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raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for BaseConvGenerator:
size mismatch for conv14.weight: copying a param with shape torch.Size([96, 96, 3, 3]) from checkpoint, the shape in current model is torch.Size([96, 48, 3, 3]).
size mismatch for conv16.weight: copying a param with shape torch.Size([48, 48, 3, 3]) from checkpoint, the shape in current model is torch.Size([24, 24, 3, 3]).
size mismatch for conv16.bias: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([24]).
size mismatch for conv17.weight: copying a param with shape torch.Size([3, 24, 3, 3]) from checkpoint, the shape in current model is torch.Size([3, 12, 3, 3]).
The text was updated successfully, but these errors were encountered:
manhnguyen92
changed the title
How to test with pre-trained model?
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format
Sep 23, 2022
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for BaseConvGenerator:
size mismatch for conv14.weight: copying a param with shape torch.Size([96, 96, 3, 3]) from checkpoint, the shape in current model is torch.Size([96, 48, 3, 3]).
size mismatch for conv16.weight: copying a param with shape torch.Size([48, 48, 3, 3]) from checkpoint, the shape in current model is torch.Size([24, 24, 3, 3]).
size mismatch for conv16.bias: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([24]).
size mismatch for conv17.weight: copying a param with shape torch.Size([3, 24, 3, 3]) from checkpoint, the shape in current model is torch.Size([3, 12, 3, 3]).
The text was updated successfully, but these errors were encountered: