Exploring Layers

import torch
from torch import nn

cl_1 = nn.Conv2d(1, 64, 3)
mp_1 = nn.MaxPool2d(2)

cl_2 = nn.Conv2d(64, 128, 3)
mp_2 = nn.MaxPool2d(2)

cl_3 = nn.Conv2d(128, 512, 3)
mp_3 = nn.MaxPool2d(2)

cl_4 = nn.Conv2d(512, 512, 3)
mp_4 = nn.MaxPool2d(2)

input = torch.randn(1, 1, 48, 48)

out_1 = mp_1(cl_1(input))
out_1.size()

out_2 = mp_2(cl_2(out_1))
out_2.size()

out_3 = mp_3(cl_3(out_2))
out_3.size()

out_4 = mp_4(cl_4(out_3))
out_4.size()

out = cl_4(cl_3(cl_2(cl_1(input))))

out = mp_2(cl_4(cl_3(mp_1(cl_2(cl_1(input))))))


model = nn.Sequential(
    nn.Conv2d(1, 64, 3),
    nn.BatchNorm2d(64),
    nn.ReLU(),
    nn.MaxPool2d(2),
    nn.Dropout(p=0.25),
    nn.Linear(33856, 1472),
    nn.Linear(1472, 512),
    nn.Linear(512, 10),
    nn.LogSoftmax(dim=1)
    )


model = nn.Sequential(
    nn.Conv2d(1, 64, 3),
    nn.ReLU(),
    nn.MaxPool2d(2),
    
    nn.Linear(33856, 1472),
    nn.Linear(1472, 512),
    nn.ReLU(),
    nn.Dropout(p=0.25),
    
    nn.Linear(512, 10),
    nn.LogSoftmax(dim=1)
    )


ln_1 = nn.Linear(1, 512)