I am struggeling to determine a cause for following behavior of 3 class classification code I have below. The classifier takes a 2D matrix of torch.Size([1, 1, 512, 512]) . The output is torch.Size([256, 3]) .
class Classifier(nn.Module):
def __init__(self):
super(Classifier, self).__init__()
self.layer1 = nn.Sequential(
nn.Conv2d(1, 32, kernel_size=5, stride=1, padding=2),
nn.ReLU(),
nn.MaxPool2d(kernel_size=2, stride=2))
self.layer2 = nn.Sequential(
nn.Conv2d(32, 64, kernel_size=5, stride=1, padding=2),
nn.ReLU(),
nn.MaxPool2d(kernel_size=2, stride=2))
self.drop_out = nn.Dropout()
self.fc1 = nn.Linear(4096, 1024)
self.fc2 = nn.Linear(1024, 3)
def forward(self, x):
out = self.layer1(x)
out = self.layer2(out)
out = out.view(-1, 4096)
out = self.drop_out(out)
out = self.fc1(out)
out = self.fc2(out)
return out
The problem is same model provides following dimensions when model summary is printed. My problem is I need to compare this with a torch.Size([1]) where the class labels are stored. Everything is showing that this is designed for 3 class classification problem but cannot determine where this value of 256 in the output tensor comes from.
summary(activity_recognizer,(1,512,512))
==========================================================================================
Layer (type:depth-idx) Output Shape Param #
==========================================================================================
├─Sequential: 1-1 [-1, 32, 256, 256] --
| └─Conv2d: 2-1 [-1, 32, 512, 512] 832
| └─ReLU: 2-2 [-1, 32, 512, 512] --
| └─MaxPool2d: 2-3 [-1, 32, 256, 256] --
├─Sequential: 1-2 [-1, 64, 128, 128] --
| └─Conv2d: 2-4 [-1, 64, 256, 256] 51,264
| └─ReLU: 2-5 [-1, 64, 256, 256] --
| └─MaxPool2d: 2-6 [-1, 64, 128, 128] --
├─Dropout: 1-3 [-1, 4096] --
├─Linear: 1-4 [-1, 1024] 4,195,328
├─Linear: 1-5 [-1, 3] 3,075
==========================================================================================
Total params: 4,250,499
Trainable params: 4,250,499
Non-trainable params: 0
Total mult-adds (G): 3.57
==========================================================================================
Input size (MB): 1.00
Forward/backward pass size (MB): 96.01
Params size (MB): 16.21
Estimated Total Size (MB): 113.22
==========================================================================================
Spend few hours but seems like I hit a deadend. Appreciate any help I can have here.