Attempt to fix build break from torch version 1.12.0 released June 28…

…, 2022.
microsoft · Jun 29, 2022 · b481353 · b481353
1 parent 9be2b60
commit b481353
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Showing 3 changed files with 11 additions and 4 deletions.
diff --git a/orttraining/orttraining/eager/opgen/opgen/ast.py b/orttraining/orttraining/eager/opgen/opgen/ast.py
@@ -2,7 +2,8 @@
 # Licensed under the MIT License.
 
 import io
-from typing import TextIO, List, Union
+from typing import List, TextIO, Union
+
 from opgen.lexer import Token
 
 
@@ -355,6 +356,10 @@ class StreamType(ConcreteType):
     pass
 
 
+class SymIntType(ConcreteType):
+    pass
+
+
 # region Decls
 
 

diff --git a/orttraining/orttraining/eager/opgen/opgen/atenops.py b/orttraining/orttraining/eager/opgen/opgen/atenops.py
@@ -126,7 +126,6 @@ def __init__(self, dY, X):
     "aten::gelu": Gelu("self"),
     "aten::max": ReduceMax("self", keepdims=0),
     "aten::min": ReduceMin("self", keepdims=0),
-    "aten::_cat": Concat("tensors", "dim"),
     "aten::fill_.Scalar": ConstantOfShape("self", value="value"),
     "aten::ne.Scalar": MakeTorchFallback(),
     "aten::ne.Scalar_out": MakeTorchFallback(),
@@ -147,6 +146,7 @@ def __init__(self, dY, X):
 # This is done to make sure it is backward and future compatible
 if version.parse(torch.__version__) < version.parse(TORCH_API_CHANGE_VERSION):
     hand_implemented["aten::gelu_backward"] = GeluGrad("grad", "self")
+    hand_implemented["aten::_cat"] = Concat("tensors", "dim")
 else:
     hand_implemented["aten::gelu_backward"] = GeluGrad("grad_output", "self")
 

diff --git a/orttraining/orttraining/eager/opgen/opgen/parser.py b/orttraining/orttraining/eager/opgen/opgen/parser.py
@@ -1,9 +1,10 @@
 # Copyright (c) Microsoft Corporation. All rights reserved.
 # Licensed under the MIT License.
 
-from opgen.lexer import *
+from typing import List, Optional, Tuple, Union
+
 from opgen.ast import *
-from typing import List, Tuple, Union, Optional
+from opgen.lexer import *
 
 
 class UnexpectedTokenError(RuntimeError):
@@ -291,6 +292,7 @@ def _parse_torch_base_type(self) -> Type:
             "Storage": StorageType,
             "ConstQuantizerPtr": ConstQuantizerPtrType,
             "Stream": StreamType,
+            "SymInt": SymIntType,
         }
         identifier = self._expect_token(TokenKind.IDENTIFIER)
         base_type_parser = base_type_parsers.get(identifier.value)