Dear TAs,
One silly question, from me.
in the WarmUp LeNet
self.conv1 = nn.Conv2d(1, 6, kernel_size=(5,5),stride=1, padding=0)
self.conv2 = nn.Conv2d(6, 16, kernel_size=(5,5),stride=1, padding=0)
self.fc1 = nn.Linear(1644, 120) <---
when I was reading the LeNet paper I thought it was 16* (5*5), because the input data is 32x32
however, I've output the size of from the code and found out the size was
28x28
why is it not 32x32 do datasets.MNIST on PyTorch chop down the size of the datasets.MNIST??
Thank you so much
ref:
(128L, 1L, 28L, 28L)
(128L, 6L, 24L, 24L)
(128L, 6L, 12L, 12L)
(128L, 16L, 8L, 8L)
(128L, 16L, 4L, 4L)
(128L, 256L)
(128L, 120L)
(128L, 84L)
(128L, 10L)
Dear TAs,
One silly question, from me.
in the WarmUp LeNet
self.conv1 = nn.Conv2d(1, 6, kernel_size=(5,5),stride=1, padding=0)
self.conv2 = nn.Conv2d(6, 16, kernel_size=(5,5),stride=1, padding=0)
self.fc1 = nn.Linear(1644, 120) <---
when I was reading the LeNet paper I thought it was 16* (5*5), because the input data is 32x32
however, I've output the size of from the code and found out the size was
28x28
why is it not 32x32 do datasets.MNIST on PyTorch chop down the size of the datasets.MNIST??
Thank you so much
ref:
(128L, 1L, 28L, 28L)
(128L, 6L, 24L, 24L)
(128L, 6L, 12L, 12L)
(128L, 16L, 8L, 8L)
(128L, 16L, 4L, 4L)
(128L, 256L)
(128L, 120L)
(128L, 84L)
(128L, 10L)