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 TestReciprocal(TestCase):
    def cpu_op_exec(self, input1):
        output = torch.reciprocal(input1)
        output = output.numpy()
        return output

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

    def npu_op_exec_out(self, input1, input2):
        output = input2.to("npu")
        torch.reciprocal(input1, out=output)
        output = output.to("cpu")
        output = output.numpy()
        return output

    def cpu_inp_op_exec(self, input1):
        output = torch.reciprocal_(input1)
        output = output.numpy()
        return output

    def npu_inp_op_exec(self, input1):
        output = torch.reciprocal_(input1)
        output = input1.to("cpu")
        output = output.numpy()
        return output

    def reciprocal_result(self, shape_format):
        for item in shape_format:
            cpu_input1, npu_input1 = create_common_tensor(item, 0, 100)
            if cpu_input1.dtype == torch.float16:
                cpu_input1 = cpu_input1.to(torch.float32)
            cpu_output = self.cpu_op_exec(cpu_input1)
            npu_output = self.npu_op_exec(npu_input1)
            cpu_output_inp = self.cpu_inp_op_exec(cpu_input1)
            npu_output_inp = self.npu_inp_op_exec(npu_input1)
            cpu_output = cpu_output.astype(npu_output.dtype)
            cpu_output_inp = cpu_output_inp.astype(npu_output_inp.dtype)

            self.assertRtolEqual(cpu_output, npu_output)
            self.assertRtolEqual(cpu_output_inp, npu_output_inp)

    def reciprocal_result_out(self, shape_format):
        for item in shape_format:
            cpu_input1, npu_input1 = create_common_tensor(item[0], 0, 100)
            cpu_input2, npu_input2 = create_common_tensor(item[1], 0, 100)
            if cpu_input1.dtype == torch.float16:
                cpu_input1 = cpu_input1.to(torch.float32)
            cpu_output = self.cpu_op_exec(cpu_input1)
            npu_output_out = self.npu_op_exec_out(npu_input1, npu_input2)
            cpu_output = cpu_output.astype(npu_output_out.dtype)

            self.assertRtolEqual(cpu_output, npu_output_out)

    def test_reciprocal_shape_format_fp16_out(self, device='npu'):
        shape_format = [[[np.float16, 0, [18]], [np.float16, 0, [18, 20]]],
                        [[np.float16, 0, [18, 20, 30]], [np.float16, 0, [18, 20, 30]]],
                        [[np.float16, 0, [18, 10, 10, 20]], [np.float16, 0, [18, 10, 20]]],
                        [[np.float16, 3, [18]], [np.float16, 3, [18]]],
                        [[np.float16, 3, [18, 20, 30]], [np.float16, 3, [18, 20, 30]]],
                        [[np.float16, 3, [18, 10, 10, 20]], [np.float16, 3, [18, 10, 20]]],
                        [[np.float16, 4, [18]], [np.float16, 4, [18]]],
                        [[np.float16, 4, [18, 20, 30]], [np.float16, 4, [18, 20, 30]]],
                        [[np.float16, 4, [18, 10, 10, 20]], [np.float16, 4, [18, 10, 20]]],
                        ]
        self.reciprocal_result_out(shape_format)

    def test_reciprocal_shape_format_fp32_out(self, device='npu'):
        shape_format = [[[np.float32, 0, [18]], [np.float32, 0, [18, 20]]],
                        [[np.float32, 0, [18, 20, 30]], [np.float32, 0, [18, 20, 30]]],
                        [[np.float32, 0, [18, 10, 10, 20]], [np.float32, 0, [18, 10, 20]]],
                        [[np.float32, 3, [18]], [np.float32, 3, [18]]],
                        [[np.float32, 3, [18, 20, 30]], [np.float32, 3, [18, 20, 30]]],
                        [[np.float32, 3, [18, 10, 10, 20]], [np.float32, 3, [18, 10, 20]]],
                        [[np.float32, 4, [18]], [np.float32, 4, [18]]],
                        [[np.float32, 4, [18, 20, 30]], [np.float32, 4, [18, 20, 30]]],
                        [[np.float32, 4, [18, 10, 10, 20]], [np.float32, 4, [18, 10, 20]]],
                        ]
        self.reciprocal_result_out(shape_format)

    def test_reciprocal_shape_format_fp16_1d(self, device='npu'):
        format_list = [0, 3, 4]
        shape_format = [[np.float16, i, [18]] for i in format_list
                        ]
        self.reciprocal_result(shape_format)

    def test_reciprocal_shape_format_fp32_1d(self, device='npu'):
        format_list = [0, 3, 4]
        shape_format = [[np.float32, i, [256]] for i in format_list
                        ]
        self.reciprocal_result(shape_format)

    def test_reciprocal_shape_format_fp16_2d(self, device='npu'):
        format_list = [0, 3, 4, 29]
        shape_format = [[np.float16, i, [64, 516]] for i in format_list
                        ]
        self.reciprocal_result(shape_format)

    def test_reciprocal_shape_format_fp32_2d(self, device='npu'):
        format_list = [0, 3, 4, 29]
        shape_format = [[np.float32, i, [64, 516]] for i in format_list
                        ]
        self.reciprocal_result(shape_format)

    def test_reciprocal_shape_format_fp16_3d(self, device='npu'):
        format_list = [0, 3, 4, 29]
        shape_format = [[np.float16, i, [64, 124, 516]] for i in format_list
                        ]
        self.reciprocal_result(shape_format)

    def test_reciprocal_shape_format_fp32_3d(self, device='npu'):
        format_list = [0, 3, 4, 29]
        shape_format = [[np.float32, i, [64, 124, 516]] for i in format_list
                        ]
        self.reciprocal_result(shape_format)

    def test_reciprocal_shape_format_fp16_4d(self, device='npu'):
        format_list = [0, 3, 4, 29]
        shape_format = [[np.float16, i, [64, 128, 516, 32]] for i in format_list
                        ]
        self.reciprocal_result(shape_format)

    def test_reciprocal_shape_format_fp32_4d(self, device='npu'):
        format_list = [0, 3, 4, 29]
        shape_format = [[np.float32, i, [64, 128, 516, 32]] for i in format_list
                        ]
        self.reciprocal_result(shape_format)


if __name__ == "__main__":
    run_tests()