Using flatten in pytorch v1.0 Sequential module

Question

Due to my CUDA version being 8, I am using torch 1.0.0

I need to use the Flatten layer for Sequential model. Here's my code :

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()

It gives me the following error:

---------------------------------------------------------------------------
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'

How can I flatten my conv layer output in pytorch 1.0.0?

Zabir Al Nazi Zabir Al Nazi · Accepted Answer · 2020-04-05T08:10:31

Just make a new Flatten layer.

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()

Using flatten in pytorch v1.0 Sequential module

1 Answers