Sequential(
(0): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(18, 18))
(1): ReLU()
(2): MaxPool2d(kernel_size=(2, 2), stride=2, padding=0, dilation=1, ceil_mode=False)
(3): Conv2d(64, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(4): ReLU()
(5): MaxPool2d(kernel_size=(2, 2), stride=2, padding=0, dilation=1, ceil_mode=False)
(6): Conv2d(192, 128, kernel_size=(1, 1), stride=(1, 1))
(7): ReLU()
(8): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(9): ReLU()
(10): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))
(11): ReLU()
(12): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(13): ReLU()
(14): MaxPool2d(kernel_size=(2, 2), stride=2, padding=0, dilation=1, ceil_mode=False)
(15): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))
(16): ReLU()
(17): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(18): ReLU()
(19): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))
(20): ReLU()
(21): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(22): ReLU()
(23): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))
(24): ReLU()
(25): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(26): ReLU()
(27): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))
(28): ReLU()
(29): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(30): ReLU()
(31): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))
(32): ReLU()
(33): Conv2d(512, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(34): ReLU()
(35): MaxPool2d(kernel_size=(2, 2), stride=2, padding=0, dilation=1, ceil_mode=False)
(36): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1))
(37): ReLU()
(38): Conv2d(512, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(39): ReLU()
(40): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1))
(41): ReLU()
(42): Conv2d(512, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(43): ReLU()
(44): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(45): ReLU()
(46): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
(47): ReLU()
(48): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(49): ReLU()
(50): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(51): ReLU()
(52): Reshape()
(53): Linear(in_features=50176, out_features=4096, bias=True)
(54): ReLU()
(55): Linear(in_features=4096, out_features=4410, bias=True)
(56): Sigmoid()
(57): Reshape()
)
This is the string description of the model if this helps.