<changed>

model.py
1) Error appear

Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!

-> class BeatGan
-> self.bce_criterion = nn.BCELoss().cuda()
   self.mse_criterion = nn.MSELoss().cuda()

-> def update_netd
->
        self.err_d_real = self.bce_criterion(self.out_d_real, torch.full((self.batchsize,), self.real_label, device=self.device).type(torch.FloatTensor).cuda())

        self.err_d_fake = self.bce_criterion(self.out_d_fake, torch.full((self.batchsize,), self.fake_label, device=self.device).type(torch.FloatTensor).cuda())


data.py
1) if you use 2D signal data, the data shape must (num_of_data, 1, width, height)

2) I changed "np.load()" parts for utilize.

3) normalize part is changed.

network.py
1) Conv2D(input channel, output channel, kernel_size, stride, padding)
  output size = output channel * (input_size-kernel_size+2*padding)/stride+1

  We use 128*128 data so we set "Encoder"'s Conv2d's parameters like that.
  The result is 50*1*1

2) Decoder is inverse of Encoder


option.py
1) change batchsize from 64 to 32, because Memory allocate issue was happened.

etc)
1) 2D-data must have the shape (n,1,w,h)
   1D-data is (n,1,w)

1-1) So, you should go to experiments/ecg/dataset/preprocessed.
    Push change.py and change2.py to ano0.
    Diretory ano0 should have _ _samples.npy file.