Revert D10412639: [nomnigraph] Add new NeuralNetOps for fusion

Differential Revision:
D10412639

Original commit changeset: a4c523fda96b

fbshipit-source-id: 973b6dd30b63b9a08069275278b0780b65067635

caffe2/core/nomnigraph/include/nomnigraph/Generated/OpClasses.h

@@ -639,23 +639,13 @@ class ChannelShuffle : public NeuralNetOperator {
 
 class Add : public NeuralNetOperator {
  public:
-  Add(int broadcast = 0)
-      : NeuralNetOperator(NNKind::Add), broadcast_(broadcast) {}
+  Add() : NeuralNetOperator(NNKind::Add) {}
 
   ~Add() {}
 
   NOMNIGRAPH_DEFINE_NN_RTTI(Add);
 
-  int getBroadcast() const {
-    return broadcast_;
-  }
-
-  void setBroadcast(int broadcast) {
-    broadcast_ = broadcast;
-  }
-
  private:
-  int broadcast_;
 };
 
 class Reshape : public NeuralNetOperator {

caffe2/core/nomnigraph/ops.def

@@ -63,7 +63,6 @@ Concat
 Softmax
 ChannelShuffle
 Add
-- Broadcast : int : 0
 Reshape
 Flatten
 

caffe2/opt/converter.cc

@@ -84,13 +84,10 @@ OperatorDef Converter::convertToOperatorDef(
     const nom::repr::NeuralNetOperator* nnOp) {
   auto* annotation = nnOp->getAnnotation();
   // Default to using the stored operator.
-  if (annotation && isa<Caffe2Annotation>(annotation)) {
+  if (isa<Caffe2Annotation>(annotation)) {
     return dyn_cast<Caffe2Annotation>(annotation)->getOperatorDef();
   }
-  LOG(WARNING) << "Cannot instantiate this OperatorDef from nomnigraph, falling back";
-  caffe2::OperatorDef op;
-  op.set_type(nnOp->getName());
-  return op;
+  CAFFE_THROW("TODO: Cannot yet instantiate OperatorDef from nomnigraph");
 }
 
 std::vector<int> getKernelShape(std::map<std::string, caffe2::Argument> argMap) {
@@ -159,13 +156,11 @@ class ClipConverter : public Converter {
     float max = std::numeric_limits<float>::max();
 
     if (argMap.count("min")) {
-      CAFFE_ENFORCE(argMap["min"].has_f(), "Invalid 'min' argument");
-      min = static_cast<float>(argMap["min"].f());
+      min = static_cast<float>(argMap["min"].i());
     }
 
     if (argMap.count("max")) {
-      CAFFE_ENFORCE(argMap["max"].has_f(), "Invalid 'max' argument");
-      max = static_cast<float>(argMap["max"].f());
+      max = static_cast<float>(argMap["max"].i());
     }
 
     return util::make_unique<repr::Clip>(min, max);
@@ -368,14 +363,13 @@ repr::NNModule convertToNNModule(
 caffe2::OperatorDef convertToOperatorDef(
     const repr::NNGraph::NodeRef& instrNode) {
   auto *nnOp = repr::nn::get<repr::NeuralNetOperator>(instrNode);
-  auto op_type = nnOp->getName();
   auto *annotation = nnOp->getAnnotation();
   caffe2::OperatorDef op;
 
-  if (ConverterRegistry()->Has(op_type)) {
-    op = ConverterRegistry()->Create(op_type)->convertToOperatorDef(nnOp);
+  if (ConverterRegistry()->Has(op.type())) {
+    op = ConverterRegistry()->Create(op.type())->convertToOperatorDef(nnOp);
   } else if (!annotation) {
-    op.set_type(op_type);
+    op.set_type(nnOp->getName());
   } else {
     if (isa<Caffe2Annotation>(annotation)) {
       auto c2_annotation = dyn_cast<Caffe2Annotation>(annotation);