[Model][Pixtral] Optimizations for input_processor_for_pixtral_hf (vl…

…lm-project#9514)

vllm/model_executor/models/pixtral.py

@@ -701,63 +701,64 @@ def input_processor_for_pixtral_hf(
     new_prompt = inputs.get("prompt")
     new_token_ids = inputs["prompt_token_ids"]
 
+    image_token = processor.image_token
+    image_break_token = processor.image_break_token
+    image_end_token = processor.image_end_token
+
     # Update new_prompt if present
     if new_prompt:
-        replace_strings = []
-        for image in image_data:
-            w, h = image.size
+        parts = new_prompt.split(image_token)
+        assert len(parts) - 1 == len(image_data)
+        new_parts = [parts[0]]  # Start with the part before any image tokens
 
+        for image, next_part in zip(image_data, parts[1:]):
+            w, h = image.size
             (num_width_tokens,
              num_height_tokens) = get_pixtral_hf_image_feature_size(
                  hf_config, image_width=w, image_height=h)
 
-            replace_tokens = [[processor.image_token] * num_width_tokens +
-                              [processor.image_break_token]
-                              ] * num_height_tokens
-            # Flatten list
-            replace_tokens = [
-                item for sublist in replace_tokens for item in sublist
+            replace_tokens = [image_token] * num_width_tokens + [
+                image_break_token
             ]
-            replace_tokens[-1] = processor.image_end_token
-            replace_str = "".join(replace_tokens)
-            replace_strings.append(replace_str)
-            new_prompt = new_prompt.replace(processor.image_token,
-                                            "<placeholder>", 1)
+            replace_tokens = replace_tokens * num_height_tokens
+            replace_tokens[-1] = image_end_token
 
-        while "<placeholder>" in new_prompt:
-            replace_str = replace_strings.pop(0)
-            new_prompt = new_prompt.replace("<placeholder>", replace_str, 1)
+            new_parts.append("".join(replace_tokens))
+            new_parts.append(next_part)
+
+        new_prompt = "".join(new_parts)
 
     # Update new_token_ids
-    image_token_id = 10
-    image_break_id = 12
-    image_end_id = 13
+    convert_tokens_to_ids = processor.tokenizer.convert_tokens_to_ids
+    image_token_id = convert_tokens_to_ids(image_token)
+    image_break_id = convert_tokens_to_ids(image_break_token)
+    image_end_id = convert_tokens_to_ids(image_end_token)
     placeholder_token_id = -999
+    # Find all image token indices at once
+    placeholder_indices = [
+        idx for idx, token_id in enumerate(new_token_ids)
+        if token_id == image_token_id
+    ]
+    assert len(placeholder_indices) == len(image_data)
     replace_tokens_list = []
-    for image in image_data:
-        w, h = image.size
+    for placeholder_idx, image in zip(placeholder_indices, image_data):
+        new_token_ids[placeholder_idx] = placeholder_token_id
 
-        num_width_tokens, num_height_tokens = get_pixtral_hf_image_feature_size(
-            hf_config, image_width=w, image_height=h)
+        w, h = image.size
+        (num_width_tokens,
+         num_height_tokens) = get_pixtral_hf_image_feature_size(hf_config,
+                                                                image_width=w,
+                                                                image_height=h)
 
-        replace_tokens = [[image_token_id] * num_width_tokens +
-                          [image_break_id]] * num_height_tokens
-        # Flatten list
-        replace_tokens = [
-            item for sublist in replace_tokens for item in sublist
-        ]
+        replace_tokens = [image_token_id] * num_width_tokens + [image_break_id]
+        replace_tokens = replace_tokens * num_height_tokens
         replace_tokens[-1] = image_end_id
         replace_tokens_list.append(replace_tokens)
-        # Replace image id with placeholder id
-        next_image_index = new_token_ids.index(image_token_id)
-        new_token_ids[next_image_index] = placeholder_token_id
-
-    while placeholder_token_id in new_token_ids:
-        replace_tokens = replace_tokens_list.pop(0)
-        next_image_index = new_token_ids.index(placeholder_token_id)
-        prefix = new_token_ids[:next_image_index]
-        postfix = new_token_ids[next_image_index + 1:]
-        new_token_ids = prefix + replace_tokens + postfix
+
+    # Backward iteration for replacement without affecting known indices
+    for placeholder_idx, replace_tokens in zip(reversed(placeholder_indices),
+                                               reversed(replace_tokens_list)):
+        new_token_ids[placeholder_idx:placeholder_idx + 1] = replace_tokens
 
     # NOTE: Create a defensive copy of the original inputs
     return token_inputs(prompt_token_ids=new_token_ids,