wehub-resource-sync
71 lines
2.2 KiB
Python
71 lines
2.2 KiB
Python
# Copyright (c) 2020 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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import numpy as np
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from legacy_test.test_collective_api_base import (
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TestCollectiveAPIRunnerBase,
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runtime_main,
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)
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import paddle
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from paddle import base
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from paddle.distributed import fleet
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paddle.enable_static()
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class TestRowParallelLinearAPI(TestCollectiveAPIRunnerBase):
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def __init__(self):
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self.global_ring_id = 0
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def get_model(self, main_prog, startup_program, rank, dtype='float32'):
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with base.program_guard(main_prog, startup_program):
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fleet.init(is_collective=True)
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np.random.seed(2020)
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np_array = np.random.rand(1000, 16)
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data = paddle.static.data(
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name='tindata', shape=[10, 1000], dtype=dtype
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)
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paddle.distributed.broadcast(data, src=0)
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data = paddle.split(data, 2, axis=1)[rank]
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if rank == 0:
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param_attr = paddle.base.ParamAttr(
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initializer=paddle.nn.initializer.Assign(
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np_array[0:500, :]
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),
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)
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else:
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param_attr = paddle.base.ParamAttr(
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initializer=paddle.nn.initializer.Assign(
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np_array[500:1000, :]
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),
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)
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linear_out = paddle.distributed.split(
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data,
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size=(1000, 16),
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operation='linear',
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axis=0,
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num_partitions=2,
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weight_attr=param_attr,
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bias_attr=True,
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)
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return [linear_out]
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if __name__ == "__main__":
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runtime_main(TestRowParallelLinearAPI, "row_parallel_linear")
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