feat: double convolution

This commit is contained in:
Martin Eyben 2025-05-16 10:48:14 +02:00
parent 15e64ffad3
commit 7670ecdabf

View File

@ -30,17 +30,21 @@ class GoModel(nn.Module):
nn.Dropout(0.4),
torch.nn.ReLU(),
nn.Conv2d(64, 64, kernel_size=3, padding=1, bias=False),
nn.BatchNorm2d(64),
nn.Conv2d(64, 128, kernel_size=3, padding=1, bias=False),
nn.BatchNorm2d(128),
torch.nn.ReLU(),
nn.Conv2d(64, 64, kernel_size=3, padding=1, bias=False),
nn.BatchNorm2d(64),
nn.Conv2d(128, 128, kernel_size=3, padding=1, bias=False),
nn.BatchNorm2d(128),
torch.nn.ReLU(),
nn.Conv2d(128, 128, kernel_size=3, padding=1, bias=False),
nn.BatchNorm2d(128),
torch.nn.ReLU(),
nn.Flatten(),
nn.Linear(64 * 8 * 8, 128),
nn.Linear(128 * 8 * 8, 128),
nn.BatchNorm1d(128),
torch.nn.ReLU(),
@ -298,6 +302,15 @@ if __name__ == "__main__":
checkpoint = torch.load(args.m, weights_only=True)
mymodel.load_state_dict(checkpoint["model_state_dict"])
if args.R is not None:
if args.m is None:
print("You need to specify weights for a model")
return
with gzip.open(args.R) as fz:
data = json.loads(fz.read().decode("utf-8"))
create_result_file(data)
if args.t is not None and args.T is not None:
trainset = torch.load(args.t)
testset = torch.load(args.T)