# Copyright (c) 2023, Huawei Technologies.All rights reserved.
#
# Licensed under the BSD 3-Clause License  (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://opensource.org/licenses/BSD-3-Clause
#
# 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 torch
import numpy as np
import torch_npu

from torch_npu.testing.testcase import TestCase, run_tests
from torch_npu.testing.common_utils import create_common_tensor


class TestComplex(TestCase):
    def cpu_op_exec(self, input1, input2):
        output = torch.complex(input1, input2)
        output = output.numpy()
        return output

    def npu_op_exec(self, input1, input2):
        output = torch.complex(input1, input2)
        output = output.to("cpu")
        output = output.numpy()
        return output

    def test_real_shape_format_complex(self, device="npu"):
        format_list = [0]
        shape_list = [[5], [5, 10], [1, 3, 2], [52, 15, 15, 20]]
        dtype_list = [np.float32, np.float64]
        # pylint:disable=complicate-comprehension
        shape_format = [
            [i, j, k]
            for i in dtype_list
            for j in format_list
            for k in shape_list
        ]
        for item in shape_format:
            cpu_input1, npu_input1 = create_common_tensor(item, -10, 10)
            cpu_input2, npu_input2 = create_common_tensor(item, -10, 10)
            cpu_output = self.cpu_op_exec(cpu_input1, cpu_input2)
            npu_output = self.npu_op_exec(npu_input1, npu_input2)
            self.assertRtolEqual(torch.real(torch.from_numpy(cpu_output)), torch.real(torch.from_numpy(npu_output)))
            self.assertRtolEqual(torch.imag(torch.from_numpy(cpu_output)), torch.imag(torch.from_numpy(npu_output)))


if __name__ == "__main__":
    run_tests()