2019-05-24 13:20:41 +08:00
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# Copyright (c) 2019 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 jin 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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import os
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2023-03-02 18:57:07 +08:00
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2019-05-28 21:31:28 +08:00
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from ..framework import Parameter
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2022-06-05 10:58:58 +08:00
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2019-05-24 13:20:41 +08:00
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__parallel_ctx__clz__ = None
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def _is_data_parallel_mode():
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global __parallel_ctx__clz__
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2022-10-23 20:01:27 +08:00
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return (
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__parallel_ctx__clz__ is not None
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and int(os.getenv("PADDLE_TRAINERS_NUM", "1")) > 1
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)
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2019-05-24 13:20:41 +08:00
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2020-08-28 14:46:28 +08:00
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def _is_parallel_ctx_initialized():
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global __parallel_ctx__clz__
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return __parallel_ctx__clz__ is not None
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2021-12-06 09:01:15 +08:00
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def _set_parallel_ctx(ccl_parallel_context):
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2019-05-24 13:20:41 +08:00
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global __parallel_ctx__clz__
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2025-08-21 02:00:58 +08:00
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assert __parallel_ctx__clz__ is None, (
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"ParallelContext can only be initialized once."
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)
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2021-12-06 09:01:15 +08:00
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__parallel_ctx__clz__ = ccl_parallel_context
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2019-05-24 13:20:41 +08:00
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def _init_parallel_ctx():
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global __parallel_ctx__clz__
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2025-08-21 02:00:58 +08:00
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assert __parallel_ctx__clz__ is not None, (
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"ParallelContext should be initialized."
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)
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2019-05-24 13:20:41 +08:00
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__parallel_ctx__clz__.init()
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def _broadcast_parameters(parameters):
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2023-03-02 18:57:07 +08:00
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from ..distributed import broadcast
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2019-05-24 13:20:41 +08:00
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for param in parameters:
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2020-12-31 13:13:44 +08:00
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# In model parallel, some parameters are split into multiple devices,
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# so we could not broadcast these parameters.
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2022-10-23 20:01:27 +08:00
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if param.is_distributed:
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continue
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2019-05-28 21:31:28 +08:00
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if isinstance(param, Parameter) and param.trainable:
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2023-03-02 18:57:07 +08:00
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broadcast(param, 0, sync_op=True)
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