Rename

Author: DarkLight1337

vllm/model_executor/models/blip2.py

@@ -20,7 +20,7 @@
 from .blip import (BlipVisionModel, dummy_image_for_blip,
                    get_max_blip_image_tokens)
 from .interfaces import SupportsMultiModal, SupportsPP
-from .utils import (WeightLoader, init_vllm_registered_model,
+from .utils import (AutoWeightsLoader, init_vllm_registered_model,
                     merge_multimodal_embeddings)
 
 # We use this internally as placeholders since there is no image token
@@ -686,5 +686,5 @@ def sample(
         return self.language_model.sample(logits, sampling_metadata)
 
     def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
-        loader = WeightLoader(self)
+        loader = AutoWeightsLoader(self)
         loader.load_weights(weights)

vllm/model_executor/models/fuyu.py

@@ -41,7 +41,7 @@
                            SequenceData)
 
 from .interfaces import SupportsMultiModal, SupportsPP
-from .utils import WeightLoader, flatten_bn, merge_multimodal_embeddings
+from .utils import AutoWeightsLoader, flatten_bn, merge_multimodal_embeddings
 
 # Cannot find the following 2 numbers from hf config.
 _IMAGE_TOKEN_ID = 71011
@@ -347,5 +347,5 @@ def sample(
         return next_tokens
 
     def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
-        loader = WeightLoader(self)
+        loader = AutoWeightsLoader(self)
         loader.load_weights(weights)

vllm/model_executor/models/gemma2.py

@@ -40,7 +40,7 @@
 from vllm.sequence import IntermediateTensors
 
 from .interfaces import SupportsLoRA, SupportsPP
-from .utils import (WeightLoader, is_pp_missing_parameter,
+from .utils import (AutoWeightsLoader, is_pp_missing_parameter,
                     make_empty_intermediate_tensors_factory, make_layers)
 
 logger = init_logger(__name__)
@@ -434,7 +434,8 @@ def sample(
         return next_tokens
 
     def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
-        loader = WeightLoader(self,
-                              allow_missing_prefixes=None if
-                              self.config.tie_word_embeddings else ["lm_head"])
+        loader = AutoWeightsLoader(
+            self,
+            allow_missing_prefixes=None
+            if self.config.tie_word_embeddings else ["lm_head"])
         loader.load_weights(weights)

vllm/model_executor/models/internvl.py

@@ -31,7 +31,7 @@
 from .clip import (dummy_image_for_clip, dummy_seq_data_for_clip,
                    get_clip_num_patches)
 from .interfaces import SupportsMultiModal, SupportsPP
-from .utils import (WeightLoader, flatten_bn, init_vllm_registered_model,
+from .utils import (AutoWeightsLoader, flatten_bn, init_vllm_registered_model,
                     merge_multimodal_embeddings)
 
 IMG_START = '<img>'
@@ -608,5 +608,5 @@ def sample(
         return self.language_model.sample(logits, sampling_metadata)
 
     def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
-        loader = WeightLoader(self)
+        loader = AutoWeightsLoader(self)
         loader.load_weights(weights)

vllm/model_executor/models/llama.py

@@ -51,7 +51,7 @@
 from vllm.utils import is_hip
 
 from .interfaces import SupportsLoRA, SupportsPP
-from .utils import (PPMissingLayer, WeightLoader, is_pp_missing_parameter,
+from .utils import (AutoWeightsLoader, PPMissingLayer, is_pp_missing_parameter,
                     make_empty_intermediate_tensors_factory, make_layers)
 
