Generate: text generation pipeline no longer emits max_length warning when it is not set (#23139)

src/transformers/pipelines/text_generation.py

@@ -1,3 +1,4 @@
+import copy
 import enum
 import warnings
 
@@ -105,17 +106,8 @@ class TextGenerationPipeline(Pipeline):
             prefix_inputs = self.tokenizer(
                 prefix, padding=False, add_special_tokens=False, return_tensors=self.framework
             )
-            prefix_length = prefix_inputs["input_ids"].shape[-1]
+            generate_kwargs["prefix_length"] = prefix_inputs["input_ids"].shape[-1]
 
-            if "max_new_tokens" in generate_kwargs:
-                pass
-            elif "max_length" in generate_kwargs:
-                generate_kwargs["max_length"] += prefix_length
-            else:
-                generate_kwargs["max_length"] = self.model.config.max_length + prefix_length
-
-            if "min_length" in generate_kwargs:
-                generate_kwargs["min_length"] += prefix_length
         if handle_long_generation is not None:
             if handle_long_generation not in {"hole"}:
                 raise ValueError(
@@ -247,6 +239,26 @@ class TextGenerationPipeline(Pipeline):
         else:
             in_b = input_ids.shape[0]
         prompt_text = model_inputs.pop("prompt_text")
+
+        # If there is a prefix, we may need to adjust the generation length. Do so without permanently modifying
+        # generate_kwargs, as some of the parameterization may come from the initialization of the pipeline.
+        generate_kwargs = copy.deepcopy(generate_kwargs)
+        prefix_length = generate_kwargs.pop("prefix_length", 0)
+        if prefix_length > 0:
+            has_max_new_tokens = "max_new_tokens" in generate_kwargs or (
+                "generation_config" in generate_kwargs
+                and generate_kwargs["generation_config"].max_new_tokens is not None
+            )
+            if not has_max_new_tokens:
+                generate_kwargs["max_length"] = generate_kwargs.get("max_length") or self.model.config.max_length
+                generate_kwargs["max_length"] += prefix_length
+            has_min_new_tokens = "min_new_tokens" in generate_kwargs or (
+                "generation_config" in generate_kwargs
+                and generate_kwargs["generation_config"].min_new_tokens is not None
+            )
+            if not has_min_new_tokens and "min_length" in generate_kwargs:
+                generate_kwargs["min_length"] += prefix_length
+
         # BS x SL
         generated_sequence = self.model.generate(input_ids=input_ids, attention_mask=attention_mask, **generate_kwargs)
         out_b = generated_sequence.shape[0]