError – If argument axis is out of range of $[-x.ndim,x.ndim)$.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore.numpy as np
>>> input_x = np.arange(9).astype("float32")
>>> output = np.split(input_x, 3)
>>> print(output)
(Tensor(shape=[3], dtype=Float32,
  value= [ 0.00000000e+00,  1.00000000e+00,  2.00000000e+00]),
 Tensor(shape=[3], dtype=Float32,
  value= [ 3.00000000e+00,  4.00000000e+00,  5.00000000e+00]),
 Tensor(shape=[3], dtype=Float32,
  value= [ 6.00000000e+00,  7.00000000e+00,  8.00000000e+00]))