add erf, tile

Author: xadupre

_unittests/ut_reference/test_torch_onnx_evaluator.py

@@ -671,7 +671,8 @@ def test_op_unary(self):
                     oh.make_node("Cos", ["X"], ["nx"]),
                     oh.make_node("Sin", ["nx"], ["t"]),
                     oh.make_node("Exp", ["t"], ["u"]),
-                    oh.make_node("Log", ["u"], ["Z"]),
+                    oh.make_node("Log", ["u"], ["uZ"]),
+                    oh.make_node("Erf", ["uZ"], ["Z"]),
                 ],
                 "dummy",
                 [oh.make_tensor_value_info("X", TFLOAT, ["a", "b"])],
@@ -1242,6 +1243,26 @@ def test_averagepool_2d(self):
             ),
         )
 
+    def test_tile(self):
+        model = oh.make_model(
+            oh.make_graph(
+                [oh.make_node("Tile", ["x", "repeat"], ["y"])],
+                "ut",
+                [
+                    oh.make_tensor_value_info("x", TFLOAT, [None, None]),
+                    oh.make_tensor_value_info("repeat", TFLOAT, [None]),
+                ],
+                [oh.make_tensor_value_info("y", TFLOAT, [None, None, None, None])],
+            ),
+            opset_imports=[oh.make_opsetid("", 18)],
+            ir_version=10,
+        )
+        self._finalize_test(
+            model,
+            torch.tensor([[1, 2], [3, 4]], dtype=torch.float32),
+            torch.tensor([2, 2], dtype=torch.int64),
+        )
+
 
 if __name__ == "__main__":
     unittest.main(verbosity=2)

onnx_diagnostic/reference/torch_ops/__init__.py

@@ -23,6 +23,7 @@
     CastLike_15,
     NonZero_13,
     Concat_1,
+    Tile_6,
     Transpose_1,
     Trilu_14,
     Where_9,
@@ -41,6 +42,7 @@
 from .unary_ops import (
     Abs_1,
     Cos_1,
+    Erf_9,
     Exp_1,
     Identity_1,
     Log_1,

onnx_diagnostic/reference/torch_ops/other_ops.py

@@ -52,6 +52,13 @@ def run(self, x: OpRunTensor) -> OpRunTensor:
         return OpRunTensor(torch.nonzero(x.tensor).T)
 
 
+class Tile_6(OpRun):
+    "Tile"
+
+    def run(self, x: OpRunTensor, repeat: OpRunTensor) -> OpRunTensor:
+        return OpRunTensor(torch.tile(x.tensor, repeat.as_tuple_int))
+
+
 class Transpose_1(OpRun):
     "Transpose"
 

onnx_diagnostic/reference/torch_ops/unary_ops.py

@@ -16,6 +16,13 @@ def run(self, x: OpRunTensor) -> OpRunTensor:
         return OpRunTensor(x.tensor.cos())
 
 
+class Erf_9(OpRun):
+    """Erf"""
+
+    def run(self, x: OpRunTensor) -> OpRunTensor:
+        return OpRunTensor(x.tensor.erf())
+
+
 class Exp_1(OpRun):
     """Exp"""