Sync from v0.13

vllm/model_executor/model_loader/base_loader.py

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+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+from abc import ABC, abstractmethod
+
+import torch
+import torch.nn as nn
+
+from vllm.config import ModelConfig, VllmConfig
+from vllm.config.load import LoadConfig
+from vllm.logger import init_logger
+from vllm.model_executor.model_loader.utils import (
+    initialize_model,
+    process_weights_after_loading,
+)
+from vllm.utils.torch_utils import set_default_torch_dtype
+
+logger = init_logger(__name__)
+
+
+class BaseModelLoader(ABC):
+    """Base class for model loaders."""
+
+    def __init__(self, load_config: LoadConfig):
+        self.load_config = load_config
+
+    @abstractmethod
+    def download_model(self, model_config: ModelConfig) -> None:
+        """Download a model so that it can be immediately loaded."""
+        raise NotImplementedError
+
+    @abstractmethod
+    def load_weights(self, model: nn.Module, model_config: ModelConfig) -> None:
+        """Load weights into a model. This standalone API allows
+        inplace weights loading for an already-initialized model"""
+        raise NotImplementedError
+
+    def load_model(
+        self, vllm_config: VllmConfig, model_config: ModelConfig
+    ) -> nn.Module:
+        """Load a model with the given configurations."""
+        device_config = vllm_config.device_config
+        load_config = vllm_config.load_config
+        load_device = (
+            device_config.device if load_config.device is None else load_config.device
+        )
+        target_device = torch.device(load_device)
+        with set_default_torch_dtype(model_config.dtype):
+            with target_device:
+                model = initialize_model(
+                    vllm_config=vllm_config, model_config=model_config
+                )
+
+            logger.debug("Loading weights on %s ...", load_device)
+            # Quantization does not happen in `load_weights` but after it
+            self.load_weights(model, model_config)
+            process_weights_after_loading(model, model_config, target_device)
+        return model.eval()