⚠️ Raise Exception when trying to generate 0 tokens ⚠️ (#28621)

* change warning to exception

* Update src/transformers/generation/utils.py

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* validate `max_new_tokens` > 0 in `GenerationConfig`

* fix truncation test parameterization in `TextGenerationPipelineTests`

---------

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

src/transformers/generation/configuration_utils.py

@@ -373,6 +373,8 @@ def validate(self, is_init=False):
  # Validation of individual attributes
  if self.early_stopping not in {True, False, "never"}:
  raise ValueError(f"`early_stopping` must be a boolean or 'never', but is {self.early_stopping}.")
+ if self.max_new_tokens is not None and self.max_new_tokens <= 0:
+ raise ValueError(f"`max_new_tokens` must be greater than 0, but is {self.max_new_tokens}.")
 
  # Validation of attribute relations:
  fix_location = ""

src/transformers/generation/utils.py

@@ -1138,11 +1138,10 @@ def _validate_generated_length(self, generation_config, input_ids_length, has_de
  )
  if input_ids_length >= generation_config.max_length:
  input_ids_string = "decoder_input_ids" if self.config.is_encoder_decoder else "input_ids"
- warnings.warn(
+ raise ValueError(
  f"Input length of {input_ids_string} is {input_ids_length}, but `max_length` is set to"
  f" {generation_config.max_length}. This can lead to unexpected behavior. You should consider"
- " increasing `max_new_tokens`.",
- UserWarning,
+ " increasing `max_length` or, better yet, setting `max_new_tokens`."
  )
 
  # 2. Min length warnings due to unfeasible parameter combinations

tests/pipelines/test_pipelines_text_generation.py

@@ -93,17 +93,19 @@ def test_small_model_pt(self):
 
  ## -- test tokenizer_kwargs
  test_str = "testing tokenizer kwargs. using truncation must result in a different generation."
+ input_len = len(text_generator.tokenizer(test_str)["input_ids"])
  output_str, output_str_with_truncation = (
- text_generator(test_str, do_sample=False, return_full_text=False)[0]["generated_text"],
+ text_generator(test_str, do_sample=False, return_full_text=False, min_new_tokens=1)[0]["generated_text"],
  text_generator(
  test_str,
  do_sample=False,
  return_full_text=False,
+ min_new_tokens=1,
  truncation=True,
- max_length=3,
+ max_length=input_len + 1,
  )[0]["generated_text"],
  )
- assert output_str != output_str_with_truncation # results must be different because one hd truncation
+ assert output_str != output_str_with_truncation # results must be different because one had truncation
 
  # -- what is the point of this test? padding is hardcoded False in the pipeline anyway
  text_generator.tokenizer.pad_token_id = text_generator.model.config.eos_token_id