Given groups=1, weight of size [64, 32, 4], expected input[1, 64, 128] to have 32 channels, but got 64 channels instead

PyTorch Live
1

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

2

The shape in this comment

cannot be true, since you are reshaping the tensor to two dimensions only.

nn.Conv1d expects a batched 3D tensor in the shape [batch_size, channels, seq_len] or an unbatched 2D tensor in the shape [channels, seq_len]. In the latter case the layer will unsqueeze the tensor’s missing batch dimension and will set a sample size of 1 to it.
I would generally recommend unsqueezing the batch dimension explicitly, as I don’t think this “flexibility” of accepting inputs without a batch dimension is a well designed feature, which mainly creates confusion.
After fixing this issue you would most likely run into a new one since you are using nn.BatchNorm2d while I assume it should be nn.BatchNorm1d.

3

Yes when I was not reshaping it, was showing ValueError: expected 4D input (got 3D input).
Now I see why it was there. Had a serious mistake by taking BatchNorm2d().
Thank you so so much. Now I don’t get the same error.