# Copyright (c) 2020 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. import unittest import numpy as np import paddle import paddle.fluid as fluid from paddle.fluid import Program, program_guard class TestNonZeroAPI(unittest.TestCase): def test_nonzero_api_as_tuple(self): data = np.array([[True, False], [False, True]]) with program_guard(Program(), Program()): x = fluid.layers.data(name='x', shape=[-1, 2]) y = paddle.nonzero(x, as_tuple=True) self.assertEqual(type(y), tuple) self.assertEqual(len(y), 2) z = fluid.layers.concat(list(y), axis=1) exe = fluid.Executor(fluid.CPUPlace()) (res,) = exe.run( feed={'x': data}, fetch_list=[z.name], return_numpy=False ) expect_out = np.array([[0, 0], [1, 1]]) np.testing.assert_allclose(expect_out, np.array(res), rtol=1e-05) data = np.array([True, True, False]) with program_guard(Program(), Program()): x = fluid.layers.data(name='x', shape=[-1]) y = paddle.nonzero(x, as_tuple=True) self.assertEqual(type(y), tuple) self.assertEqual(len(y), 1) z = fluid.layers.concat(list(y), axis=1) exe = fluid.Executor(fluid.CPUPlace()) (res,) = exe.run( feed={'x': data}, fetch_list=[z.name], return_numpy=False ) expect_out = np.array([[0], [1]]) np.testing.assert_allclose(expect_out, np.array(res), rtol=1e-05) def test_nonzero_api(self): data = np.array([[True, False], [False, True]]) with program_guard(Program(), Program()): x = fluid.layers.data(name='x', shape=[-1, 2]) y = paddle.nonzero(x) exe = fluid.Executor(fluid.CPUPlace()) (res,) = exe.run( feed={'x': data}, fetch_list=[y.name], return_numpy=False ) expect_out = np.array([[0, 0], [1, 1]]) np.testing.assert_allclose(expect_out, np.array(res), rtol=1e-05) data = np.array([True, True, False]) with program_guard(Program(), Program()): x = fluid.layers.data(name='x', shape=[-1]) y = paddle.nonzero(x) exe = fluid.Executor(fluid.CPUPlace()) (res,) = exe.run( feed={'x': data}, fetch_list=[y.name], return_numpy=False ) expect_out = np.array([[0], [1]]) np.testing.assert_allclose(expect_out, np.array(res), rtol=1e-05) def test_dygraph_api(self): data_x = np.array([[True, False], [False, True]]) with fluid.dygraph.guard(): x = fluid.dygraph.to_variable(data_x) z = paddle.nonzero(x) np_z = z.numpy() expect_out = np.array([[0, 0], [1, 1]]) if __name__ == "__main__": unittest.main()