56 lines
2.4 KiB
Python
56 lines
2.4 KiB
Python
#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# Copyright 2023 The vLLM team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This file is a part of the vllm-ascend project.
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# Adapted from vllm-project/vllm/vllm/worker/gpu_model_runner.py
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# isort: skip_file
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import torch.nn as nn
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from vllm.config import CUDAGraphMode
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from vllm.v1.kv_cache_interface import KVCacheConfig
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from vllm_ascend.worker.model_runner_v1 import NPUModelRunner
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class XliteModelRunner(NPUModelRunner):
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def get_model(self) -> nn.Module:
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"""See :meth:`NPUModelRunner.get_model` and :meth:`XliteWrapper.unwrap` for details."""
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if not hasattr(self, "xlite_model"):
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return super().get_model()
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return self.xlite_model.unwrap()
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def load_model(self) -> None:
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from vllm_ascend.xlite.xlite import XliteWrapper
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super().load_model()
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self.model = self.xlite_model = XliteWrapper(self.model, self.vllm_config, device=self.device)
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def initialize_kv_cache(self, kv_cache_config: KVCacheConfig) -> None:
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super().initialize_kv_cache(kv_cache_config)
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self.xlite_model.register_kv_caches(self.kv_caches)
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def _should_build_dummy_attn_metadata(
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self,
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force_attention: bool = False,
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is_profile: bool = False,
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cudagraph_runtime_mode: CUDAGraphMode | None = None,
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) -> bool:
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"""
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Override to build attention metadata during dummy_run when xlite is enable.
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For xlite, we need to build metadata during DP dummy_run to ensure all ranks
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have consistent metadata, even when some ranks have no requests.
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"""
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base_condition = super()._should_build_dummy_attn_metadata(force_attention, is_profile, cudagraph_runtime_mode)
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xlite_condition = self.ascend_config.xlite_graph_config.enabled and not is_profile
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return base_condition or xlite_condition
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