Fix whisper kwargs and generation config (#30018)

* clean-up whisper kwargs

* failing test

Author: zucchini-nlp

src/transformers/models/whisper/generation_whisper.py

@@ -511,7 +511,6 @@ def generate(
         self._set_language_and_task(
             language=language, task=task, is_multilingual=is_multilingual, generation_config=generation_config
         )
-        self._set_token_ids(generation_config=generation_config, config=self.config, kwargs=kwargs)
         self._set_num_frames(
             return_token_timestamps=return_token_timestamps, generation_config=generation_config, kwargs=kwargs
         )
@@ -546,13 +545,13 @@ def generate(
             logits_processor=logits_processor,
             begin_index=begin_index,  # begin index is index of first generated decoder token
             is_shortform=is_shortform,
-            num_beams=kwargs.get("num_beams", 1),
+            num_beams=generation_config.num_beams,
         )
 
         # 5. If we're in shortform mode, simple generate the whole input at once and return the output
         if is_shortform:
             if temperature is not None:
-                kwargs["temperature"] = temperature
+                generation_config.temperature = temperature
 
             decoder_input_ids = kwargs.pop("decoder_input_ids", None)
             if decoder_input_ids is None:
@@ -564,8 +563,8 @@ def generate(
                     [prompt_ids[None].repeat(decoder_input_ids.shape[0], 1), decoder_input_ids], dim=-1
                 )
 
-            if kwargs.get("max_new_tokens", 0) + decoder_input_ids.shape[-1] > self.config.max_target_positions:
-                max_new_tokens = kwargs.get("max_new_tokens", 0)
+            max_new_tokens = generation_config.max_new_tokens if generation_config.max_new_tokens is not None else 0
+            if max_new_tokens + decoder_input_ids.shape[-1] > self.config.max_target_positions:
                 raise ValueError(
                     f"The length of `decoder_input_ids` equal `prompt_ids` plus special start tokens is {decoder_input_ids.shape[-1]}, and the `max_new_tokens` "
                     f"is {max_new_tokens}. Thus, the combined length of "
@@ -666,11 +665,10 @@ def generate(
             )
 
             # 6.6 set max new tokens or max length
-            kwargs = self._set_max_new_tokens_and_length(
+            self._set_max_new_tokens_and_length(
                 config=self.config,
                 decoder_input_ids=decoder_input_ids,
                 generation_config=generation_config,
-                kwargs=kwargs,
             )
 
             # 6.7 Set current `begin_index` for all logit processors
@@ -770,9 +768,9 @@ def generate_with_fallback(
 
         for fallback_idx, temperature in enumerate(temperatures):
             generation_config.do_sample = temperature is not None and temperature > 0.0
-
             generation_config.temperature = temperature if generation_config.do_sample else 1.0
-            generation_config.num_beams = kwargs.get("num_beams", 1) if not generation_config.do_sample else 1
+            if generation_config.do_sample:
+                generation_config.num_beams = 1
 
             generate_kwargs = copy.copy(kwargs)
             for key in ["do_sample", "temperature", "num_beams"]:
@@ -1095,20 +1093,15 @@ def replace_or_add(lst: List[int], num: int, itr: Iterator[int]):
         task = getattr(generation_config, "task", None)
         language = getattr(generation_config, "language", None)
 
-        if kwargs.get("forced_decoder_ids", None) is not None:
-            forced_decoder_ids = kwargs["forced_decoder_ids"]
-        elif hasattr(generation_config, "forced_decoder_ids") and generation_config.forced_decoder_ids is not None:
-            forced_decoder_ids = generation_config.forced_decoder_ids
-
+        forced_decoder_ids = generation_config.forced_decoder_ids
+        if forced_decoder_ids is not None:
             if language is None and task is None and forced_decoder_ids[0][1] is None:
                 logger.warning_once(
                     "Due to a bug fix in https://github.com/huggingface/transformers/pull/28687 transcription using a multilingual Whisper will default to language detection followed by transcription instead of translation to English."
                     "This might be a breaking change for your use case. If you want to instead always translate your audio to English, make sure to pass `language='en'`."
                 )
         elif hasattr(config, "forced_decoder_ids") and config.forced_decoder_ids is not None:
             forced_decoder_ids = config.forced_decoder_ids
-        else:
-            forced_decoder_ids = None
 
         if forced_decoder_ids is not None and task is not None:
             logger.info(
@@ -1288,21 +1281,6 @@ def _check_decoder_input_ids(kwargs):
                 "Passing `decoder_input_ids` is deprecated. Consider passing `prompt_ids` instead.",
             )
 
