Revert "[inductor] Handle the case where kwargs contains tensor (#88215)"

This reverts commit 983c0e7f31.

Reverted https://github.com/pytorch/pytorch/pull/88215 on behalf of https://github.com/huydhn due to Sorry for reverting your PR but I think it breaks trunk https://github.com/pytorch/pytorch/actions/runs/3380662072/jobs/5613987333 with a failure in test_torchinductor_opinfo.py

test/inductor/test_torchinductor.py

@@ -4083,20 +4083,6 @@ class CommonTemplate:
                 else:
                     self.assertEqual(len(inps), 0)
 
-    @unittest.skipIf(HAS_CUDA, "histogramdd only supports cpu")
-    def test_kwargs(self):
-        def fn(x, y):
-            return torch.histogramdd(
-                x,
-                bins=[3, 3],
-                weight=y,
-            )
-
-        self.common(
-            fn,
-            [torch.randn((4, 2)), torch.randn((4))],
-        )
-
 
 if HAS_CPU:
 

torch/_inductor/ir.py

@@ -8,7 +8,6 @@ import textwrap
 from collections import OrderedDict
 from enum import Enum
 from functools import partial
-from inspect import signature
 from typing import Any, Callable, ClassVar, Dict, List, Optional, Set, Tuple, Union
 from unittest.mock import patch
 
@@ -2237,8 +2236,7 @@ class ExternKernel(InputsKernel):
 
     @classmethod
     def process_kernel(cls, kernel, *args, **kwargs):
-        binded_args = signature(kernel).bind(*args, **kwargs).arguments
-        args_flat, args_spec = pytree.tree_flatten(binded_args)
+        args_flat, args_spec = pytree.tree_flatten(args)
 
         is_arg_tensor = []
         tensor_args = []
@@ -2251,16 +2249,15 @@ class ExternKernel(InputsKernel):
                 non_tensor_args.append(arg)
 
         def unflatten_args(new_tensor_args, new_non_tensor_args):
-            result = []
+            new_args = []
             it_tensors = iter(new_tensor_args)
             it_non_tensors = iter(new_non_tensor_args)
             for is_tensor in is_arg_tensor:
                 if is_tensor:
-                    result.append(next(it_tensors))
+                    new_args.append(next(it_tensors))
                 else:
-                    result.append(next(it_non_tensors))
-            result = pytree.tree_unflatten(result, args_spec)
-            return result.get("args", []), result.get("kwargs", {})
+                    new_args.append(next(it_non_tensors))
+            return pytree.tree_unflatten(new_args, args_spec)
 
         tensor_args = [cls.realize_input(x) for x in tensor_args]
 
@@ -2286,8 +2283,9 @@ class ExternKernel(InputsKernel):
             ).zero_()
             example_args.append(arg)
 
-        new_args, new_kwargs = unflatten_args(example_args, non_tensor_args)
-        example_output = kernel(*new_args, **new_kwargs)
+        example_output = kernel(
+            *unflatten_args(example_args, non_tensor_args), **kwargs
+        )
 
         return example_output, tensor_args, non_tensor_args, unflatten_args
 
@@ -2880,13 +2878,15 @@ class FallbackKernel(ExternKernelAlloc):
             def __repr__(self):
                 return self.ref
 
+        tensor_args = [Shim(x.codegen_reference()) for x in self.inputs]
+        constant_args = [Shim(repr(x)) for x in self.constant_args]
+
         def gen_kwarg(k, v):
             return f"{k}={repr(v)}"
 
-        tensor_args = [Shim(x.codegen_reference()) for x in self.inputs]
-        constant_args = [Shim(repr(x)) for x in self.constant_args]
-        args, kwargs = self.unflatten_args(tensor_args, constant_args)
-        return list(map(repr, args)) + list(gen_kwarg(k, v) for k, v in kwargs.items())
+        kwargs = list(gen_kwarg(k, v) for k, v in self.kwargs.items())
+
+        return list(map(repr, self.unflatten_args(tensor_args, constant_args))) + kwargs
 
     @classmethod
     def create(cls, kernel, *args, **kwargs):

torch/_inductor/lowering.py

@@ -164,10 +164,8 @@ def _register_lowering(
             args = args[0]
         # Only look at args that are Tensors
         indices = [i for i, x in enumerate(args) if isinstance(x, TensorBox)]
-        # kwargs tensors not supported yet unless it's a fallback op
-        assert not any(isinstance(x, TensorBox) for x in kwargs.values()) or all(
-            fn in fallbacks for fn in aten_fn
-        )
+        # kwargs tensors not supported yet
+        assert not any(isinstance(x, TensorBox) for x in kwargs.values())
 
         if (type_promotion_kind or convert_input_to_bool) and indices:
             if convert_input_to_bool: