由于我的CUDA版本是8,所以我用的是torch 1.0.0
我需要为 Sequential 模型使用 Flatten 层。这是我的代码:
import torch
import torch.nn as nn
import torch.nn.functional as F
print(torch.__version__)
# 1.0.0
from collections import OrderedDict
layers = OrderedDict()
layers['conv1'] = nn.Conv2d(1, 5, 3)
layers['relu1'] = nn.ReLU()
layers['conv2'] = nn.Conv2d(5, 1, 3)
layers['relu2'] = nn.ReLU()
layers['flatten'] = nn.Flatten()
layers['linear1'] = nn.Linear(3600, 1)
model = nn.Sequential(
layers
).cuda()
它给我以下错误:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-38-080f7c5f5037> in <module>
6 layers['conv2'] = nn.Conv2d(5, 1, 3)
7 layers['relu2'] = nn.ReLU()
----> 8 layers['flatten'] = nn.Flatten()
9 layers['linear1'] = nn.Linear(3600, 1)
10 model = nn.Sequential(
AttributeError: module 'torch.nn' has no attribute 'Flatten'
如何在 pytorch 1.0.0 中展平我的转换层输出?
最佳答案
只需新建一个 Flatten 层即可。
from collections import OrderedDict
class Flatten(nn.Module):
def forward(self, input):
return input.view(input.size(0), -1)
layers = OrderedDict()
layers['conv1'] = nn.Conv2d(1, 5, 3)
layers['relu1'] = nn.ReLU()
layers['conv2'] = nn.Conv2d(5, 1, 3)
layers['relu2'] = nn.ReLU()
layers['flatten'] = Flatten()
layers['linear1'] = nn.Linear(3600, 1)
model = nn.Sequential(
layers
).cuda()
关于python - 在 pytorch v1.0 Sequential 模块中使用 flatten,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/61039700/