 
@@ -550,9 +550,10 @@ def sample(self, logits: torch.Tensor,
         return next_tokens
 
     def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
-        loader = WeightLoader(self,
-                              allow_missing_prefixes=None if
-                              self.config.tie_word_embeddings else ["lm_head"])
+        loader = AutoWeightsLoader(
+            self,
+            allow_missing_prefixes=None
+            if self.config.tie_word_embeddings else ["lm_head"])
         loader.load_weights(
             self.maybe_remap_mistral(name, loaded_weight)
             for name, loaded_weight in weights)

vllm/model_executor/models/llava.py

@@ -25,7 +25,7 @@
 from .siglip import (SiglipVisionModel, dummy_image_for_siglip,
                      dummy_seq_data_for_siglip, get_max_siglip_image_tokens,
                      input_processor_for_siglip)
-from .utils import (WeightLoader, flatten_bn, init_vllm_registered_model,
+from .utils import (AutoWeightsLoader, flatten_bn, init_vllm_registered_model,
                     merge_multimodal_embeddings)
 
 
@@ -405,5 +405,5 @@ def sample(
         return self.language_model.sample(logits, sampling_metadata)
 
     def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
-        loader = WeightLoader(self)
+        loader = AutoWeightsLoader(self)
         loader.load_weights(weights)

vllm/model_executor/models/llava_next.py

@@ -28,7 +28,7 @@
 from .siglip import (SiglipVisionModel, dummy_image_for_siglip,
                      dummy_seq_data_for_siglip, get_siglip_image_feature_size,
                      get_siglip_patch_grid_length, input_processor_for_siglip)
-from .utils import (WeightLoader, flatten_bn, init_vllm_registered_model,
+from .utils import (AutoWeightsLoader, flatten_bn, init_vllm_registered_model,
                     merge_multimodal_embeddings)
 
 # Result in the max possible feature size (2x2 grid of 336x336px tiles)
@@ -641,5 +641,5 @@ def sample(
         return self.language_model.sample(logits, sampling_metadata)
 
     def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
-        loader = WeightLoader(self)
+        loader = AutoWeightsLoader(self)
         loader.load_weights(weights)

vllm/model_executor/models/llava_next_video.py

@@ -27,7 +27,7 @@
 from .interfaces import SupportsMultiModal, SupportsPP
 from .siglip import (SiglipVisionModel, dummy_image_for_siglip,
                      dummy_seq_data_for_siglip)
-from .utils import (WeightLoader, init_vllm_registered_model,
+from .utils import (AutoWeightsLoader, init_vllm_registered_model,
                     merge_multimodal_embeddings)
 
 # For profile run
@@ -457,5 +457,5 @@ def sample(
         return self.language_model.sample(logits, sampling_metadata)
 
     def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
-        loader = WeightLoader(self)
+        loader = AutoWeightsLoader(self)
         loader.load_weights(weights)

vllm/model_executor/models/llava_onevision.py

@@ -34,7 +34,7 @@
 from .siglip import (SiglipVisionModel, dummy_seq_data_for_siglip,
                      dummy_video_for_siglip, get_siglip_image_feature_size,
                      get_siglip_patch_grid_length, input_processor_for_siglip)
-from .utils import (WeightLoader, flatten_bn, init_vllm_registered_model,
+from .utils import (AutoWeightsLoader, flatten_bn, init_vllm_registered_model,
                     merge_multimodal_embeddings)
 
 logger = init_logger(__name__)
@@ -871,5 +871,5 @@ def sample(
         return self.language_model.sample(logits, sampling_metadata)
 
     def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
-        loader = WeightLoader(self)
+        loader = AutoWeightsLoader(self)
         loader.load_weights(weights)

vllm/model_executor/models/paligemma.py

@@ -20,7 +20,7 @@
 from .interfaces import SupportsMultiModal, SupportsPP
 from .siglip import (SiglipVisionModel, dummy_image_for_siglip,
                      dummy_seq_data_for_siglip, get_max_siglip_image_tokens)
-from .utils import WeightLoader, merge_multimodal_embeddings
+from .utils import AutoWeightsLoader, merge_multimodal_embeddings
 
 logger = init_logger(__name__)
 
@@ -291,5 +291,5 @@ def sample(
         return self.language_model.sample(logits, sampling_metadata)
 
     def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
-        loader = WeightLoader(self)
+        loader = AutoWeightsLoader(self)
         loader.load_weights(weights)