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support lodtensorarray for send/recv (#35279)
* support lodtensorarray
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lilong12
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Sep 3, 2021
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95 changes: 95 additions & 0 deletions
95
python/paddle/fluid/tests/unittests/collective_sendrecv_op_array.py
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,95 @@ | ||
| # Copyright (c) 2018 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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| from __future__ import print_function | ||
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| import numpy as np | ||
| import argparse | ||
| import os | ||
| import sys | ||
| import signal | ||
| import time | ||
| import socket | ||
| from contextlib import closing | ||
| from six import string_types | ||
| import math | ||
| import paddle | ||
| import paddle.fluid as fluid | ||
| import paddle.fluid.profiler as profiler | ||
| import paddle.fluid.unique_name as nameGen | ||
| from paddle.fluid import core | ||
| import unittest | ||
| from multiprocessing import Process | ||
| import paddle.fluid.layers as layers | ||
| from functools import reduce | ||
| from test_collective_base import TestCollectiveRunnerBase, runtime_main | ||
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| paddle.enable_static() | ||
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| class TestCollectiveSendRecv(TestCollectiveRunnerBase): | ||
| def __init__(self): | ||
| self.global_ring_id = 0 | ||
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| def get_model(self, main_prog, startup_program): | ||
| ring_id = self.global_ring_id | ||
| with fluid.program_guard(main_prog, startup_program): | ||
| tindata = layers.data( | ||
| name="tindata", | ||
| shape=[10, 1000], | ||
| dtype='float64', | ||
| append_batch_size=False) | ||
| if self.rank == 0: | ||
| data1 = fluid.layers.assign( | ||
| np.array( | ||
| [[0, 1, 2]], dtype='float32')) | ||
| data2 = fluid.layers.assign( | ||
| np.array( | ||
| [[3, 4, 5]], dtype='float32')) | ||
| elif self.rank == 1: | ||
| data1 = fluid.layers.assign( | ||
| np.array( | ||
| [[3, 4, 5]], dtype='float32')) | ||
| data2 = fluid.layers.assign( | ||
| np.array( | ||
| [[0, 1, 2]], dtype='float32')) | ||
| tensor_array = fluid.layers.create_array(dtype='float32') | ||
| i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0) | ||
| fluid.layers.array_write(data1, i, tensor_array) | ||
| fluid.layers.array_write(data2, i + 1, tensor_array) | ||
| if self.rank == 0: | ||
| main_prog.global_block().append_op( | ||
| type="send_v2", | ||
| inputs={'X': tensor_array}, | ||
| attrs={ | ||
| 'ring_id': ring_id, | ||
| 'peer': 1, | ||
| 'use_calc_stream': True | ||
| }) | ||
| else: | ||
| main_prog.global_block().append_op( | ||
| type="recv_v2", | ||
| outputs={'Out': tensor_array}, | ||
| attrs={ | ||
| 'peer': 0, | ||
| 'ring_id': ring_id, | ||
| 'dtype': data1.dtype, | ||
| 'out_shape': [1, 3], | ||
| 'use_calc_stream': True, | ||
| }) | ||
| return tensor_array | ||
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| if __name__ == "__main__": | ||
| runtime_main(TestCollectiveSendRecv, "sendrecv_array", 0) |
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