38 lines
1.5 KiB
Python
38 lines
1.5 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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import torch
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import torch.nn as nn
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from vllm.config import LoadConfig, ModelConfig, VllmConfig
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from vllm.model_executor.model_loader.base_loader import BaseModelLoader
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from vllm.model_executor.model_loader.utils import (
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initialize_model, process_weights_after_loading, set_default_torch_dtype)
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from vllm.model_executor.model_loader.weight_utils import (
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initialize_dummy_weights)
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class DummyModelLoader(BaseModelLoader):
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"""Model loader that will set model weights to random values."""
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def __init__(self, load_config: LoadConfig):
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super().__init__(load_config)
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if load_config.model_loader_extra_config:
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raise ValueError(f"Model loader extra config is not supported for "
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f"load format {load_config.load_format}")
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def download_model(self, model_config: ModelConfig) -> None:
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pass # Nothing to download
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def load_model(self, vllm_config: VllmConfig,
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model_config: ModelConfig) -> nn.Module:
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device_config = vllm_config.device_config
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target_device = torch.device(device_config.device)
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with set_default_torch_dtype(model_config.dtype):
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with target_device:
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model = initialize_model(vllm_config=vllm_config)
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# NOTE(woosuk): For accurate performance evaluation, we assign
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# random values to the weights.
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initialize_dummy_weights(model)
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process_weights_after_loading(model, model_config, target_device)
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return model.eval()
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