super().collect_images->self.collect_images

lmdeploy/vl/model/cogvlm.py

@@ -77,7 +77,7 @@ def build_model(self):
 
     def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refer to the spec of `super().preprocess`"""
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, _ in images:
             image = image.convert('RGB')

lmdeploy/vl/model/deepseek.py

@@ -88,7 +88,7 @@ def build_model(self):
 
     def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refers to the spec of `super.preprocess()"""
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, _ in images:
             image = image.convert('RGB')

lmdeploy/vl/model/glm_4v.py

@@ -87,7 +87,7 @@ def build_model(self):
 
     def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refers to the spec of `super.preprocess()"""
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, params in images:
             image = image.convert('RGB')

lmdeploy/vl/model/internvl.py

@@ -198,7 +198,7 @@ def _forward(self, inputs):
 
     def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refers to `super.preprocess() for spec."""
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, params in images:
             image = image.convert('RGB')

lmdeploy/vl/model/llava.py

@@ -312,7 +312,7 @@ def encode_images(self, images: torch.Tensor) -> torch.Tensor:
 
     def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refer to `super().preprocess() for spec."""
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, params in images:
             image = image.convert('RGB')

lmdeploy/vl/model/llava_hf.py

@@ -59,7 +59,7 @@ def build_model(self):
 
     def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refers to `super.preprocess() for spec."""
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, params in images:
             image = image.convert('RGB')

lmdeploy/vl/model/llava_next.py

@@ -79,7 +79,7 @@ def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refers to the spec of `super.preprocess()"""
         from transformers.models.llava_next.modeling_llava_next import \
             image_size_to_num_patches
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, params in images:
             image = image.convert('RGB')

lmdeploy/vl/model/mllama.py

@@ -19,11 +19,11 @@ def build_preprocessor(self):
         self.image_token_id = 128256
 
     def build_model(self):
-        assert 0, 'cogvlm is not supported by turbomind'
+        assert 0, 'mllama is not supported by turbomind'
 
     def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refer to the spec of `super().preprocess`"""
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, params in images:
             image = image.convert('RGB')
@@ -77,4 +77,4 @@ def to_pytorch(self, messages, chat_template, tokenizer, sequence_start):
                                       sequence_start)
 
     def to_turbomind(self, messages, chat_template, sequence_start):
-        assert 0, 'cogvlm is not supported by turbomind'
+        assert 0, 'mllama is not supported by turbomind'

lmdeploy/vl/model/phi3_vision.py

@@ -128,7 +128,7 @@ def build_preprocessor(self):
                                                   trust_remote_code=True)
         if hasattr(processor, 'tokenizer'):
             del processor.tokenizer
-            processor.prtokenizer = None
+            processor.tokenizer = None
         self.processor = processor.image_processor
         self.processor = processor
 
@@ -184,7 +184,7 @@ def build_model(self):
 
     def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refers to `super.preprocess() for spec."""
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, params in images:
             image = image.convert('RGB')

lmdeploy/vl/model/qwen.py

@@ -74,7 +74,7 @@ def build_model(self):
 
     def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refers to `super.preprocess() for spec."""
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, params in images:
             image = image.convert('RGB')

lmdeploy/vl/model/qwen2.py

@@ -71,7 +71,7 @@ def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refer to `super().preprocess()` for spec."""
         from qwen_vl_utils import process_vision_info
 
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         optional_keys = {
             'resized_height', 'resized_width', 'min_pixels', 'max_pixels'
         }

lmdeploy/vl/model/xcomposer2.py

@@ -214,7 +214,7 @@ def _preprocess_4khd_7b(self, image: Image, params: Dict) -> Dict:
 
     def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refer to `super().preprocess() for spec."""
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, params in images:
             image = image.convert('RGB')

lmdeploy/vl/model/yi.py

@@ -124,7 +124,7 @@ def build_model(self):
 
     def preprocess(self, messages: List[Dict]) -> List[Dict]:
         """refer to `super().preprocess() for spec."""
-        images = super().collect_images(messages)
+        images = self.collect_images(messages)
         outputs = []
         for image, params in images:
             image = image.convert('RGB')