mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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3a6058e445
* add stable ci * fix * update * fix * rename tests dir;fix stable ci bug * add timeout limit * update
73 lines
2.2 KiB
Python
73 lines
2.2 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 unittest
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import numpy as np
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import paddle
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import paddle.distributed as dist
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from paddle.distributed import fleet
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from fastdeploy.distributed.custom_all_reduce import CustomAllreduce
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class Test(unittest.TestCase):
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def setUp(self):
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"""
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Initialize the test environment,
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including setting random seeds.
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"""
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paddle.seed(2025)
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strategy = fleet.DistributedStrategy()
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strategy.hybrid_configs = {
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"dp_degree": 1,
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"mp_degree": 2,
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"pp_degree": 1,
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"sharding_degree": 1,
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}
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fleet.init(is_collective=True, strategy=strategy)
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def test_case(self):
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"""
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Check if the CustomAllreduce function works properly.
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"""
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mns = [[1, 2048], [2, 4096], [20, 4096], [128, 4096], [256, 4096], [256, 8192]]
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hcg = fleet.get_hybrid_communicate_group()
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model_parallel_group = hcg.get_model_parallel_group()
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fa = CustomAllreduce(model_parallel_group)
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for m, n in mns:
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data_cusom_ar = paddle.rand([m, n], dtype="bfloat16")
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data_paddle = data_cusom_ar.clone()
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if fa.should_custom_ar(data_cusom_ar):
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fa.custom_all_reduce(data_cusom_ar)
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dist.all_reduce(data_paddle)
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if dist.get_rank() == 0:
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np.testing.assert_allclose(
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data_cusom_ar.numpy(),
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data_paddle.numpy(),
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rtol=1e-04,
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atol=1e-04,
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)
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if __name__ == "__main__":
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unittest.main()
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