[AOTI][refactor] Remove dead code (pytorch#149287)

Pull Request resolved: pytorch#149287
Approved by: https://github.com/cyyever, https://github.com/yushangdi

Author: desertfire

torch/_inductor/codegen/wrapper.py

@@ -124,72 +124,6 @@ def can_match_buffer_size(input_buf: BufferLike, output_buf: BufferLike):
     return False
 
 
-def convert_arg_type(arg: torch.Argument) -> str:
-    from .cpp import CONTAINER_PYTHON_TO_CPP, PYTHON_TO_CPP
-
-    # use x.real_type instead of x.type so that we get ScalarType instead of int
-    python_type = repr(arg.real_type)  # type: ignore[attr-defined]
-
-    if python_type == "Tensor":
-        # Conversions rules follow https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/native#func
-        if arg.alias_info is not None and arg.alias_info.is_write:
-            return f"at::{python_type}&"
-        else:
-            return f"at::{python_type} const&"
-
-    if python_type in PYTHON_TO_CPP:
-        cpp_type = PYTHON_TO_CPP[python_type]
-        return cpp_type
-
-    # Convert args of container types e.g. Optional[*]
-    for py_container, cpp_container in CONTAINER_PYTHON_TO_CPP.items():
-        container_match = re.findall(py_container + r"\[([a-zA-Z_]+)]", python_type)
-        if len(container_match) == 1:
-            contained_type = container_match[0]
-            assert contained_type in PYTHON_TO_CPP, (
-                f"unsupported {py_container} type in convert_arg_type: {contained_type}"
-            )
-            cpp_contained_type = PYTHON_TO_CPP[contained_type]
-            return f"{cpp_container}<{cpp_contained_type}>"
-
-    raise AssertionError(f"unsupport python_type: {python_type}")
-
-
-def convert_return_type(ret: torch.Argument) -> str:
-    # use x.real_type instead of x.type so that we get ScalarType instead of int
-    python_type = repr(ret.real_type)  # type: ignore[attr-defined]
-    python_to_cpp = {
-        "Tensor": "at::Tensor",
-        "List[Tensor]": "std::vector<at::Tensor>",
-    }
-
-    cpp_type = python_to_cpp.get(python_type, None)
-    assert cpp_type is not None, f"NYI return type: {python_type}"
-    # An output aliasing an input is returned by reference only when it's a
-    # Tensor, not when it's a Tensor[]. For example, aten.split.Tensor's output
-    # aliases the input tensor, but the op returns a vector by value.
-    if python_type == "Tensor" and ret.alias_info is not None:
-        cpp_type += "&"
-    return cpp_type
-
-
-def get_cpp_op_schema(kernel: torch._ops.OpOverload) -> str:
-    args = kernel._schema.arguments
-    returns = kernel._schema.returns
-
-    num_returns = len(returns)
-    assert num_returns > 0, "must have at least one return value"
-
-    if num_returns == 1:
-        cpp_return_value = convert_return_type(returns[0])
-    elif num_returns > 1:
-        tuple_returns = ", ".join([convert_return_type(r) for r in returns])
-        cpp_return_value = f"std::tuple<{tuple_returns}>"
-
-    cpp_arg_type = [f"{convert_arg_type(arg)} {arg.name}" for arg in args]
-    return f"{cpp_return_value}({', '.join(cpp_arg_type)})"  # type: ignore[possibly-undefined]
-
-
 # TODO: Move to a well known place
 TritonMetaParams = dict[str, int]
 TritonGrid = Union[