Revert "[hop] ban creating hop by directly instantiating HigherOrderOperator. (pytorch#133645)"

This reverts commit 696107e. Reverted pytorch#133645 on behalf of https://github.com/ydwu4 due to breaking ci. probably due to land race ([comment](pytorch#133645 (comment)))

Author: pytorchmergebot

test/dynamo/test_higher_order_ops.py

@@ -6299,11 +6299,7 @@ def fn(x):
  self._validate(fn, backend, x)
 
  def test_override_fallthrough_dispatch_key(self):
- class _FallthroughTestOnly(torch._ops.HigherOrderOperator):
- def __init__(self):
- super().__init__("_fallthrough_test_only")
-
- test_op = _FallthroughTestOnly()
+ test_op = torch._ops.HigherOrderOperator("_fallthrough_test_only")
  default_keys = torch._ops._HIGHER_ORDER_OP_DEFAULT_FALLTHROUGH_DISPATCH_KEYS
  self.assertTrue(
  not any(test_op.non_fallthrough_keys.has(key) for key in default_keys)

test/functorch/test_eager_transforms.py

@@ -4989,11 +4989,7 @@ def forward(self, x_1):
 
 
 def construct_sum_pyop():
- class MySum(HigherOrderOperator):
- def __init__(self):
- super().__init__("mysum")
-
- mysum = MySum()
+ mysum = HigherOrderOperator("mysum")
 
  @mysum.py_impl(torch._C._functorch.TransformType.Vmap)
  def mysum_batch_rule(interpreter, x, dim):

torch/_dynamo/_trace_wrapped_higher_order_op.py

@@ -48,13 +48,8 @@ def trace_wrapped(*args, **kwargs):
  return _trace_wrapped_op(*args, **kwargs)
 
 
-class TraceWrapped(HigherOrderOperator):
- def __init__(self):
- super().__init__("trace_wrapped")
-
-
 # TODO(jansel): need to ensure this does not get DCEed
-_trace_wrapped_op = TraceWrapped()
+_trace_wrapped_op = HigherOrderOperator("trace_wrapped")
 
 
 def _assert_meta(grad, size, stride, dtype):

torch/_export/wrappers.py

@@ -12,12 +12,7 @@
 from torch.utils import _pytree as pytree
 
 
-class ExportTracepoint(HigherOrderOperator):
- def __init__(self):
- super().__init__("export_tracepoint")
-
-
-_export_tracepoint = ExportTracepoint()
+_export_tracepoint = HigherOrderOperator("_export_tracepoint")
 
 
 @_export_tracepoint.py_impl(ProxyTorchDispatchMode)

torch/_higher_order_ops/executorch_call_delegate.py

@@ -25,12 +25,7 @@
 from torch.utils._pytree import tree_flatten
 
 
-class ExecutorchCallDelegate(HigherOrderOperator):
- def __init__(self):
- super().__init__("executorch_call_delegate")
-
-
-executorch_call_delegate = ExecutorchCallDelegate()
+executorch_call_delegate = HigherOrderOperator("executorch_call_delegate")
 executorch_call_delegate.fallthrough(torch._C.DispatchKey.PythonDispatcher)
 executorch_call_delegate.fallthrough(torch._C.DispatchKey.PythonTLSSnapshot)
 executorch_call_delegate.fallthrough(torch._C.DispatchKey.ADInplaceOrView)

torch/_higher_order_ops/map.py

@@ -36,14 +36,8 @@ def __call__(self, xs, *args):
  return map_wrapper(xs, *args)
 
 
-class MapImpl(HigherOrderOperator):
- def __init__(self):
- super().__init__("map_impl")
-
-
 map = MapWrapper("map")
-
-map_impl = MapImpl()
+map_impl = HigherOrderOperator("map_impl")
 
 dummy_aot_config = AOTConfig(
  fw_compiler=None, # type: ignore[arg-type]

torch/_higher_order_ops/run_const_graph.py

@@ -8,12 +8,7 @@
 from torch.utils import _pytree as pytree
 
 
-class RunConstGraph(HigherOrderOperator):
- def __init__(self):
- super().__init__("run_const_graph")
-
-
-run_const_graph = RunConstGraph()
+run_const_graph = HigherOrderOperator("run_const_graph")
 
 
 @run_const_graph.py_impl(ProxyTorchDispatchMode)

torch/_higher_order_ops/strict_mode.py

@@ -28,12 +28,7 @@ def strict_mode(callable, operands):
  )
 
 
-class StrictMode(HigherOrderOperator):
- def __init__(self):
- super().__init__("strict_mode")
-
-
-strict_mode_op = StrictMode()
+strict_mode_op = HigherOrderOperator("strict_mode")
 
 
 @strict_mode_op.py_impl(DispatchKey.CompositeExplicitAutograd)

torch/_higher_order_ops/torchbind.py

@@ -16,18 +16,12 @@
 
 log = logging.getLogger(__name__)
 
-
 # The call_torchbind operator represents a method invocation on a torchbind
 # object. The calling convention is:
 # call_torchbind(self: ScriptObject, method_name: str, *method_args, **method_kwargs)
 # We do not expect users to write this operator directly. Instead it will be
 # emitted by Dynamo when tracing encounters a torchbind object.
-class CallTorchBind(HigherOrderOperator):
- def __init__(self):
- super().__init__("call_torchbind")
-
-
-call_torchbind = CallTorchBind()
+call_torchbind = HigherOrderOperator("call_torchbind")
 
 # Register this operator as side-effectful with FX.
 # TODO: this is not really sufficient. While passes (hopefully) check

torch/_ops.py

@@ -246,10 +246,6 @@ class HigherOrderOperator(OperatorBase):
  # practice due to name collisions.
  def __init__(self, name):
  super().__init__()
- if type(self) is HigherOrderOperator:
- raise RuntimeError(
- "Direct instantiation of HigherOrderOperator is not allowed. Please subclass it."
- )
  self._name = name
 
  # Make _OPNamespace not scream, this whole name based association needs a good hard look