mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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e70e2279ce
* [XPU] xpu support PD disaggregation * [XPU] fix the issue of cache KV transfer process startup failure on non-zero XPU cards * [XPU] xpu support PD disaggregation in v1 scheduler --------- Co-authored-by: ddchenhao66 <dhaochen163.com>
43 lines
1.4 KiB
Python
43 lines
1.4 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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import os
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from fastdeploy.config import FDConfig
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from fastdeploy.platforms import current_platform
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def init_rank_and_device_id(fd_config: FDConfig):
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""" """
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rank = (
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fd_config.parallel_config.local_data_parallel_id * fd_config.parallel_config.tensor_parallel_size
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+ fd_config.parallel_config.tensor_parallel_rank
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)
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if current_platform.is_xpu():
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cuda_visible_devices = os.getenv("XPU_VISIBLE_DEVICES", None)
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else: # default cuda
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cuda_visible_devices = os.getenv("CUDA_VISIBLE_DEVICES", None)
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if cuda_visible_devices is None:
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device_id = rank
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else:
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cuda_visible_devices = cuda_visible_devices.split(",")
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rank_index = rank % len(cuda_visible_devices)
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device_id = cuda_visible_devices[rank_index]
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return rank, device_id
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