#   Copyright (c) 2023 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
from op_test import get_device_place

import paddle
from paddle import base

paddle.enable_static()


class TestHypotAPI(unittest.TestCase):
    def setUp(self):
        self.x_shape = [10, 10]
        self.y_shape = [10, 1]
        self.x_np = np.random.uniform(-10, 10, self.x_shape).astype(np.float32)
        self.y_np = np.random.uniform(-10, 10, self.y_shape).astype(np.float32)

    def test_static_graph(self):
        paddle.enable_static()
        startup_program = base.Program()
        train_program = base.Program()
        with base.program_guard(startup_program, train_program):
            x = paddle.static.data(
                name='input1', dtype='float32', shape=self.x_shape
            )
            y = paddle.static.data(
                name='input2', dtype='float32', shape=self.y_shape
            )
            out = paddle.hypot(x, y)

            place = get_device_place()
            exe = base.Executor(place)
            res = exe.run(
                base.default_main_program(),
                feed={'input1': self.x_np, 'input2': self.y_np},
                fetch_list=[out],
            )
            np_out = np.hypot(self.x_np, self.y_np)
            np.testing.assert_allclose(res[0], np_out, atol=1e-5, rtol=1e-5)
            paddle.disable_static()

    def test_dygraph(self):
        paddle.disable_static()
        x = paddle.to_tensor(self.x_np)
        y = paddle.to_tensor(self.y_np)
        result = paddle.hypot(x, y)
        np.testing.assert_allclose(
            np.hypot(self.x_np, self.y_np), result.numpy(), rtol=1e-05
        )

        paddle.enable_static()

    def test_error(self):
        x = paddle.to_tensor(self.x_np)
        y = 3.8
        self.assertRaises(TypeError, paddle.hypot, x, y)
        self.assertRaises(TypeError, paddle.hypot, y, x)


class TestHypotAPIBroadCast(TestHypotAPI):
    def setUp(self):
        self.x_np = np.arange(6).astype(np.float32)
        self.y_np = np.array([20]).astype(np.float32)
        self.x_shape = [6]
        self.y_shape = [1]


class TestHypotAPI3(TestHypotAPI):
    def setUp(self):
        self.x_shape = []
        self.y_shape = []
        self.x_np = np.random.uniform(-10, 10, self.x_shape).astype(np.float32)
        self.y_np = np.random.uniform(-10, 10, self.y_shape).astype(np.float32)


class TestHypotAPI4(TestHypotAPI):
    def setUp(self):
        self.x_shape = [1]
        self.y_shape = [1]
        self.x_np = np.random.uniform(-10, 10, self.x_shape).astype(np.float32)
        self.y_np = np.random.uniform(-10, 10, self.y_shape).astype(np.float32)


if __name__ == "__main__":
    unittest.main()