Update model_loader deps and qqq quantization deps (#2220) (#2318)

Co-authored-by: HandH1998 <1335248067@qq.com>

python/sglang/srt/model_loader/utils.py

@@ -0,0 +1,41 @@
+# Adapted from https://github.com/vllm-project/vllm/blob/v0.6.4.post1/vllm/model_executor/model_loader/utils.py
+
+"""Utilities for selecting and loading models."""
+import contextlib
+from typing import Tuple, Type
+
+import torch
+from torch import nn
+
+from sglang.srt.configs.model_config import ModelConfig
+
+
+@contextlib.contextmanager
+def set_default_torch_dtype(dtype: torch.dtype):
+    """Sets the default torch dtype to the given dtype."""
+    old_dtype = torch.get_default_dtype()
+    torch.set_default_dtype(dtype)
+    yield
+    torch.set_default_dtype(old_dtype)
+
+
+def get_model_architecture(model_config: ModelConfig) -> Tuple[Type[nn.Module], str]:
+    from sglang.srt.models.registry import ModelRegistry
+
+    architectures = getattr(model_config.hf_config, "architectures", [])
+    # Special handling for quantized Mixtral.
+    # FIXME(woosuk): This is a temporary hack.
+    mixtral_supported = ["fp8", "compressed-tensors", "gptq_marlin", "awq_marlin"]
+
+    if (
+        model_config.quantization is not None
+        and model_config.quantization not in mixtral_supported
+        and "MixtralForCausalLM" in architectures
+    ):
+        architectures = ["QuantMixtralForCausalLM"]
+
+    return ModelRegistry.resolve_model_cls(architectures)
+
+
+def get_architecture_class_name(model_config: ModelConfig) -> str:
+    return get_model_architecture(model_config)[1]