Function Differences with torch.nn.init.constant_

torch.nn.init.constant_

torch.nn.init.constant_(
    tensor,
    val
)

For more information, see torch.nn.init.constant_.

mindspore.common.initializer.Constant

class mindspore.common.initializer.Constant(value)(arr)

For more information, see mindspore.common.initializer.Constant.

Differences

PyTorch: Fills in the input tensor with constant val.

MindSpore：Fills in a constant array with value(int or numpy array) and update-in-place for the input.

Code Example

import mindspore
import torch
import numpy as np

# In MindSpore, fill a constant array with value(int or numpy array).
input_constant = np.array([1, 2, 3])
constant_init = mindspore.common.initializer.Constant(value=1)
out_constant = constant_init(input_constant)
print(input_constant)
# Out：
# [1 1 1]

# In torch, fill in the input tensor with constant val.
input_constant = np.array([1, 2, 3])
out_constant = torch.nn.init.constant_(
    tensor=torch.tensor(input_constant),
    val=1
)
print(out_constant)
# Out：
# tensor([1, 1, 1])