-    @staticmethod
-    def _set_token_ids(generation_config, config, kwargs):
-        eos_token_id = kwargs.pop("eos_token_id", None)
-        decoder_start_token_id = kwargs.pop("decoder_start_token_id", None)
-
-        eos_token_id = eos_token_id if eos_token_id is not None else generation_config.eos_token_id
-        decoder_start_token_id = (
-            decoder_start_token_id if decoder_start_token_id is not None else generation_config.decoder_start_token_id
-        )
-
-        generation_config.eos_token_id = eos_token_id if eos_token_id is not None else config.eos_token_id
-        generation_config.decoder_start_token_id = (
-            decoder_start_token_id if decoder_start_token_id is not None else config.decoder_start_token_id
-        )
-
     @staticmethod
     def _set_num_frames(return_token_timestamps, generation_config, kwargs):
         if return_token_timestamps:
@@ -1313,7 +1291,6 @@ def _set_num_frames(return_token_timestamps, generation_config, kwargs):
                     "Model generation config has no `alignment_heads`, token-level timestamps not available. "
                     "See https://gist.github.com/hollance/42e32852f24243b748ae6bc1f985b13a on how to add this property to the generation config."
                 )
-
             generation_config.num_frames = kwargs.pop("num_frames", None)
 
     @staticmethod
@@ -1517,47 +1494,21 @@ def _prepare_decoder_input_ids(
         return decoder_input_ids, kwargs
 
     @staticmethod
-    def _set_max_new_tokens_and_length(config, decoder_input_ids, generation_config, kwargs):
+    def _set_max_new_tokens_and_length(config, decoder_input_ids, generation_config):
         num_initial_tokens = min(config.max_target_positions // 2 - 1, decoder_input_ids.shape[-1] - 1)
 
-        passed_max_length = kwargs.pop("max_length", None)
-        passed_max_new_tokens = kwargs.pop("max_new_tokens", None)
-        max_length_config = getattr(generation_config, "max_length", None)
-        max_new_tokens_config = getattr(generation_config, "max_new_tokens", None)
-
-        max_new_tokens = None
-        max_length = None
-
         # Make sure we don't get larger than `max_length`
-        if passed_max_length is not None and passed_max_new_tokens is None:
-            max_length = min(passed_max_length + num_initial_tokens, config.max_target_positions)
-            logger.info(
-                f"Increase max_length from {passed_max_length} to {max_length} since input is conditioned on previous segment."
-            )
-        elif max_length_config is not None and passed_max_new_tokens is None and max_new_tokens_config is None:
+        if generation_config.max_length is not None and generation_config.max_new_tokens is None:
             max_length = min(generation_config.max_length + num_initial_tokens, config.max_target_positions)
             logger.info(
-                f"Increase max_length from {max_length_config} to {max_length} since input is conditioned on previous segment."
+                f"Increase max_length from {generation_config.max_length} to {max_length} since input is conditioned on previous segment."
             )
         elif (
-            passed_max_new_tokens is not None
-            and passed_max_new_tokens + decoder_input_ids.shape[-1] > config.max_target_positions
+            generation_config.max_new_tokens is not None
+            and generation_config.max_new_tokens + decoder_input_ids.shape[-1] > config.max_target_positions
         ):
             max_new_tokens = config.max_target_positions - decoder_input_ids.shape[-1]
-        elif (
-            passed_max_new_tokens is None
-            and max_new_tokens_config is not None
-            and max_new_tokens_config + decoder_input_ids.shape[-1] > config.max_target_positions
-        ):
-            max_new_tokens = config.max_target_positions - decoder_input_ids.shape[-1]
-
-        if max_new_tokens is not None:
-            kwargs["max_new_tokens"] = max_new_tokens
-
-        if max_length is not None:
-            kwargs["max_length"] = max_length
-
-        return kwargs
+            generation_config.max_new_tokens = max_new_tokens
 
     @staticmethod
     def _retrieve_compression_ratio(tokens, vocab_size):