# Copyright (c) 2021 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 eager_op_test import OpTest

import paddle
from paddle import static
from paddle.fluid import dygraph

paddle.enable_static()


def ref_complex(x, y):
    return x + 1j * y


class TestComplexOp(OpTest):
    def init_spec(self):
        self.x_shape = [10, 10]
        self.y_shape = [10, 10]
        self.dtype = "float64"

    def setUp(self):
        self.op_type = "complex"
        self.python_api = paddle.complex
        self.init_spec()
        x = np.random.randn(*self.x_shape).astype(self.dtype)
        y = np.random.randn(*self.y_shape).astype(self.dtype)
        out_ref = ref_complex(x, y)
        self.inputs = {'X': x, 'Y': y}
        self.outputs = {'Out': out_ref}

    def test_check_output(self):
        self.check_output()

    def test_check_grad(self):
        self.check_grad(
            ['X', 'Y'],
            'Out',
        )

    def test_check_grad_ignore_x(self):
        self.check_grad(
            ['Y'],
            'Out',
            no_grad_set=set('X'),
        )

    def test_check_grad_ignore_y(self):
        self.check_grad(
            ['X'],
            'Out',
            no_grad_set=set('Y'),
        )


class TestComplexOpBroadcast1(TestComplexOp):
    def init_spec(self):
        self.x_shape = [10, 3, 1, 4]
        self.y_shape = [100, 1]
        self.dtype = "float64"


class TestComplexOpBroadcast2(TestComplexOp):
    def init_spec(self):
        self.x_shape = [100, 1]
        self.y_shape = [10, 3, 1, 4]
        self.dtype = "float32"


class TestComplexOpBroadcast3(TestComplexOp):
    def init_spec(self):
        self.x_shape = [1, 100]
        self.y_shape = [100]
        self.dtype = "float32"


class TestComplexAPI(unittest.TestCase):
    def setUp(self):
        self.x = np.random.randn(10, 10)
        self.y = np.random.randn(10, 10)
        self.out = ref_complex(self.x, self.y)

    def test_dygraph(self):
        with dygraph.guard():
            x = paddle.to_tensor(self.x)
            y = paddle.to_tensor(self.y)
            out_np = paddle.complex(x, y).numpy()
        np.testing.assert_allclose(self.out, out_np, rtol=1e-05)

    def test_static(self):
        mp, sp = static.Program(), static.Program()
        with static.program_guard(mp, sp):
            x = static.data("x", shape=[10, 10], dtype="float64")
            y = static.data("y", shape=[10, 10], dtype="float64")
            out = paddle.complex(x, y)

        exe = static.Executor()
        exe.run(sp)
        [out_np] = exe.run(
            mp, feed={"x": self.x, "y": self.y}, fetch_list=[out]
        )
        np.testing.assert_allclose(self.out, out_np, rtol=1e-05)


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