From f98ab184452e748d7b79629bbd079fcbb909d838 Mon Sep 17 00:00:00 2001
From: Jiakai Liu <liujiakai@fb.com>
Date: Thu, 19 Nov 2020 12:27:23 -0800
Subject: [PATCH] [pytorch][codegen] move is_abstract property to
 NativeFunction model (#48252)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48252

Moved to a shared place so that gen_variable_type.py can reuse it.

Test Plan: Imported from OSS

Reviewed By: ezyang

Differential Revision: D25087808

Pulled By: ljk53

fbshipit-source-id: 1f32e506956fc4eb08734cfde0add47b3e666bd9
---
 tools/codegen/gen.py   | 23 +----------------------
 tools/codegen/model.py | 16 ++++++++++++++++
 2 files changed, 17 insertions(+), 22 deletions(-)

diff --git a/tools/codegen/gen.py b/tools/codegen/gen.py
index 5324246d6c8e..a0a1f21d13dc 100644
--- a/tools/codegen/gen.py
+++ b/tools/codegen/gen.py
@@ -845,12 +845,6 @@ def compute_declaration_yaml(f: NativeFunction) -> object:
     is_factory_method = any(isinstance(a.argument, TensorOptionsArguments) for a in cpp_args) \
         and Variant.method not in f.variants
 
-    if f.structured_delegate:
-        # Structured functions MUST have a dispatch table
-        is_abstract = True
-    else:
-        is_abstract = f.dispatch.keys() != {'Math'}
-
     return OrderedDict([
         ('name', cpp.name(f.func)),
         ('operator_name', str(f.func.name.name)),
@@ -869,22 +863,7 @@ def compute_declaration_yaml(f: NativeFunction) -> object:
         ('returns', returns),
         ('inplace', f.func.name.name.inplace),
         ('is_factory_method', is_factory_method),
-        # Note [Abstract ATen methods]
-        # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-        # An abstract ATen method is one whose dispatch differs between
-        # types.  These are implemented in derived types (with a
-        # standard (throwing) definition in Type).  A concrete ATen
-        # method is one which has the same dispatch for all types;
-        # we just implement it in the base Type.  This is exposed
-        # in Declarations.yaml via a field named 'abstract'.
-        #
-        # Although this is what we have historically exposed, it is
-        # actually not all that useful for end users, who are also interested
-        # whether or not there is an explicit entry in derivatives.yaml
-        # for the entry or not (as this affects whether or not the operation is
-        # overrideable or not.)  Once this all gets cleaned up, this
-        # property will be obsolete.
-        ('abstract', is_abstract),
+        ('abstract', f.is_abstract),
         ('device_guard', f.device_guard),
         ('with_gil', False),
         ('deprecated', False),
diff --git a/tools/codegen/model.py b/tools/codegen/model.py
index bddbfd4f5338..c7425444c165 100644
--- a/tools/codegen/model.py
+++ b/tools/codegen/model.py
@@ -125,6 +125,22 @@ class NativeFunction:
     # in terms of the out kernel referenced by the string here.
     structured_delegate: Optional['OperatorName']
 
+    # Note [Abstract ATen methods]
+    # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+    # An abstract ATen method is one whose dispatch differs between
+    # types.  These are implemented in derived types (with a
+    # standard (throwing) definition in Type).  A concrete ATen
+    # method is one which has the same dispatch for all types;
+    # we just implement it in the base Type.  This is exposed
+    # in Declarations.yaml via a field named 'abstract'.
+    @property
+    def is_abstract(self) -> bool:
+        if self.structured_delegate:
+            # Structured functions MUST have a dispatch table
+            return True
+        else:
+            return self.dispatch.keys() != {'Math'}
+
     # NB: The benefit of defining a dataclass is that we automatically get
     # a constructor defined for all the fields we specify.  No need
     # to explicitly write it out.