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68 lines
2.5 KiB
68 lines
2.5 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 op_test
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import unittest
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import numpy as np
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import paddle.fluid as fluid
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from paddle.fluid import Program, program_guard
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def create_test_class(op_type, callback, binary_op=True):
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class Cls(op_test.OpTest):
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def setUp(self):
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a = np.random.choice(a=[True, False], size=(10, 7)).astype(bool)
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if binary_op:
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b = np.random.choice(a=[True, False], size=(10, 7)).astype(bool)
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c = callback(a, b)
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else:
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c = callback(a)
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self.outputs = {'Out': c}
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self.op_type = op_type
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if binary_op:
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self.inputs = {'X': a, 'Y': b}
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else:
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self.inputs = {'X': a}
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def test_output(self):
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self.check_output()
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def test_error(self):
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with program_guard(Program(), Program()):
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x = fluid.layers.data(name='x', shape=[2], dtype='bool')
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y = fluid.layers.data(name='y', shape=[2], dtype='bool')
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a = fluid.layers.data(name='a', shape=[2], dtype='int32')
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op = eval("fluid.layers.%s" % self.op_type)
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if self.op_type != "logical_not":
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self.assertRaises(TypeError, op, x=x, y=y, out=1)
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self.assertRaises(TypeError, op, x=x, y=a)
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self.assertRaises(TypeError, op, x=a, y=y)
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else:
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self.assertRaises(TypeError, op, x=x, out=1)
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self.assertRaises(TypeError, op, x=a)
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Cls.__name__ = op_type
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globals()[op_type] = Cls
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create_test_class('logical_and', lambda _a, _b: np.logical_and(_a, _b))
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create_test_class('logical_or', lambda _a, _b: np.logical_or(_a, _b))
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create_test_class('logical_not', lambda _a: np.logical_not(_a), False)
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create_test_class('logical_xor', lambda _a, _b: np.logical_xor(_a, _b))
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if __name__ == '__main__':
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unittest.main()
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