File size: 977 Bytes
5b6d90c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | import torch
import torch.nn as nn
class MiniVisionV2(nn.Module):
def __init__(self):
super().__init__()
self.model = nn.Sequential(
nn.Conv2d(1, 32, 3, padding=1),
nn.BatchNorm2d(32),
nn.ReLU(),
nn.MaxPool2d(2, 2),
nn.Conv2d(32, 64, 3, padding=1),
nn.BatchNorm2d(64),
nn.ReLU(),
nn.MaxPool2d(2, 2),
nn.Flatten(),
nn.Linear(3136, 256),
nn.ReLU(),
nn.Dropout(0.3),
nn.Linear(256, 10)
)
def forward(self, x):
x = self.model(x)
return x
if __name__ == '__main__':
minivisionv2 = MiniVisionV2()
params = sum(p.numel() for p in minivisionv2.parameters())
print(f"Total params: {params / 1000000:,}M")
input = torch.randn(64, 1, 28, 28)
with torch.no_grad():
output = minivisionv2(input)
print(output)
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