Differences with torch.linspace

torch.linspace

torch.linspace(start,
               end,
               steps,
               *,
               out=None,
               dtype=None,
               layout=torch.strided,
               device=None,
               requires_grad=False
              )

For more information, see torch.linspace.

mindspore.ops.linspace

mindspore.ops.linspace(start,
                       end,
                       steps
                      )

For more information, see mindspore.ops.linspace.

Differences

API function of MindSpore is consistent with that of PyTorch.

MindSpore: The dtype of output Tensor is the same as the parameter start.

PyTorch: the dtype of output Tensor is determined by the parameter dtype.

Categories	Subcategories	PyTorch	MindSpore	Difference
input	input 1	start	start	The data type of start parameter in MindSpore is Union[Tensor, int, float], while the data type of start parameter in PyTorch is float
	input 2	end	end	The data type of end parameter in MindSpore is Union[Tensor, int, float], while the data type of end parameter in PyTorch is float
	input 3	steps	steps	The data type of steps parameter in MindSpore is Union[Tensor, int], while the data type of steps parameter in PyTorch is int
	input 4	out	-	For details, see General Difference Parameter Table
	input 5	dtype	-	The dtype of output Tensor in MindSpore is the same as the parameter start，while the dtype of output Tensor in PyTorch is determined by the parameter dtype
	input 6	layout	-	For details, see General Difference Parameter Table
	input 7	device	-	For details, see General Difference Parameter Table
	input 8	requires_grad	-	For details, see General Difference Parameter Table

Code Example

# PyTorch
import torch

output = torch.linspace(1, 10, 5, dtype=torch.float32)
print(output)
# tensor([1.0000, 3.2500, 5.5000, 7.7500, 10.0000])

# MindSpore
import mindspore as ms
from mindspore import Tensor, ops

start = Tensor(1, ms.float32)
limit = Tensor(10, ms.float32)
delta = Tensor(5, ms.int32)
output = ops.linspace(start, limit, delta)
print(output)
# [1. 3.25 5.5 7.75 10.]