fix: small change to main_network
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@ -41,6 +41,25 @@ hidden_size = 135*64
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#żeby to skończyć kiedykolwiek i jak uda mi się to CUDA zrobić to zmieniam rozdziałke z 1024 na 128
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#Użycie konwolucyjnej warstwy dobiło mi z 85 do 90
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# model = torch.nn.Sequential(
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# torch.nn.Conv2d(3, 6, 5),
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# torch.nn.MaxPool2d(2, 2),
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# torch.nn.Conv2d(6, 16, 5),
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# torch.nn.Flatten(),
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# torch.nn.Linear(53824, hidden_size),
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# torch.nn.ReLU(),
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# torch.nn.Linear(hidden_size, 32*32),
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# torch.nn.ReLU(),
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# torch.nn.Linear(32*32, 10),
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# torch.nn.LogSoftmax(dim=-1)
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# ).to(device)
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# train(model, trainset)
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# print(accuracy(model, testset))
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# torch.save(model.state_dict(), 'model.pt')
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model = torch.nn.Sequential(
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torch.nn.Conv2d(3, 6, 5),
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torch.nn.MaxPool2d(2, 2),
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@ -53,9 +72,4 @@ model = torch.nn.Sequential(
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torch.nn.Linear(32*32, 10),
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torch.nn.LogSoftmax(dim=-1)
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).to(device)
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train(model, trainset)
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print(accuracy(model, testset))
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# torch.save(model.state_dict(), 'model.pt')
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model.load_state_dict(torch.load('model.pt'))
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