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259 lines
9.8 KiB
259 lines
9.8 KiB
# Copyright (c) 2018 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 paddle.fluid as fluid
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import paddle.fluid.core as core
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from paddle.fluid import framework, unique_name, layer_helper
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from paddle.fluid.executor import Executor
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from paddle.fluid.layers import fill_constant, assign, While, elementwise_add, Print
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class TestRoutineOp(unittest.TestCase):
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def test_simple_routine(self):
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ch = fluid.make_channel(dtype=core.VarDesc.VarType.LOD_TENSOR)
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# Create LOD_TENSOR<INT64> and put it into the scope. This placeholder
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# variable will be filled in and returned by fluid.channel_recv
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result = self._create_tensor('return_value',
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core.VarDesc.VarType.LOD_TENSOR,
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core.VarDesc.VarType.INT64)
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with fluid.Go():
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input_value = fill_constant(
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shape=[1], dtype=core.VarDesc.VarType.FP64, value=1234)
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fluid.channel_send(ch, input_value)
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result, status = fluid.channel_recv(ch, result)
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fluid.channel_close(ch)
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cpu = core.CPUPlace()
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exe = Executor(cpu)
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outs = exe.run(fetch_list=[result])
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self.assertEqual(outs[0], 1234)
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def test_daisy_chain(self):
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'''
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Mimics classic Daisy-chain test: https://talks.golang.org/2012/concurrency.slide#39
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'''
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n = 100
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leftmost = fluid.make_channel(dtype=core.VarDesc.VarType.LOD_TENSOR)
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left = leftmost
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# TODO(thuan): Use fluid.While() after scope capture is implemented.
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# https://github.com/PaddlePaddle/Paddle/issues/8502
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for i in range(n):
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right = fluid.make_channel(dtype=core.VarDesc.VarType.LOD_TENSOR)
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with fluid.Go():
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one_tensor = self._create_one_dim_tensor(1)
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result = self._create_tensor('return_value',
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core.VarDesc.VarType.LOD_TENSOR,
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core.VarDesc.VarType.INT64)
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result, status = fluid.channel_recv(right, result)
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one_added = fluid.layers.elementwise_add(x=one_tensor, y=result)
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fluid.channel_send(left, one_added)
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left = right
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# Trigger the channel propagation by sending a "1" to rightmost channel
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with fluid.Go():
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one_tensor = self._create_one_dim_tensor(1)
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fluid.channel_send(right, one_tensor)
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leftmost_result = self._create_tensor('return_value',
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core.VarDesc.VarType.LOD_TENSOR,
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core.VarDesc.VarType.INT64)
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leftmost_result, status = fluid.channel_recv(leftmost, leftmost_result)
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cpu = core.CPUPlace()
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exe = Executor(cpu)
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leftmost_data = exe.run(fetch_list=[leftmost_result])
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# The leftmost_data should be equal to the number of channels + 1
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self.assertEqual(leftmost_data[0][0], n + 1)
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def _create_one_dim_tensor(self, value):
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one_dim_tensor = fill_constant(shape=[1], dtype='int', value=value)
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one_dim_tensor.stop_gradient = True
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return one_dim_tensor
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def _create_tensor(self, name, type, dtype):
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return framework.default_main_program().current_block().create_var(
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name=unique_name.generate(name), type=type, dtype=dtype)
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def _create_persistable_tensor(self, name, type, dtype):
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return framework.default_main_program().current_block().create_var(
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name=unique_name.generate(name),
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type=type,
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dtype=dtype,
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persistable=True)
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def test_select(self):
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with framework.program_guard(framework.Program()):
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ch1 = fluid.make_channel(
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dtype=core.VarDesc.VarType.LOD_TENSOR, capacity=1)
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result1 = self._create_tensor('return_value',
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core.VarDesc.VarType.LOD_TENSOR,
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core.VarDesc.VarType.FP64)
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input_value = fill_constant(
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shape=[1], dtype=core.VarDesc.VarType.FP64, value=10)
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with fluid.Select() as select:
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with select.case(fluid.channel_send, ch1, input_value):
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# Execute something.
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pass
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with select.default():
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pass
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# This should not block because we are using a buffered channel.
