I have workaround this problem by splitting the data into two parts. But now I have another Issue:
train_dataset= TensorDataset(input_tensor,target_tensor, label)
train_dl = DataLoader(train_dataset,batch_size=batch_size, shuffle=True,drop_last=drop_last)
My issue is that I need to have a pair of input and target tensor. But when I activate shuffling the input and target are somehow shuffled in a different manner. Is there a method to keep the input tensor and target tensor in pairs even with shuffling activated.