# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve. # # 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. import unittest import numpy as np from op_test import OpTest class TestMultiplexOp(OpTest): def setUp(self): self.op_type = "multiplex" rows = 4 index = np.arange(0, rows).astype('int32') np.random.shuffle(index) index = np.reshape(index, (rows, 1)) ins1 = np.random.random((rows, 10)).astype("float32") ins2 = np.random.random((rows, 10)).astype("float32") ins3 = np.random.random((rows, 10)).astype("float32") ins4 = np.random.random((rows, 10)).astype("float32") self.inputs = { 'Ids': index, 'X': [('x1', ins1), ('x2', ins2), ('x3', ins3), ('x4', ins4)] } # multiplex output output = np.zeros_like(ins1) for i in range(0, rows): k = index[i][0] output[i] = self.inputs['X'][k][1][i] self.outputs = {'Out': output} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(['x1', 'x2', 'x3', 'x4'], 'Out') def test_check_grad_ignore_x1(self): self.check_grad(['x2', 'x3', 'x4'], 'Out', no_grad_set=set('x1')) def test_check_grad_ignore_x1_x2(self): self.check_grad(['x3', 'x4'], 'Out', no_grad_set=set(['x1', 'x2'])) def test_check_grad_ignore_x3(self): self.check_grad(['x1', 'x2', 'x4'], 'Out', no_grad_set=set('x3')) if __name__ == '__main__': unittest.main()