[Misc][Refactor] Generalize linear_method to be quant_method (#4373)

vllm/model_executor/models/llava.py

@@ -9,8 +9,9 @@ from transformers import CLIPVisionModel, LlavaConfig
 from vllm.attention import AttentionMetadata
 from vllm.config import VisionLanguageConfig
 from vllm.model_executor.layers.activation import get_act_fn
-from vllm.model_executor.layers.linear import LinearMethodBase
 from vllm.model_executor.layers.logits_processor import LogitsProcessor
+from vllm.model_executor.layers.quantization.base_config import (
+    QuantizationConfig)
 from vllm.model_executor.layers.sampler import Sampler
 from vllm.model_executor.layers.vocab_parallel_embedding import ParallelLMHead
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
@@ -61,7 +62,7 @@ class LlavaForConditionalGeneration(nn.Module):
     def __init__(self,
                  config: "LlavaConfig",
                  vision_language_config: VisionLanguageConfig,
-                 linear_method: Optional["LinearMethodBase"] = None) -> None:
+                 quant_config: Optional["QuantizationConfig"] = None) -> None:
         super().__init__()
         self.config = config
 
@@ -83,8 +84,8 @@ class LlavaForConditionalGeneration(nn.Module):
             text_hidden_size=config.text_config.hidden_size,
             projector_hidden_act=config.projector_hidden_act)
 
-        self.linear_method = linear_method
-        self.language_model = LlamaModel(config.text_config, linear_method)
+        self.quant_config = quant_config
+        self.language_model = LlamaModel(config.text_config, quant_config)
         self.unpadded_vocab_size = config.text_config.vocab_size
         self.lm_head = ParallelLMHead(
             self.unpadded_vocab_size,