---------------------------------------------------------------- Layer (type) Output Shape Param # ================================================================ Conv2d-1 [-1, 64, 40, 40] 9,408 BatchNorm2d-2 [-1, 64, 40, 40] 128 ReLU-3 [-1, 64, 40, 40] 0 MaxPool2d-4 [-1, 64, 20, 20] 0 Conv2d-5 [-1, 64, 20, 20] 36,864 BatchNorm2d-6 [-1, 64, 20, 20] 128 ReLU-7 [-1, 64, 20, 20] 0 Conv2d-8 [-1, 64, 20, 20] 36,864 BatchNorm2d-9 [-1, 64, 20, 20] 128 ReLU-10 [-1, 64, 20, 20] 0 BasicBlock-11 [-1, 64, 20, 20] 0 Conv2d-12 [-1, 64, 20, 20] 36,864 BatchNorm2d-13 [-1, 64, 20, 20] 128 ReLU-14 [-1, 64, 20, 20] 0 Conv2d-15 [-1, 64, 20, 20] 36,864 BatchNorm2d-16 [-1, 64, 20, 20] 128 ReLU-17 [-1, 64, 20, 20] 0 BasicBlock-18 [-1, 64, 20, 20] 0 Conv2d-19 [-1, 128, 10, 10] 73,728 BatchNorm2d-20 [-1, 128, 10, 10] 256 ReLU-21 [-1, 128, 10, 10] 0 Conv2d-22 [-1, 128, 10, 10] 147,456 BatchNorm2d-23 [-1, 128, 10, 10] 256 Conv2d-24 [-1, 128, 10, 10] 8,192 BatchNorm2d-25 [-1, 128, 10, 10] 256 ReLU-26 [-1, 128, 10, 10] 0 BasicBlock-27 [-1, 128, 10, 10] 0 Conv2d-28 [-1, 128, 10, 10] 147,456 BatchNorm2d-29 [-1, 128, 10, 10] 256 ReLU-30 [-1, 128, 10, 10] 0 Conv2d-31 [-1, 128, 10, 10] 147,456 BatchNorm2d-32 [-1, 128, 10, 10] 256 ReLU-33 [-1, 128, 10, 10] 0 BasicBlock-34 [-1, 128, 10, 10] 0 Conv2d-35 [-1, 256, 5, 5] 294,912 BatchNorm2d-36 [-1, 256, 5, 5] 512 ReLU-37 [-1, 256, 5, 5] 0 Conv2d-38 [-1, 256, 5, 5] 589,824 BatchNorm2d-39 [-1, 256, 5, 5] 512 Conv2d-40 [-1, 256, 5, 5] 32,768 BatchNorm2d-41 [-1, 256, 5, 5] 512 ReLU-42 [-1, 256, 5, 5] 0 BasicBlock-43 [-1, 256, 5, 5] 0 Conv2d-44 [-1, 256, 5, 5] 589,824 BatchNorm2d-45 [-1, 256, 5, 5] 512 ReLU-46 [-1, 256, 5, 5] 0 Conv2d-47 [-1, 256, 5, 5] 589,824 BatchNorm2d-48 [-1, 256, 5, 5] 512 ReLU-49 [-1, 256, 5, 5] 0 BasicBlock-50 [-1, 256, 5, 5] 0 Conv2d-51 [-1, 512, 3, 3] 1,179,648 BatchNorm2d-52 [-1, 512, 3, 3] 1,024 ReLU-53 [-1, 512, 3, 3] 0 Conv2d-54 [-1, 512, 3, 3] 2,359,296 BatchNorm2d-55 [-1, 512, 3, 3] 1,024 Conv2d-56 [-1, 512, 3, 3] 131,072 BatchNorm2d-57 [-1, 512, 3, 3] 1,024 ReLU-58 [-1, 512, 3, 3] 0 BasicBlock-59 [-1, 512, 3, 3] 0 Conv2d-60 [-1, 512, 3, 3] 2,359,296 BatchNorm2d-61 [-1, 512, 3, 3] 1,024 ReLU-62 [-1, 512, 3, 3] 0 Conv2d-63 [-1, 512, 3, 3] 2,359,296 BatchNorm2d-64 [-1, 512, 3, 3] 1,024 ReLU-65 [-1, 512, 3, 3] 0 BasicBlock-66 [-1, 512, 3, 3] 0 AdaptiveAvgPool2d-67 [-1, 512, 1, 1] 0 BatchNorm1d-68 [-1, 512] 1,024 Dropout-69 [-1, 512] 0 Linear-70 [-1, 512] 262,144 ReLU-71 [-1, 512] 0 BatchNorm1d-72 [-1, 512] 1,024 Dropout-73 [-1, 512] 0 Linear-74 [-1, 256] 131,072 BatchNorm1d-75 [-1, 256] 0 ResNet-76 [-1, 256] 0 ================================================================ Total params: 11,571,776 Trainable params: 11,571,776 Non-trainable params: 0 ---------------------------------------------------------------- Input size (MB): 0.07 Forward/backward pass size (MB): 8.21 Params size (MB): 44.14 Estimated Total Size (MB): 52.43 ----------------------------------------------------------------