Differences with torch.randint_like

torch.randint_like

torch.randint_like(input, low=0, high, *, dtype=None, layout=torch.strided, device=None, requires_grad=False, memory_format=torch.preserve_format)

For more information, see torch.randint_like.

mindspore.ops.randint_like

mindspore.ops.randint_like(input, low, high, *, dtype=None, seed=None)

For more information, see mindspore.ops.randint_like.

Differences

PyTorch: low is an optional input, and the default value is 0.

MindSpore: low is a mandatory input with no default value.

Categories	Subcategories	PyTorch	MindSpore	Difference
Parameters	Parameter 1	input	input	No difference
	Parameter 2	low	low	low in PyTorch has a default value of 0, while low in MindSpore does not have a default value
	Parameter 3	high	high	No difference
	Parameter 4	dtype	dtype	No difference
	Parameter 5	layout	-	Common differences
	Parameter 6	device	-	Common differences
	Parameter 7	requires_grad	-	Common differences
	Parameter 8	memory_format	-	Common differences
	Parameter 9	-	seed	Common differences

Code Example

# PyTorch
import torch

# PyTorch does not need to input the value of low, which is equivalent to low=0 in MindSpore.
x = torch.tensor([[2, 3], [1, 2]], dtype=torch.int32)
y = torch.randint_like(x, 10)
print(tuple(y.shape))
# (2, 2)

# MindSpore
import mindspore

# MindSpore must take the default value of low in the torch (0 in this case) and pass it in as input.
x = mindspore.Tensor([[2, 3], [1, 2]], mindspore.int32)
x = mindspore.ops.randint_like(x, 0, 10)
print(x.shape)
# (2, 2)