Could you check the shape of the images
tensor in the DataLoader
loop before applying the reshape
operation?
Based on the comments I guess it would be [N=300, 4, 256, 256]
and after applying the reshape
it would be:
images = images.reshape(-1,SEQUENCE_LENGHT,INPUT_SIZE)
[batch_size=4*300=1200, SEQUENCE_LENGTH=256, INPUT_SIZE=256]
In that case you are flattening the channels into the batch dimension, which is usually wrong (you are increasing the number of samples in the current batch), which would later raise the shape mismatch error.