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58 lines
2.3 KiB
Python
58 lines
2.3 KiB
Python
"""
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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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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"""
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from fastdeploy import envs
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from fastdeploy.config import FDConfig
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from fastdeploy.model_executor.layers.attention import IluvatarAttnBackend
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from fastdeploy.worker.gpu_model_runner import GPUModelRunner
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class IluvatarModelRunner(GPUModelRunner):
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def __init__(
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self,
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fd_config: FDConfig,
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device: str, # logic device
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device_id: int, # physical device id
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rank: int,
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local_rank: int,
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):
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super(IluvatarModelRunner, self).__init__(
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fd_config=fd_config, device=device, device_id=device_id, rank=rank, local_rank=local_rank
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)
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assert not self.speculative_decoding, "Iluvatar does not support speculative decoding"
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assert self.guided_backend is None, "Iluvatar does not support guided decoding"
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assert not envs.ENABLE_V1_KVCACHE_SCHEDULER, "Iluvatar does not support v1 kvcache scheduler"
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assert not self.cache_config.enable_prefix_caching, "Iluvatar does not support prefix caching"
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def initialize_attn_backend(self) -> None:
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"""
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Initialize attention backends
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"""
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assert len(self.attn_backends) == 0
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num_heads = self.model_config.num_attention_heads // self.parallel_config.tensor_parallel_size
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self.model_config.kv_num_heads = max(
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1,
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int(self.model_config.num_key_value_heads) // self.parallel_config.tensor_parallel_size,
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)
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attn_backend = IluvatarAttnBackend(
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self.fd_config,
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kv_num_heads=self.model_config.kv_num_heads,
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num_heads=num_heads,
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head_dim=self.model_config.head_dim,
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)
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self.attn_backends.append(attn_backend)
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