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Inception.py
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Inception.py
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import torch
import torch.nn as nn
import torchvision.models as models
import torch.nn.functional as F
class Identity(nn.Module):
def __init__(self):
super(Identity, self).__init__()
def forward(self, x):
return x
class Inception(nn.Module):
def __init__(self):
super(Inception, self).__init__()
self.inception = models.inception_v3(pretrained=True)
self.inception.avgpool = Identity()
self.inception.dropout = Identity()
def forward(self, x):
x = self.inception.Conv2d_1a_3x3(x)
# 149 x 149 x 32
x = self.inception.Conv2d_2a_3x3(x)
# 147 x 147 x 32
x = self.inception.Conv2d_2b_3x3(x)
# 147 x 147 x 64
x = F.max_pool2d(x, kernel_size=3, stride=2)
# 73 x 73 x 64
x = self.inception.Conv2d_3b_1x1(x)
# 73 x 73 x 80
x = self.inception.Conv2d_4a_3x3(x)
# 71 x 71 x 192
x = F.max_pool2d(x, kernel_size=3, stride=2)
# 35 x 35 x 192
x = self.inception.Mixed_5b(x)
# 35 x 35 x 256
x = self.inception.Mixed_5c(x)
# 35 x 35 x 288
x = self.inception.Mixed_5d(x)
# 35 x 35 x 288
x = self.inception.Mixed_6a(x)
# 17 x 17 x 768
x = self.inception.Mixed_6b(x)
# 17 x 17 x 768
x = self.inception.Mixed_6c(x)
# 17 x 17 x 768
x = self.inception.Mixed_6d(x)
# 17 x 17 x 768
x = self.inception.Mixed_6e(x)
# 17 x 17 x 768
x = self.inception.Mixed_7a(x)
# 8 x 8 x 1280
x = self.inception.Mixed_7b(x)
# 8 x 8 x 2048
x = self.inception.Mixed_7c(x)
# 8 x 8 x 2048
return x