比较torch.nn.Dropout与mindspore.nn.Dropout的功能差异

查看源文件

torch.nn.Dropout

class torch.nn.Dropout(
    p=0.5,
    inplace=False
)

更多内容详见torch.nn.Dropout。

mindspore.nn.Dropout

class mindspore.nn.Dropout(
    keep_prob=0.5,
    dtype=mstype.float
)

更多内容详见mindspore.nn.Dropout。

使用方式

PyTorch中P参数为丢弃参数的概率。

MindSpore中keep_prob参数为保留参数的概率。

代码示例

# The following implements Dropout with MindSpore.
import torch.nn
import mindspore.nn
import numpy as np

m = torch.nn.Dropout(p=0.9)
input = torch.tensor(np.ones([5,5]),dtype=float)
output = m(input)
print(output)

# out:
#   [[0 10 0 0 0]
#   [0 0 0 0 0]
#   [0 0 10 0 0]
#   [0 10 0 0 0]
#   [0 0 0 0 10]]

input = mindspore.Tensor(np.ones([5,5]),mindspore.float32)
net = mindspore.nn.Dropout(keep_prob=0.1)
net.set_train()
output = net(input)
print(output)

# out:
#   [[0 10 0 0 0]
#   [0 0 0 10 0]
#   [0 0 0 0 0]
#   [0 10 10 0 0]
#   [0 0 10 0 0]]