add exceptions

src/transformers/generation_utils.py

@@ -848,6 +848,11 @@ def _validate_model_kwargs(self, model_kwargs: Dict[str, Any]):
  for key in ["decoder_input_ids"]:
  model_kwargs.pop(key, None)
 
+ # Transfo_XL does not use have "attention_mask" as an argument, and it is harmless (it is being passed in the
+ # tests, through)
+ if "transfoxl" in str(self).lower():
+ model_kwargs.pop("attention_mask", None)
+
  unused_model_args = []
  model_args = set(inspect.signature(self.prepare_inputs_for_generation).parameters)
  # `kwargs`` if often used to handle optional forward pass inputs like `attention_mask`. If

tests/generation/test_generation_utils.py

@@ -2052,7 +2052,7 @@ def test_max_new_tokens_decoder_only(self):
 
  # max_new_tokens and max_length serve the same purpose and should not be used together.
  with self.assertWarns(UserWarning):
- gpt2_model.generate(decoder_input_ids=input_ids, max_new_tokens=10, max_length=20)
+ gpt2_model.generate(input_ids=input_ids, max_new_tokens=10, max_length=20)
 
  def test_encoder_decoder_generate_with_inputs_embeds(self):
  article = """Justin Timberlake and Jessica Biel, welcome to parenthood."""

tests/models/bigbird_pegasus/test_modeling_bigbird_pegasus.py

@@ -360,7 +360,7 @@ def test_generate_fp16(self):
  if torch_device == "cuda":
  model.half()
  model.generate(**input_dict)
- model.generate(**input_dict, do_sample=True, early_stopping=False, num_return_sequences=3)
+ model.generate(**input_dict, do_sample=True, num_return_sequences=3)
 
  @slow
  def test_batched_forward_original_full(self):