fix(vLLM): importlib relative import

ChatTTS/model/velocity/model_loader.py

@@ -1,16 +1,15 @@
 """Utilities for selecting and loading models."""
 
 import contextlib
-from typing import Type
 
 import torch
 import torch.nn as nn
-from transformers import PretrainedConfig
 
 from vllm.config import ModelConfig
 from vllm.model_executor.models import ModelRegistry
 from vllm.model_executor.weight_utils import get_quant_config, initialize_dummy_weights
-import importlib
+
+from .llama import LlamaModel
 
 
 @contextlib.contextmanager
@@ -22,16 +21,7 @@ def _set_default_torch_dtype(dtype: torch.dtype):
     torch.set_default_dtype(old_dtype)
 
 
-def _get_model_architecture(config: PretrainedConfig) -> Type[nn.Module]:
-    model_cls = getattr(
-        importlib.import_module(".llama"), "LlamaModel", None
-    )
-    return model_cls
-
-
 def get_model(model_config: ModelConfig) -> nn.Module:
-    model_class = _get_model_architecture(model_config.hf_config)
-
     # Get the (maybe quantized) linear method.
     linear_method = None
     if model_config.quantization is not None:
@@ -63,7 +53,7 @@ def get_model(model_config: ModelConfig) -> nn.Module:
         # Create a model instance.
         # The weights will be initialized as empty tensors.
         with torch.device("cuda"):
-            model = model_class(model_config.hf_config, linear_method)
+            model = LlamaModel(model_config.hf_config, linear_method)
         if model_config.load_format == "dummy":
             # NOTE(woosuk): For accurate performance evaluation, we assign
             # random values to the weights.