# 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 = paddle.static.data(name='x', shape=[-1, 2], dtype='float32')
            x.desc.set_need_check_feed(False)
            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 = paddle.static.data(name='x', shape=[-1], dtype='float32')
            x.desc.set_need_check_feed(False)
            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 = paddle.static.data(name='x', shape=[-1, 2], dtype='float32')
            x.desc.set_need_check_feed(False)
            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 = paddle.static.data(name='x', shape=[-1], dtype='float32')
            x.desc.set_need_check_feed(False)
            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()
