I am using a
ReformerForQuestionAnsweringfor training on a QA task.
Here’s a snippet of the code that can reproduce the error.
from transformers import ReformerTokenizer, ReformerForQuestionAnswering tokenizer = ReformerTokenizer.from_pretrained('google/reformer-crime-and-punishment') model = ReformerForQuestionAnswering.from_pretrained('google/reformer-crime-and-punishment') question, text = "Who was Jim Henson?", "Jim Henson was a nice puppet" inputs = tokenizer(question, text, return_tensors='pt') start_positions = torch.tensor() end_positions = torch.tensor() outputs = model(**inputs, start_positions=start_positions, end_positions=end_positions) loss = outputs.loss loss.backward()
The backward() call throws the following error
TypeError: int() argument must be a string, a bytes-like object or a number, not ‘NoneType’