Generate: Relaxed max_length and max_new_tokens coexistence (#21347)

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

src/transformers/generation/configuration_utils.py

@@ -63,14 +63,12 @@ class GenerationConfig(PushToHubMixin):
 
         max_length (`int`, *optional*, defaults to 20):
             The maximum length the generated tokens can have. Corresponds to the length of the input prompt +
-            `max_new_tokens`. In general, prefer the use of `max_new_tokens`, which ignores the number of tokens in the
+            `max_new_tokens`. Its effect is overridden by `max_new_tokens`, if also set.
-            prompt.
         max_new_tokens (`int`, *optional*):
             The maximum numbers of tokens to generate, ignoring the number of tokens in the prompt.
         min_length (`int`, *optional*, defaults to 0):
             The minimum length of the sequence to be generated. Corresponds to the length of the input prompt +
-            `min_new_tokens`. In general, prefer the use of `min_new_tokens`, which ignores the number of tokens in the
+            `min_new_tokens`. Its effect is overridden by `min_new_tokens`, if also set.
-            prompt.
         min_new_tokens (`int`, *optional*):
             The minimum numbers of tokens to generate, ignoring the number of tokens in the prompt.
         early_stopping (`bool`, *optional*, defaults to `False`):

src/transformers/generation/flax_utils.py

@@ -318,20 +318,20 @@ class FlaxGenerationMixin:
         has_default_max_length = kwargs.get("max_length") is None and generation_config.max_length is not None
         if has_default_max_length and generation_config.max_new_tokens is None:
             warnings.warn(
-                "Neither `max_length` nor `max_new_tokens` have been set, `max_length` will default to"
+                f"Using `max_length`'s default ({generation_config.max_length}) to control the generation length. "
-                f" {generation_config.max_length} (`generation_config.max_length`). Controlling `max_length` via the"
+                "This behaviour is deprecated and will be removed from the config in v5 of Transformers -- we"
-                " config is deprecated and `max_length` will be removed from the config in v5 of Transformers -- we"
                 " recommend using `max_new_tokens` to control the maximum length of the generation.",
                 UserWarning,
             )
-        elif has_default_max_length and generation_config.max_new_tokens is not None:
+        elif generation_config.max_new_tokens is not None:
             generation_config.max_length = generation_config.max_new_tokens + input_ids_seq_length
-        elif not has_default_max_length and generation_config.max_new_tokens is not None:
+            if not has_default_max_length:
-            raise ValueError(
+                logger.warn(
-                "Both `max_new_tokens` and `max_length` have been set but they serve the same purpose -- setting a"
+                    f"Both `max_new_tokens` (={generation_config.max_new_tokens}) and `max_length`(="
-                " limit to the generated output length. Remove one of those arguments. Please refer to the"
+                    f"{generation_config.max_length}) seem to have been set. `max_new_tokens` will take precedence. "
-                " documentation for more information. "
+                    "Please refer to the documentation for more information. "
-                "(https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)"
+                    "(https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)",
+                    UserWarning,
                 )
 
         if generation_config.min_length is not None and generation_config.min_length > generation_config.max_length:

src/transformers/generation/tf_utils.py

@@ -700,20 +700,20 @@ class TFGenerationMixin:
         has_default_max_length = kwargs.get("max_length") is None and generation_config.max_length is not None
         if has_default_max_length and generation_config.max_new_tokens is None:
             warnings.warn(
-                "Neither `max_length` nor `max_new_tokens` have been set, `max_length` will default to"
+                f"Using `max_length`'s default ({generation_config.max_length}) to control the generation length. "
-                f" {generation_config.max_length} (`generation_config.max_length`). Controlling `max_length` via the"
+                "This behaviour is deprecated and will be removed from the config in v5 of Transformers -- we"
-                " config is deprecated and `max_length` will be removed from the config in v5 of Transformers -- we"
                 " recommend using `max_new_tokens` to control the maximum length of the generation.",
                 UserWarning,
             )
-        elif has_default_max_length and generation_config.max_new_tokens is not None:
+        elif generation_config.max_new_tokens is not None:
             generation_config.max_length = generation_config.max_new_tokens + input_ids_seq_length
-        elif not has_default_max_length and generation_config.max_new_tokens is not None:
+            if not has_default_max_length:
-            raise ValueError(
+                logger.warn(
-                "Both `max_new_tokens` and `max_length` have been set but they serve the same purpose -- setting a"
+                    f"Both `max_new_tokens` (={generation_config.max_new_tokens}) and `max_length`(="
-                " limit to the generated output length. Remove one of those arguments. Please refer to the"
+                    f"{generation_config.max_length}) seem to have been set. `max_new_tokens` will take precedence. "
-                " documentation for more information. "
+                    "Please refer to the documentation for more information. "
-                "(https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)"
+                    "(https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)",
+                    UserWarning,
                 )
 
         if generation_config.min_length is not None and generation_config.min_length > generation_config.max_length:

