[ez] remove unused functions (#156466)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/156466
Approved by: https://github.com/jingsh

torch/_inductor/codegen/multi_kernel.py

@@ -18,65 +18,6 @@ from .common import TensorArg, WorkspaceArg
 log = logging.getLogger(__name__)
 
 
-def get_kernel_argdefs(kernel):
-    arg_defs, _, _, _ = kernel.args.python_argdefs()
-    return [x.name for x in arg_defs]
-
-
-def _get_all_args(args_list, arg_types_list=None):
-    all_args = max(args_list, key=len)[:]
-    arg_types = max(arg_types_list, key=len)[:] if arg_types_list is not None else None
-    for args in args_list:
-        assert OrderedSet(args).issubset(OrderedSet(all_args)), (
-            f"{args} v.s. {all_args}"
-        )
-
-    return all_args, arg_types
-
-
-def get_all_kernel_argdefs(kernels):
-    """
-    The logic here must match with `get_all_call_args`, except no need to get arg_types here
-    """
-    argdefs_list = [get_kernel_argdefs(kernel) for kernel in kernels]
-
-    return _get_all_args(argdefs_list)[0]
-
-
-def get_all_call_args(call_args_list, arg_types_list):
-    """
-    Passed in the call_args for each subkernel and return the call_args for the
-    combined multi-kernel.
-
-    Note an algorithm as follows does not always work:
-    ```
-        all_call_args: Dict[
-            Any, None
-        ] = {}  # use a dict rather than set to maintain insertion order
-        for call_args in call_args_list:
-            all_call_args.update({arg: None for arg in call_args})
-
-        all_call_args = list(all_call_args.keys())
-    ```
-    It will fail if any kernel has the same argument passed in multiple times.
-    Check test_pass_same_arg_multi_times in test_multi_kernel.py
-
-    Instead, we pick the longest call args and assert that other call args are
-    a subset of it.
-    """
-    return _get_all_args(call_args_list, arg_types_list)
-
-
-def get_numel_argdefs(kernel):
-    numel_argdefs = [
-        f"{tree.prefix}numel"
-        for tree in kernel.range_trees
-        if not tree.is_reduction or kernel.inside_reduction
-    ]
-
-    return numel_argdefs
-
-
 class MultiKernelState:
     """
     Maintain state of multi-kernel compilation so we don't define duplicated