Traceback (most recent call last):
File "/content/drive/MyDrive/Workspace/deep-text-recognition-benchmark/train.py", line 317, in <module>
train(opt)
File "/content/drive/MyDrive/Workspace/deep-text-recognition-benchmark/train.py", line 163, in train
preds = model(image, text[:, :-1]) # align with Attention.forward
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/parallel/data_parallel.py", line 183, in forward
return self.module(*inputs[0], **module_kwargs[0])
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/content/drive/MyDrive/Workspace/deep-text-recognition-benchmark/model.py", line 76, in forward
visual_feature = self.FeatureExtraction(input)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/content/drive/MyDrive/Workspace/deep-text-recognition-benchmark/modules/feature_extraction.py", line 62, in forward
return self.ConvNet(input)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/content/drive/MyDrive/Workspace/deep-text-recognition-benchmark/modules/feature_extraction.py", line 242, in forward
x = self.conv4_2(x)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/conv.py", line 460, in forward
return self._conv_forward(input, self.weight, self.bias)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/conv.py", line 456, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: Calculated padded input size per channel: (1 x 22). Kernel size: (2 x 2). Kernel size can't be greater than actual input size
generated 3 datasets(train, valid, eval) placed them into data/train, data/valid, data/eval folders Running in Google Colab:
Getting an error:
Output before an error:
Would be grateful for any advice. Thank you in advance.