Remove ImportNodeReshape (#208)

src/Builder/FrontendDialectTransformer.cpp

@@ -313,26 +313,6 @@ private:
         node, inputs, expectedNumOperands, expectedNumResults);
   }
 
-  void ImportNodeReshape(onnx::NodeProto node) {
-    int expectedNumOperands = mlir::ONNXReshapeOp::getNumberOfOperands();
-    int expectedNumResults = mlir::ONNXReshapeOp::getNumberOfResults();
-    std::vector<mlir::Value> inputs;
-    std::string item;
-    for (int i = 0; i < node.input().size(); ++i) {
-      item = node.input()[i];
-      // For the second argument, check if there exists an initializer.
-      if (initializedTensors.ContainKey(legalize_name(item))) {
-        inputs.push_back(initializedTensors.EmitInitializerForInputTensor(
-            UnknownLoc(), builder_, legalize_name(item)));
-      } else if (frontend_symbols_.ContainKey(legalize_name(item))) {
-        inputs.push_back(frontend_symbols_.GetTensorByOnnxName(item));
-      }
-    }
-
-    buildOutputAndOperation<mlir::ONNXReshapeOp>(
-        node, inputs, expectedNumOperands, expectedNumResults);
-  }
-
   /*!
    * Special handle for MaxPool operations.
    */

src/Builder/OpBuildTable.inc

@@ -223,7 +223,7 @@ if (opName == "ReduceSumSquare")
 if (opName == "Relu")
    buildOperation<mlir::ONNXReluOp>(node);
 if (opName == "Reshape")
-   ImportNodeReshape(node);
+   buildOperation<mlir::ONNXReshapeOp>(node);
 if (opName == "Resize")
    buildOperation<mlir::ONNXResizeOp>(node);
 if (opName == "ReverseSequence")

utils/gen_onnx_mlir.py

@@ -239,7 +239,6 @@ special_op_handler = dict([
     ("MaxPool", "ImportNodeMaxPool"),
     ("BatchNormalization", "ImportNodeBatchNormalization"),
     ("Pad", "ImportNodePad"),
-    ("Reshape", "ImportNodeReshape"),
     #("Transpose", "ImportNodeTranspose")
 ])