const std::string tf_op_full_name = llvm::Twine("tf.", tf_op_name).str();

    // Create the TF op
    OperationState op_state(op.getLoc(), tf_op_full_name);
    op_state.addOperands(op.getOperands());
    op_state.addTypes(op.getResultTypes());

    SmallVector<NamedAttribute, 2> attrs;
    std::string parsed_op_name;
    tensorflow::NodeDef node_def;
    if (failed(ParseCustomOption(op.getCustomOption().getValue(), op.getLoc(),

    ) {
        List<TypeSpec> interceptorTypeSpecs = generateInterceptorClasses(requestsClassGroup, onFailure);

        return builder -> builder
            .addModifiers(Modifier.PUBLIC)
            .addTypes(interceptorTypeSpecs);
    }

    @SuppressWarnings("ReturnValueIgnored")

  DCHECK_GE(num_regions, 1);
  for (int i = 0; i < num_regions; ++i) {
    Region* region = state.addRegion();
    region->push_back(new Block);
  }
  state.addTypes(output_types);
}

Block& ParallelExecuteOp::GetRegionBlockWithIndex(unsigned index) {
  return getOperation()->getRegion(index).front();
}

Operation::result_range ParallelExecuteOp::GetRegionOutputs(

    bool WrapsSingleOp();
  }];

  let builders = [
    OpBuilder<(ins "StringAttr":$device, "TypeRange":$result_types),
    [{
      $_state.addAttribute("device", device);
      $_state.addTypes(result_types);
      $_state.addRegion();
    }]>
  ];

  let hasCanonicalizer = 1;
}

def TfDevice_ReturnOp : TfDevice_Op<"return", [Pure, ReturnLike, Terminator]> {
  let summary = [{

  let hasFolder = 1;
  let hasCanonicalizer = 1;

  let builders = [
    OpBuilder<(ins "TypedAttr":$value),
    [{
      $_state.addAttribute("value", value);
      $_state.addTypes(value.getType());
    }]>
  ];

  let extraClassDeclaration = [{
    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r);
  }];
}

    auto& new_control_inputs_for_item = it->second;
    builder.setInsertionPoint(&item);
    OperationState state(item.getLoc(), item.getName());
    types.assign(item.result_type_begin(), item.result_type_end());
    state.addTypes(types);
    for (Region& region : item.getRegions()) {
      state.addRegion()->takeBody(region);
    }
    // Assign existing operands for item.
    operands.assign(item.operand_begin(), item.operand_end());

  let hasFolder = 1;

  let builders = [
    OpBuilder<(ins "Attribute":$value),
    [{
      auto* ctx = value.getContext();
      $_state.addAttribute("value", value);
      $_state.addTypes(TFRAttrType::get(ctx));
    }]>
  ];

  let assemblyFormat = [{
    $value attr-dict `->` type($out)
  }];
}

def TFR_ConstantTensorOp : TFR_Op<"constant_tensor", [Pure]> {

		}
		if _, ok := dat[suffix]; ok {
			// Already handled.
			continue
		}

		b, err := sectionData(s)
		if err != nil {
			return nil, err
		}

		if suffix == "types" {
			err = d.AddTypes(fmt.Sprintf("types-%d", i), b)
		} else {
			err = d.AddSection(".debug_"+suffix, b)
		}
		if err != nil {
			return nil, err
		}
	}

	return d, nil
}

		}
		if _, ok := dat[suffix]; ok {
			// Already handled.
			continue
		}

		b, err := sectionData(s)
		if err != nil {
			return nil, err
		}

		if suffix == "types" {
			err = d.AddTypes(fmt.Sprintf("types-%d", i), b)
		} else {
			err = d.AddSection(".debug_"+suffix, b)
		}
		if err != nil {
			return nil, err
		}
	}

	return d, nil
}

TFRDialect::TFRDialect(MLIRContext *context)
    : Dialect(/*name=*/"tfr", context, TypeID::get<TFRDialect>()) {
  // TFR depends on TensorFlow for its canonicalization
  context->getOrLoadDialect<TF::TensorFlowDialect>();

  addTypes<TFRTensorType, TFRTensorListType, TFRAttrType>();
  addOperations<
#define GET_OP_LIST
#include "tensorflow/compiler/mlir/tfr/ir/tfr_ops.cc.inc"
      >();

  addInterfaces<TFRInlinerInterface>();
}