Given groups=1, weight of size [256, 2048, 1, 1], expected input[2, 960, 34, 46] to have 2048 channels, but got 960 channels instead

Hi all,

I’m trying to train the deeplabv3_mobilenet_v3_large model (pretrained). When, I do model(imgs) with imgs of size: torch.Size([2, 3, 544, 728]) thus batch of size 2, RGB and image dimensions. I get this error: Given groups=1, weight of size [256, 2048, 1, 1], expected input[2, 960, 34, 46] to have 2048 channels, but got 960 channels instead.
Why is this error raised ? I don’t have this issue with the other deeplablab models.

Thanks in advance for the help!

I cannot reproduce the issue with the given input shape:

model = models.segmentation.deeplabv3_mobilenet_v3_large()
x = torch.randn(2, 3, 544, 728)
out = model(x)
print(out['out'].shape)
# > torch.Size([2, 21, 544, 728])