mindspore.ops.dsplit

mindspore.ops.dsplit(input, indices_or_sections)

жІҝ第дёүиҪҙеҲҶеүІиҫ“е…ҘtensorгҖӮзӯүеҗҢдәҺ \(axis=2\) ж—¶зҡ„ ops.tensor_split гҖӮ

еҸӮж•°пјҡ

• input (Tensor) - еҫ…еҲҶеүІзҡ„tensorгҖӮ

• indices_or_sections (Union[int, tuple(int), list(int)]) - еҸӮиҖғ mindspore.ops.tensor_split() дёӯзҡ„indices_or_sectionsеҸӮж•°гҖӮ

иҝ”еӣһпјҡ

еӨҡдёӘtensorз»„жҲҗзҡ„tupleгҖӮ

ж”ҜжҢҒе№іеҸ°пјҡ

Ascend GPU CPU

ж ·дҫӢпјҡ

>>> import mindspore
>>> input = vpn梯子 免费 mindspore.ops.arange(16.0).reshape(2, 2, 4)
>>> print(input)
[[[ 0.  1.  2.  3.]
  [ 4.  5. vpn梯子 免费  6.  7.]]
 [[ 8.  9. 10. 11.]
  [12. 13. 免费的vpn梯子 14. 15.]]]
>>> output = mindspore.ops.dsplit(input, 2)
>>> print(output)
(Tensor(shape=[2, vpn free 2, 2], dtype=Float32, value=
[[[ 0.00000000e+00,  1.00000000e+00],
  [ 4.00000000e+00,  5.00000000e+00]],
 [[ 8.00000000e+00,  9.00000000e+00],
  [ 1.20000000e+01,  1.30000000e+01]]]), Tensor(shape=[2, 2, 2], dtype=Float32, value=
[[[ 2.00000000e+00,  3.00000000e+00],
  [ 6.00000000e+00,  7.00000000e+00]],
 [[ 1.00000000e+01,  vpn梯子 1.10000000e+01],
  [ 1.40000000e+01,  1.50000000e+01]]]))
>>> vpn梯子 免费 output = mindspore.ops.dsplit(input, [3, 6])
>>> print(output)
(Tensor(shape=[2, 2, 3], dtype=Float32, value=
[[[ 0.00000000e+00,  1.00000000e+00,  2.00000000e+00],
  [ 4.00000000e+00,  5.00000000e+00,  6.00000000e+00]],
 vpn梯子 免费 [[ 8.00000000e+00,  9.00000000e+00,  vpn梯子 1.00000000e+01],
  [ 1.20000000e+01, 免费的vpn梯子  1.30000000e+01,  vpn free 1.40000000e+01]]]), Tensor(shape=[2, 2, 1], dtype=Float32, value=
[[[ 3.00000000e+00],
  [ 7.00000000e+00]],
 [[ 1.10000000e+01],
  [ 1.50000000e+01]]]), Tensor(shape=[2, 2, 0], dtype=Float32, value=
))