# 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 TestTransposeOp(OpTest): def setUp(self): self.init_op_type() self.initTestCase() self.inputs = {'X': np.random.random(self.shape).astype("float32")} self.attrs = { 'axis': list(self.axis), 'use_mkldnn': self.use_mkldnn, } self.outputs = { 'XShape': np.random.random(self.shape).astype("float32"), 'Out': self.inputs['X'].transpose(self.axis) } def init_op_type(self): self.op_type = "transpose2" self.use_mkldnn = False def test_check_output(self): self.check_output(no_check_set=['XShape']) def test_check_grad(self): self.check_grad(['X'], 'Out') def initTestCase(self): self.shape = (3, 4) self.axis = (1, 0) class TestCase0(TestTransposeOp): def initTestCase(self): self.shape = (3, ) self.axis = (0, ) class TestCase1(TestTransposeOp): def initTestCase(self): self.shape = (3, 4, 5) self.axis = (0, 2, 1) class TestCase2(TestTransposeOp): def initTestCase(self): self.shape = (2, 3, 4, 5) self.axis = (0, 2, 3, 1) class TestCase3(TestTransposeOp): def initTestCase(self): self.shape = (2, 3, 4, 5, 6) self.axis = (4, 2, 3, 1, 0) class TestCase4(TestTransposeOp): def initTestCase(self): self.shape = (2, 3, 4, 5, 6, 1) self.axis = (4, 2, 3, 1, 0, 5) class TestTransposeOpError(OpTest): def test_errors(self): with program_guard(Program(), Program()): x = fluid.layers.data(name='x', shape=[10, 5, 3], dtype='float32') def test_x_Variable_check(): # the Input(x)'s type must be Variable fluid.layers.transpose("not_variable", perm=[1, 0, 2]) self.assertRaises(TypeError, test_x_Variable_check) def test_x_dtype_check(): # the Input(x)'s dtype must be one of [float16, float32, float64, int32, int64] x1 = fluid.layers.data( name='x1', shape=[10, 5, 3], dtype='bool') fluid.layers.transpose(x1, perm=[1, 0, 2]) self.assertRaises(TypeError, test_x_dtype_check) def test_perm_list_check(): # Input(perm)'s type must be list fluid.layers.transpose(x, perm="[1, 0, 2]") self.assertRaises(TypeError, test_perm_list_check) def test_perm_length_and_x_dim_check(): # Input(perm) is the permutation of dimensions of Input(input) # its length should be equal to dimensions of Input(input) fluid.layers.transpose(x, perm=[1, 0, 2, 3, 4]) self.assertRaises(ValueError, test_perm_length_and_x_dim_check) def test_each_elem_value_check(): # Each element in Input(perm) should be less than Input(x)'s dimension fluid.layers.transpose(x, perm=[3, 5, 7]) self.assertRaises(ValueError, test_each_elem_value_check) if __name__ == '__main__': unittest.main()