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result1, status = fluid.channel_recv(ch1, result1)
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fluid.channel_close(ch1)
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cpu = core.CPUPlace()
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exe = Executor(cpu)
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result = exe.run(fetch_list=[result1])
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self.assertEqual(result[0][0], 10)
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def test_fibonacci(self):
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"""
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Mimics Fibonacci Go example: https://tour.golang.org/concurrency/5
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"""
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with framework.program_guard(framework.Program()):
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quit_ch_input_var = self._create_persistable_tensor(
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'quit_ch_input', core.VarDesc.VarType.LOD_TENSOR,
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core.VarDesc.VarType.INT32)
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quit_ch_input = fill_constant(
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shape=[1],
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dtype=core.VarDesc.VarType.INT32,
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value=0,
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out=quit_ch_input_var)
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result = self._create_persistable_tensor(
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'result', core.VarDesc.VarType.LOD_TENSOR,
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core.VarDesc.VarType.INT32)
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fill_constant(
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shape=[1],
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dtype=core.VarDesc.VarType.INT32,
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value=0,
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out=result)
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x = fill_constant(
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shape=[1], dtype=core.VarDesc.VarType.INT32, value=0)
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y = fill_constant(
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shape=[1], dtype=core.VarDesc.VarType.INT32, value=1)
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while_cond = fill_constant(
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shape=[1], dtype=core.VarDesc.VarType.BOOL, value=True)
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while_false = fill_constant(
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shape=[1], dtype=core.VarDesc.VarType.BOOL, value=False)
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x_tmp = fill_constant(
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shape=[1], dtype=core.VarDesc.VarType.INT32, value=0)
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def fibonacci(channel, quit_channel):
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while_op = While(cond=while_cond)
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with while_op.block():
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result2 = fill_constant(
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shape=[1], dtype=core.VarDesc.VarType.INT32, value=0)
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with fluid.Select() as select:
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with select.case(
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fluid.channel_send, channel, x, is_copy=True):
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assign(input=x, output=x_tmp)
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assign(input=y, output=x)
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assign(elementwise_add(x=x_tmp, y=y), output=y)
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with select.case(fluid.channel_recv, quit_channel,
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result2):
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# Quit
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helper = layer_helper.LayerHelper('assign')
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helper.append_op(
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type='assign',
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inputs={'X': [while_false]},
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outputs={'Out': [while_cond]})
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ch1 = fluid.make_channel(dtype=core.VarDesc.VarType.LOD_TENSOR)
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quit_ch = fluid.make_channel(dtype=core.VarDesc.VarType.LOD_TENSOR)
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with fluid.Go():
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for i in range(10):
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fluid.channel_recv(ch1, result)
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Print(result)
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fluid.channel_send(quit_ch, quit_ch_input)
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fibonacci(ch1, quit_ch)
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fluid.channel_close(ch1)
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fluid.channel_close(quit_ch)
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cpu = core.CPUPlace()
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exe = Executor(cpu)
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exe_result = exe.run(fetch_list=[result])
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self.assertEqual(exe_result[0][0], 34)
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def test_ping_pong(self):
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"""
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Mimics Ping Pong example: https://gobyexample.com/channel-directions
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"""
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with framework.program_guard(framework.Program()):
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result = self._create_tensor('return_value',
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core.VarDesc.VarType.LOD_TENSOR,
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core.VarDesc.VarType.FP64)
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ping_result = self._create_tensor('ping_return_value',
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core.VarDesc.VarType.LOD_TENSOR,
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core.VarDesc.VarType.FP64)
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def ping(ch, message):
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fluid.channel_send(ch, message, is_copy=True)
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def pong(ch1, ch2):
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fluid.channel_recv(ch1, ping_result)
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fluid.channel_send(ch2, ping_result, is_copy=True)
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pings = fluid.make_channel(
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dtype=core.VarDesc.VarType.LOD_TENSOR, capacity=1)
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pongs = fluid.make_channel(
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dtype=core.VarDesc.VarType.LOD_TENSOR, capacity=1)
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msg = fill_constant(
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shape=[1], dtype=core.VarDesc.VarType.FP64, value=9)
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ping(pings, msg)
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pong(pings, pongs)
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fluid.channel_recv(pongs, result)
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fluid.channel_close(pings)
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fluid.channel_close(pongs)
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cpu = core.CPUPlace()
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exe = Executor(cpu)
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exe_result = exe.run(fetch_list=[result])
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self.assertEqual(exe_result[0][0], 9)
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if __name__ == '__main__':
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unittest.main()
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