[opt:fuse_pad_into_conv] remove NOTSET auto_pad (#251)

#33

---------

Signed-off-by: 462630221 <462630221@qq.com>
Signed-off-by: take-cheeze <takechi101010@gmail.com>
Co-authored-by: 462630221 <462630221@qq.com>

Author: take-cheeze

onnxoptimizer/passes/fuse_pad_into_conv.h

@@ -119,6 +119,14 @@ struct FusePadIntoConv final : public PredicateBasedPass {
       return false;
     }
 
+    // Clean the auto_pad if NOTSET
+    if (conv->hasAttribute(Symbol("auto_pad"))) {
+      if (conv->s(Symbol("auto_pad")) != "NOTSET") {
+        return false;
+      }
+      conv->removeAttribute(Symbol("auto_pad"));
+    }
+
     int conv_pads_size = pads_size - 4;
     std::vector<int64_t> conv_pads(conv_pads_size, 0);
     // Fuse into existing padding, if available

onnxoptimizer/test/optimizer_test.py

@@ -2011,6 +2011,33 @@ def test_fuse_pad_into_conv_reflection_pad_no_fuse(self):
 
         assert optimized_model.graph == graph
 
+    # type: () -> None
+    def test_fuse_pad_into_conv_with_notset_autopad(self):
+        pad = helper.make_node(
+            "Pad", ["X"], ["P"], mode="constant", pads=[0, 0, 0, 0, 0, 0, 1, 1]
+        )
+        conv = helper.make_node("Conv", ["P", "Y"], ["Z"], auto_pad="NOTSET")
+        graph = helper.make_graph(
+            [pad, conv],
+            "test",
+            [
+                helper.make_tensor_value_info("X", TensorProto.FLOAT, (1, 5, 2, 2)),
+                helper.make_tensor_value_info("Y", TensorProto.FLOAT, (16, 5, 3, 3)),
+            ],
+            [helper.make_tensor_value_info("Z", TensorProto.FLOAT, (1, 16, 1, 1))],
+        )
+        optimized_model = self._optimized(
+            graph,
+            ["fuse_pad_into_conv"],
+            False,
+            opset_imports=[helper.make_opsetid("", 10)],
+        )
+
+        assert len(list(optimized_model.graph.node)) == 1
+        assert optimized_model.graph.node[0].op_type == "Conv"
+        assert optimized_model.graph.node[0].attribute[0].name == "pads"
+        assert list(optimized_model.graph.node[0].attribute[0].ints) == [0, 0, 1, 1]
+
     def test_fuse_pad_into_avgpool_no_optional_value_opset10(self):
         pad = helper.make_node(
             "Pad", ["X"], ["P"], mode="constant", pads=[0, 0, 0, 0, 0, 0, 1, 1]