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.