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[AutoParallel] Add paddle.distributed.reshard python API. (PaddlePadd…
…le#57293) * Add paddle.distributed.reshard API. It supports reshard for DistTensor. * Polish code with review comments. * Fix problem of in_dynamic_mode * Fix some problems according to review comments. * Set test_reshard_api as multi-cards testcase. And set its timeout.
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| Original file line number | Diff line number | Diff line change |
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| # Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
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| import os | ||
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| import numpy as np | ||
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| import paddle | ||
| import paddle.distributed as dist | ||
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| class TestReshardAPI: | ||
| def __init__(self): | ||
| self._shape = eval(os.getenv("shape")) | ||
| self._dtype = os.getenv("dtype") | ||
| self._seeds = eval(os.getenv("seeds")) | ||
| self._backend = os.getenv("backend") | ||
| self._shard = eval(os.getenv("shard")) | ||
| self._mesh = dist.ProcessMesh([0, 1], dim_names=["x"]) | ||
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| def run_test_cases(self): | ||
| if self._backend == "cpu": | ||
| paddle.set_device("cpu") | ||
| self.test_case_p_to_r() | ||
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| def test_case_p_to_r(self): | ||
| a = paddle.ones(self._shape) | ||
| in_shard_specs = [None for i in range(len(self._shape))] | ||
| out_shard_specs = [None for i in range(len(self._shape))] | ||
| dist_attr = dist.DistAttr( | ||
| mesh=self._mesh, sharding_specs=in_shard_specs | ||
| ) | ||
| dist_attr._set_partial_dims([0]) | ||
| out_dist_attr = dist.DistAttr( | ||
| mesh=self._mesh, sharding_specs=out_shard_specs | ||
| ) | ||
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| input_tensor = dist.shard_tensor(a, dist_attr=dist_attr) | ||
| output_tensor = dist.reshard(input_tensor, dist_attr=out_dist_attr) | ||
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| input_tensor = dist.shard_tensor(a, dist_attr=dist_attr) | ||
| assert np.equal(output_tensor.shape, input_tensor.shape).all() | ||
| np.testing.assert_equal(output_tensor._local_value().numpy(), a.numpy()) | ||
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| def test_case_r_to_s(self): | ||
| a = paddle.ones(self._shape) | ||
| in_shard_specs = [None for i in range(len(self._shape))] | ||
| out_shard_specs = [None for i in range(len(self._shape))] | ||
| out_shard_specs[self._shard] = "x" | ||
| dist_attr = dist.DistAttr( | ||
| mesh=self._mesh, sharding_specs=in_shard_specs | ||
| ) | ||
| out_dist_attr = dist.DistAttr( | ||
| mesh=self._mesh, sharding_specs=out_shard_specs | ||
| ) | ||
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| input_tensor = dist.shard_tensor(a, dist_attr=dist_attr) | ||
| output_tensor = dist.reshard(input_tensor, dist_attr=out_dist_attr) | ||
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| out_shape = list(self._shape) | ||
| if out_shape[self._shard] % 2 == 0: | ||
| out_shape[self._shard] = out_shape[self._shard] // 2 | ||
| np.testing.assert_equal(output_tensor.numpy(), input_tensor.numpy()) | ||
| else: | ||
| out_shape[self._shard] = ( | ||
| out_shape[self._shard] // 2 | ||
| if dist.get_rank() == 1 | ||
| else out_shape[self._shard] // 2 + 1 | ||
| ) | ||
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| assert np.equal(output_tensor.shape, input_tensor.shape).all() | ||
| assert np.equal(output_tensor._local_shape, out_shape).all() | ||
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| if __name__ == '__main__': | ||
| TestReshardAPI().run_test_cases() |
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|---|---|---|
| @@ -0,0 +1,45 @@ | ||
| # Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
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| import unittest | ||
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| import collective.test_communication_api_base as test_base | ||
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| class TestReshardAPI(test_base.CommunicationTestDistBase): | ||
| def setUp(self): | ||
| super().setUp(num_of_devices=2, timeout=120) | ||
| self._default_envs = { | ||
| "shape": "(10, 20)", | ||
| "dtype": "float32", | ||
| "seeds": str(self._seeds), | ||
| "shard": "0", | ||
| } | ||
| self._changeable_envs = { | ||
| "backend": ["cpu", "gpu"], | ||
| } | ||
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| def test_reshard_api(self): | ||
| envs_list = test_base.gen_product_envs_list( | ||
| self._default_envs, self._changeable_envs | ||
| ) | ||
| for envs in envs_list: | ||
| self.run_test_case( | ||
| "reshard_api.py", | ||
| user_defined_envs=envs, | ||
| ) | ||
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| if __name__ == "__main__": | ||
| unittest.main() |