I am trying to generate time series data using convolutional GAN.

My model is here:

seq_size = batch_size

n_features = X2_scaled.shape[2]

# Discriminator

D = nn.Sequential(

```
nn.Conv1d(32, 64, kernel_size=4, stride=2,padding=2,dilation=1),#32
nn.BatchNorm2d(64),
nn.ReLU(),
nn.Conv1d(64, 64, kernel_size=3, stride=2, padding=1,dilation=2),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv1d(64, 32, kernel_size=1, stride=2, padding=0,dilation=4),
# nn.BatchNorm2d(4),
nn.Sigmoid()
```

)

# Generator

G = nn.Sequential(

nn.Linear(4, 7),# as z is of (latent_dim,4)

```
nn.ConvTranspose1d(7, 64, kernel_size=3, stride=1,padding=1),
nn.BatchNorm1d(64),
nn.ReLU(),
nn.ConvTranspose1d(64, 64, kernel_size=2, stride=1,padding=1),
nn.BatchNorm1d(64),
nn.ReLU(),
nn.ConvTranspose1d(64, 32, kernel_size=1, stride=1,padding=1),
# nn.BatchNorm1d(4),
nn.Tanh(),
)
```

D = D.to(device)

G = G.to(device)

# training

total_step = len(data_loader)

for epoch in range(num_epochs):

for i, (samples) in enumerate(data_loader):

samples = samples.reshape(batch_size, -1).to(device)

print(samples.shape) # giving original input shape (568,32,4)

→ outputs = D(samples.float())

Here I am getting the runtime error: Given groups=1, weight of size [64, 32, 4], expected input[1, 64, 128] to have 32 channels, but got 64 channels instead.

I am unable to see my mistake here. please help me. Thanks in advance