Slide 16
Slide 16 text
© Hitachi, Ltd. 2020. All rights reserved.
Custom Convolution Network
● Custom pooling layer
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Point 3
def forward(self, x):
x = x.view(x.size(0), 1, x.size(1), x.size(2))
x = self.conv1(x, pool_size=(1, 1), pool_type="both")
x = self.conv2(x, pool_size=(4, 1), pool_type="both")
x = self.conv3(x, pool_size=(1, 3), pool_type="both")
x = self.conv4(x, pool_size=(4, 1), pool_type="both")
x = self.conv5(x, pool_size=(1, 3), pool_type="both")
………………………………………………………………………………
elif pool_type == "both":
x1 = F.max_pool2d(x, kernel_size=pool_size)
x2 = F.avg_pool2d(x, kernel_size=pool_size)
x = x1 + x2