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 TestFlip(TestCase):
    def cpu_op_exec(self, input1, dims):
        output = torch.flip(input1, dims)
        output = output.numpy()
        return output

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

    def test_flip_shape_format(self):
        shape_format = [
            [[np.float32, 0, [2, 2, 2]], [0]],
            [[np.float32, 0, [2, 2, 2, 4]], [-2]],
            [[np.int32, 0, [2, 2, 2]], [0, 1]],
            [[np.int32, 0, [2, 2, 2, 4]], [-1, 1]],
        ]
        for item in shape_format:
            cpu_input1, npu_input1 = create_common_tensor(item[0], 1, 100)
            cpu_output = self.cpu_op_exec(cpu_input1, item[1])
            npu_output = self.npu_op_exec(npu_input1, item[1])
            self.assertRtolEqual(cpu_output, npu_output)


if __name__ == "__main__":
    run_tests()