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66 lines
2.3 KiB
66 lines
2.3 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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from __future__ import print_function
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import unittest
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import paddle.fluid as fluid
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import paddle.fluid.layers as layers
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class TestProgramToReadableCode(unittest.TestCase):
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def setUp(self):
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self.program = fluid.Program()
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self.block = self.program.current_block()
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self.var = self.block.create_var(
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name="X", shape=[-1, 23, 48], dtype='float32')
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self.param = self.block.create_parameter(
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name="W", shape=[23, 48], dtype='float32', trainable=True)
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self.op = self.block.append_op(
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type="abs", inputs={"X": [self.var]}, outputs={"Out": [self.var]})
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# add control flow op and sub block
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self.append_cond_op(self.program)
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def append_cond_op(self, program):
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def true_func():
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return layers.fill_constant(shape=[2, 3], dtype='int32', value=2)
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def false_func():
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return layers.fill_constant(shape=[3, 2], dtype='int32', value=-1)
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with fluid.program_guard(program):
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x = layers.fill_constant(shape=[1], dtype='float32', value=0.1)
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y = layers.fill_constant(shape=[1], dtype='float32', value=0.23)
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pred = layers.less_than(y, x)
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out = layers.cond(pred, true_func, false_func)
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def test_program_code(self):
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self.var._to_readable_code()
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self.param._to_readable_code()
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self.op._to_readable_code()
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self.block._to_readable_code()
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self.program._to_readable_code()
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def test_program_print(self):
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print(self.var)
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print(self.param)
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print(self.op)
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print(self.block)
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print(self.program)
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if __name__ == "__main__":
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unittest.main()
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