TestDataSet(Dataset):
def __init__(self):
super(TestDataSet, self).__init__()
self.data_dict_X = X_validate
self.data_dict_y = y_validate
def __getitem__(self, index):
t = self.data_dict_X[index, 0:36]
t = torch.tensor(t).view(6, 6)
return t, self.data_dict_y[index]
def __len__(self):
return len(self.data_dict_y)
def cnn_classification():
batch_size = 256
trainDataLoader = DataLoader(TrainingDataSet(), batch_size=batch_size, shuffle=False)
testDataLoader = DataLoader(TestDataSet(), batch_size=batch_size, shuffle=False)
epoch_num = 200
#lr = 0.001
lr = 0.001
net = VGGBaseSimpleS2().to(device)
print(net)
# loss
loss_func = nn.CrossEntropyLoss()
# optimizer
optimizer = torch.optim.Adam(net.parameters(), lr=lr)
# optimizer = torch.optim.SGD(net.parameters(), lr=lr, momentum=0.9, weight_decay=5e-4)
scheduler = torch.op
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