Differences with torch.Tensor.sum

torch.Tensor.sum

torch.Tensor.sum(dim=None, keepdim=False, dtype=None)

For more information, see torch.Tensor.sum.

mindspore.Tensor.sum

mindspore.Tensor.sum(axis=None, dtype=None, keepdims=False, initial=None)

For more information, see mindspore.Tensor.sum.

Differences

MindSpore API has the same function as that of PyTorch, but the number and order of parameters are not the same.

PyTorch: No parameter initial. The relative order of parameters keepdim and dtype is different from MindSpore.

MindSpore: The starting value of the summation can be configured with the parameter initial. The relative order of the parameters keepdim and dtype differs from that of PyTorch.

Categories	Subcategories	PyTorch	MindSpore	Differences
Parameters	Parameter 1	dim	axis	Both parameters have different names, and both indicate the specified dimension of the summation
	Parameter 2	keepdim	dtype	The relative order of `keepdim` and `dtype` are different
	Parameter 3	dtype	keepdims	The relative order of `keepdims` and `dtype` are different
	Parameter 4	-	initial	MindSpore can configure the starting value of the summation with the parameter `initial`, and PyTorch has no parameter `initial`.

Code Example# PyTorch
import torch

b = torch.Tensor([10, -5])
print(torch.Tensor.sum(b))
# tensor(5.)

# MindSpore
import mindspore as ms

a = ms.Tensor([10, -5], ms.float32)
print(a.sum())
# 5.0
print(a.sum(initial=2))
# 7.0