wehub-resource-sync
75 lines
2.7 KiB
Python
75 lines
2.7 KiB
Python
# Copyright (c) 2021 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 os
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import unittest
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from legacy_test.test_parallel_dygraph_dataparallel import (
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TestMultipleAccelerators,
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)
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class TestHybridParallel(TestMultipleAccelerators):
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# check sharding logic as well as the accuracy with single mode
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def test_hybrid_parallel_sharding_logic(self):
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# test shard v2
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os.environ["FLAGS_shard_split_param"] = "1"
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self.run_mnist_2accelerators('hybrid_parallel_sharding_model.py')
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# test shard grad reduce
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os.environ["FLAGS_shard_split_param"] = "0"
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self.run_mnist_2accelerators('hybrid_parallel_sharding_model.py')
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def test_hybrid_parallel_sharding_tensor_fusion(self):
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os.environ["FLAGS_shard_split_param"] = "0"
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self.run_mnist_2accelerators(
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'hybrid_parallel_sharding_model_with_fusion.py'
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)
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def test_hybrid_parallel_sharding_tensor_fusion_amp(self):
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os.environ["FLAGS_shard_split_param"] = "0"
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self.run_mnist_2accelerators(
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'hybrid_parallel_sharding_model_with_fusion_amp.py'
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)
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def test_hybrid_parallel_sharding_state_dict(self):
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os.environ["FLAGS_shard_split_param"] = "0"
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self.run_mnist_2accelerators('hybrid_parallel_sharding_state_dict.py')
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def test_group_param_tensor_fusion(self):
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self.run_mnist_2accelerators(
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'hybrid_parallel_tensor_fusion_with_group.py'
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)
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def test_group_shard_with_color(self):
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# test shard v2
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os.environ["FLAGS_shard_split_param"] = "1"
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os.environ["FLAGS_shard_param_with_color"] = "1"
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self.run_mnist_2accelerators('hybrid_parallel_sharding_model.py')
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# reset
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os.environ["FLAGS_shard_param_with_color"] = "0"
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def test_hybrid_parallel_sharding_with_fuse_optimizer_states(self):
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# test shard v2
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os.environ["FLAGS_shard_split_param"] = "1"
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self.run_mnist_2accelerators(
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'hybrid_parallel_sharding_model_with_fuse_optimizer_states_enabled.py'
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)
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# reset
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os.environ["FLAGS_shard_split_param"] = "0"
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if __name__ == "__main__":
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unittest.main()
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