# 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 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("float64")} self.attrs = { 'axis': list(self.axis), 'use_mkldnn': self.use_mkldnn, } self.outputs = { 'XShape': np.random.random(self.shape).astype("float64"), '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, 40) self.axis = (1, 0) class TestCase0(TestTransposeOp): def initTestCase(self): self.shape = (100, ) self.axis = (0, ) class TestCase1(TestTransposeOp): def initTestCase(self): self.shape = (3, 4, 10) 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 TestCase5(TestTransposeOp): def initTestCase(self): self.shape = (2, 16, 96) self.axis = (0, 2, 1) class TestCase6(TestTransposeOp): def initTestCase(self): self.shape = (2, 10, 12, 16) self.axis = (3, 1, 2, 0) class TestCase7(TestTransposeOp): def initTestCase(self): self.shape = (2, 10, 2, 16) self.axis = (0, 1, 3, 2) class TestCase8(TestTransposeOp): def initTestCase(self): self.shape = (2, 3, 2, 3, 2, 4, 3, 3) self.axis = (0, 1, 3, 2, 4, 5, 6, 7) class TestCase9(TestTransposeOp): def initTestCase(self): self.shape = (2, 3, 2, 3, 2, 4, 3, 3) self.axis = (6, 1, 3, 5, 0, 2, 4, 7) class TestTransposeOpError(unittest.TestCase): def test_errors(self): with program_guard(Program(), Program()): x = fluid.layers.data(name='x', shape=[10, 5, 3], dtype='float64') 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) class TestTAPI(unittest.TestCase): def test_out(self): with fluid.program_guard(fluid.Program()): data = fluid.data(shape=[10], dtype="float64", name="data") data_t = paddle.t(data) place = fluid.CPUPlace() exe = fluid.Executor(place) data_np = np.random.random([10]).astype("float64") result, = exe.run(feed={"data": data_np}, fetch_list=[data_t]) expected_result = np.transpose(data_np) self.assertEqual((result == expected_result).all(), True) with fluid.program_guard(fluid.Program()): data = fluid.data(shape=[10, 5], dtype="float64", name="data") data_t = paddle.t(data) place = fluid.CPUPlace() exe = fluid.Executor(place) data_np = np.random.random([10, 5]).astype("float64") result, = exe.run(feed={"data": data_np}, fetch_list=[data_t]) expected_result = np.transpose(data_np) self.assertEqual((result == expected_result).all(), True) with fluid.program_guard(fluid.Program()): data = fluid.data(shape=[1, 5], dtype="float64", name="data") data_t = paddle.t(data) place = fluid.CPUPlace() exe = fluid.Executor(place) data_np = np.random.random([1, 5]).astype("float64") result, = exe.run(feed={"data": data_np}, fetch_list=[data_t]) expected_result = np.transpose(data_np) self.assertEqual((result == expected_result).all(), True) with fluid.dygraph.guard(): np_x = np.random.random([10]).astype("float64") data = fluid.dygraph.to_variable(np_x) z = paddle.t(data) np_z = z.numpy() z_expected = np.array(np.transpose(np_x)) self.assertEqual((np_z == z_expected).all(), True) with fluid.dygraph.guard(): np_x = np.random.random([10, 5]).astype("float64") data = fluid.dygraph.to_variable(np_x) z = paddle.t(data) np_z = z.numpy() z_expected = np.array(np.transpose(np_x)) self.assertEqual((np_z == z_expected).all(), True) with fluid.dygraph.guard(): np_x = np.random.random([1, 5]).astype("float64") data = fluid.dygraph.to_variable(np_x) z = paddle.t(data) np_z = z.numpy() z_expected = np.array(np.transpose(np_x)) self.assertEqual((np_z == z_expected).all(), True) def test_errors(self): with fluid.program_guard(fluid.Program()): x = fluid.data(name='x', shape=[10, 5, 3], dtype='float64') def test_x_dimension_check(): paddle.t(x) self.assertRaises(ValueError, test_x_dimension_check) if __name__ == '__main__': unittest.main()