# 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. from __future__ import print_function import unittest import numpy as np from op_test import OpTest import paddle.fluid as fluid from paddle.fluid import Program, program_guard class TestSignOp(OpTest): def setUp(self): self.op_type = "sign" self.inputs = { 'X': np.random.uniform(-10, 10, (10, 10)).astype("float64") } self.outputs = {'Out': np.sign(self.inputs['X'])} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(['X'], 'Out') class TestSignOpError(unittest.TestCase): def test_errors(self): with program_guard(Program(), Program()): # The input type of sign_op must be Variable or numpy.ndarray. input1 = 12 self.assertRaises(TypeError, fluid.layers.sign, input1) # The input dtype of sign_op must be float16, float32, float64. input2 = fluid.layers.data( name='input2', shape=[12, 10], dtype="int32") input3 = fluid.layers.data( name='input3', shape=[12, 10], dtype="int64") self.assertRaises(TypeError, fluid.layers.sign, input2) self.assertRaises(TypeError, fluid.layers.sign, input3) input4 = fluid.layers.data( name='input4', shape=[4], dtype="float16") fluid.layers.sign(input4) if __name__ == "__main__": unittest.main()