import sys
import os

sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))

import infinicore
import torch
from framework import (
    BaseOperatorTest,
    TensorSpec,
    TestCase,
    GenericTestRunner,
    is_broadcast,
)

# Test cases format: (shape, a_strides_or_None, b_strides_or_None, out_strides_or_None)
# equal compares element-wise and returns boolean tensor

_TEST_CASES_DATA = [
    ((8, 8), None, None, None),
    ((8, 8), (16, 1), (16, 1), None),
    ((8, 8), None, (0, 1), None),
    ((1, 8), None, None, (8, 1)),
    ((2, 3, 4), None, None, None),
    ((16, 128), (256, 1), (256, 1), None),
]

_TOLERANCE_MAP = {
    infinicore.float16: {"atol": 0, "rtol": 1e-2},
    infinicore.float32: {"atol": 0, "rtol": 1e-3},
    infinicore.int32: {"atol": 0, "rtol": 0},
}

_TENSOR_DTYPES = [infinicore.float16, infinicore.float32, infinicore.int32]


def parse_test_cases():
    test_cases = []
    for data in _TEST_CASES_DATA:
        shape, a_strides, b_strides, out_strides = data[0], data[1], data[2], data[3]

        a_supports_inplace = not is_broadcast(a_strides)
        b_supports_inplace = not is_broadcast(b_strides)
        out_supports_inplace = not is_broadcast(out_strides)

        for dtype in _TENSOR_DTYPES:
            tol = _TOLERANCE_MAP.get(dtype, {"atol": 0, "rtol": 1e-3})
            a_spec = TensorSpec.from_tensor(shape, a_strides, dtype)
            b_spec = TensorSpec.from_tensor(shape, b_strides, dtype)
            out_spec = TensorSpec.from_tensor(shape, out_strides, infinicore.bool)

            # Out-of-place
            test_cases.append(
                TestCase(
                    inputs=[a_spec, b_spec],
                    kwargs={},
                    output_spec=None,
                    comparison_target=None,
                    tolerance=tol,
                    description="Equal - OUT_OF_PLACE",
                )
            )

            # explicit out
            if out_supports_inplace:
                test_cases.append(
                    TestCase(
                        inputs=[a_spec, b_spec],
                        kwargs=None,
                        output_spec=out_spec,
                        comparison_target="out",
                        tolerance=tol,
                        description="Equal - INPLACE(out)",
                    )
                )

            # Equal 结果为 bool，无法安全复用浮点/整型输入作为输出缓冲区。
            # 只有当输入 dtype 本身为 bool 时才允许 inplace，这里提前留出开关。
            allow_input_inplace = dtype == infinicore.bool

            if allow_input_inplace and a_supports_inplace:
                test_cases.append(
                    TestCase(
                        inputs=[a_spec, b_spec],
                        kwargs={"out": 0},
                        output_spec=None,
                        comparison_target=0,
                        tolerance=tol,
                        description="Equal - INPLACE(a)",
                    )
                )

            if allow_input_inplace and b_supports_inplace:
                test_cases.append(
                    TestCase(
                        inputs=[a_spec, b_spec],
                        kwargs={"out": 1},
                        output_spec=None,
                        comparison_target=1,
                        tolerance=tol,
                        description="Equal - INPLACE(b)",
                    )
                )

    return test_cases


class OpTest(BaseOperatorTest):
    """Equal operator test with simplified implementation"""

    def __init__(self):
        super().__init__("Equal")

    def get_test_cases(self):
        return parse_test_cases()

    def torch_operator(self, *args, **kwargs):
        return torch.eq(*args, **kwargs)

    def infinicore_operator(self, *args, **kwargs):
        return infinicore.equal(*args, **kwargs)


def main():
    """Main entry point"""
    runner = GenericTestRunner(OpTest)
    runner.run_and_exit()


if __name__ == "__main__":
    main()
