wehub-resource-sync
63 lines
2.0 KiB
Python
63 lines
2.0 KiB
Python
# 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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import unittest
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import numpy as np
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import paddle
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from paddle.distributed import fleet
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from paddle.distributed.fleet.base import topology as tp
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from paddle.distributed.fleet.layers.mpu import mp_ops
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class CommGroupNumTest(unittest.TestCase):
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def test_comm_group_num(self):
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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": 2,
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"sharding_degree": 2,
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"order": ["dp", "pp", "sharding", "sep", "mp"],
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}
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fleet.init(is_collective=True, strategy=strategy)
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place = paddle.framework._current_expected_place()
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input = np.random.uniform(
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low=-2.0, high=2.0, size=(1, 4096, 16000)
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).astype('float32')
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input = paddle.to_tensor(input, place=place)
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input.stop_gradient = False
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label = np.random.randint(
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low=1, high=29956, size=(1, 4096, 1), dtype='int64'
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)
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label = paddle.to_tensor(label, place=place)
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label.stop_gradient = True
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model_parallel_group = (
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tp._HYBRID_PARALLEL_GROUP.get_model_parallel_group()
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)
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loss = mp_ops._c_softmax_with_cross_entropy(
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input,
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label,
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group=model_parallel_group,
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ignore_index=-100,
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)
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if __name__ == '__main__':
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unittest.main()
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