src/transformers/generation/utils.py

@@ -1274,20 +1274,20 @@ class GenerationMixin:
         has_default_max_length = kwargs.get("max_length") is None and generation_config.max_length is not None
         if has_default_max_length and generation_config.max_new_tokens is None:
             warnings.warn(
-                "Neither `max_length` nor `max_new_tokens` has been set, `max_length` will default to"
+                f"Using `max_length`'s default ({generation_config.max_length}) to control the generation length. "
-                f" {generation_config.max_length} (`generation_config.max_length`). Controlling `max_length` via the"
+                "This behaviour is deprecated and will be removed from the config in v5 of Transformers -- we"
-                " config is deprecated and `max_length` will be removed from the config in v5 of Transformers -- we"
                 " recommend using `max_new_tokens` to control the maximum length of the generation.",
                 UserWarning,
             )
-        elif has_default_max_length and generation_config.max_new_tokens is not None:
+        elif generation_config.max_new_tokens is not None:
             generation_config.max_length = generation_config.max_new_tokens + input_ids_seq_length
-        elif not has_default_max_length and generation_config.max_new_tokens is not None:
+            if not has_default_max_length:
-            raise ValueError(
+                logger.warn(
-                "Both `max_new_tokens` and `max_length` have been set but they serve the same purpose -- setting a"
+                    f"Both `max_new_tokens` (={generation_config.max_new_tokens}) and `max_length`(="
-                " limit to the generated output length. Remove one of those arguments. Please refer to the"
+                    f"{generation_config.max_length}) seem to have been set. `max_new_tokens` will take precedence. "
-                " documentation for more information. "
+                    "Please refer to the documentation for more information. "
-                "(https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)"
+                    "(https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)",
+                    UserWarning,
                 )
 
         if generation_config.min_length is not None and generation_config.min_length > generation_config.max_length:

tests/generation/test_utils.py

@@ -2178,10 +2178,6 @@ class GenerationIntegrationTests(unittest.TestCase):
         # 1 BOS + 20 + 3 new tokens
         self.assertEqual(list(outputs.shape), [1, 24])
 
-        # max_new_tokens and max_length serve the same purpose and must not be used together.
-        with self.assertRaises(ValueError):
-            bart_model.generate(decoder_input_ids=input_ids, max_new_tokens=10, max_length=20)
-
     def test_max_new_tokens_decoder_only_contrastive_search_t5(self):
         article = """Justin Timberlake and Jessica Biel, welcome to parenthood."""
         t5_tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5")
@@ -2212,12 +2208,6 @@ class GenerationIntegrationTests(unittest.TestCase):
         # 1 BOS + 20 + 3 new tokens
         self.assertEqual(list(outputs.shape), [1, 24])
 
-        # max_new_tokens and max_length serve the same purpose and must not be used together.
-        with self.assertRaises(ValueError):
-            t5_model.generate(
-                decoder_input_ids=input_ids, max_new_tokens=10, max_length=20, penalty_alpha=0.6, top_k=4
-            )
-
     def test_max_new_tokens_decoder_only_contrastive_search_bart(self):
         article = """Justin Timberlake and Jessica Biel, welcome to parenthood."""
         bart_tokenizer = BartTokenizer.from_pretrained("hf-internal-testing/tiny-random-bart")
@@ -2250,12 +2240,6 @@ class GenerationIntegrationTests(unittest.TestCase):
         # 1 BOS + 20 + 3 new tokens
         self.assertEqual(list(outputs.shape), [1, 24])
 
-        # max_new_tokens and max_length serve the same purpose and must not be used together.
-        with self.assertRaises(ValueError):
-            bart_model.generate(
-                decoder_input_ids=input_ids, max_new_tokens=10, max_length=20, penalty_alpha=0.6, top_k=4
-            )
-
     def test_max_new_tokens_decoder_only_contrastive_search_gptj(self):
         article = """Justin Timberlake."""
         gptj_tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gptj")
@@ -2279,10 +2263,6 @@ class GenerationIntegrationTests(unittest.TestCase):
         # 1 BOS token + 23 new tokens
         self.assertEqual(list(outputs.shape), [1, 24])
 
-        # max_new_tokens and max_length serve the same purpose and must not be used together.
-        with self.assertRaises(ValueError):
-            gptj_model.generate(input_ids=input_ids, max_new_tokens=10, max_length=20, penalty_alpha=0.6, top_k=4)
-
     def test_max_new_tokens_decoder_only_contrastive_search_gpt2(self):
         article = """Justin Timberlake."""
         gpt2_tokenizer = GPT2Tokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2")
@@ -2306,10 +2286,6 @@ class GenerationIntegrationTests(unittest.TestCase):
         # 1 BOS token + 23 new tokens
         self.assertEqual(list(outputs.shape), [1, 24])
 
-        # max_new_tokens and max_length serve the same purpose and must not be used together.
-        with self.assertRaises(ValueError):
-            gpt2_model.generate(input_ids=input_ids, max_new_tokens=10, max_length=20, penalty_alpha=0.6, top_k=4)
-
     def test_max_new_tokens_decoder_only(self):
         article = """Justin Timberlake."""
         gpt2_tokenizer = GPT2Tokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2")
@@ -2333,10 +2309,6 @@ class GenerationIntegrationTests(unittest.TestCase):
         # 1 BOS token + 23 new tokens
         self.assertEqual(list(outputs.shape), [1, 24])
 
-        # max_new_tokens and max_length serve the same purpose and must not be used together.
-        with self.assertRaises(ValueError):
-            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."""
         tokenizer = BartTokenizer.from_pretrained("hf-internal-testing/tiny-random-bart")