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luojianing 提交于 2023-07-21 15:16 . replace target=blank

Function Differences with torch.any

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The following mapping relationships can be found in this file.

PyTorch APIs MindSpore APIs
torch.any mindspore.ops.any
torch.Tensor.any mindspore.Tensor.any

torch.any

torch.any(input, dim, keepdim=False, *, out=None) -> Tensor

For more information, see torch.any.

mindspore.ops.any

mindspore.ops.any(x, axis=(), keep_dims=False) -> Tensor

For more information, see mindspore.ops.any.

Differences

PyTorch: Perform logic OR on the elements of input according to the specified dim. keepdim controls whether the output and input have the same dimension. out can fetch the output.

MindSpore: Perform logic OR on the elements of x according to the specified axis. The keep_dims has the same function as PyTorch, and MindSpore does not have the out parameter. MindSpore has a default value for axis, and performs the logical OR on all elements of x if axis is the default.

Categories Subcategories PyTorch MindSpore Differences
Parameters Parameter 1 input x Same function, different parameter names
Parameter 2 dim axis PyTorch must pass dim and only one integer. MindSpore axis can be passed as an integer, a tuples of integers or a list of integers
Parameter 3 keepdim keep_dims Same function, different parameter names
Parameter 4 out - PyTorch out can get the output. MindSpore does not have this parameter

Code Example

# PyTorch
import torch

input = torch.tensor([[False, True, False, True], [False, True, False, False]])
print(torch.any(input, dim=0, keepdim=True))
# tensor([[False,  True, False,  True]])

# MindSpore
import mindspore

x = mindspore.Tensor([[False, True, False, True], [False, True, False, False]])
print(mindspore.ops.any(x, axis=0, keep_dims=True))
# [[False  True False  True]]
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