Allow importing variadic inputs/outputs of onnx operators (#16)

* Allow importing variadic inputs/outputs of onnx operators

* Enable testcases for variadic ops

* Modify gen_doc.py

src/builder/frontend_dialect_transformer.cpp

@@ -330,8 +330,8 @@ private:
    * default}
    */
   template <typename T>
-  void
+  void ImportNodeOneOut(const onnx::NodeProto &node, int nIn, int nOut,
-  ImportNodeOneOut(const onnx::NodeProto &node, int nIn, int nOut) {
+                        bool variadicIn = false, bool variadicOut = false) {
     std::vector<mlir::Value> inputs;
     for (const auto &item : node.input()) {
       if (frontend_symbols_.ContainKey(legalize_name(item))) {
@@ -348,8 +348,8 @@ private:
     auto attributes = ImportNodeAttributes(node);
 
     llvm::StringRef OpName = node.op_type();
-
+    if ((variadicIn || nIn == inputs.size()) &&
-    if (nIn == inputs.size() && nOut == outputTypes.size()) {
+        (variadicOut || nOut == outputTypes.size())) {
       auto op =
           builder_.create<T>(UnknownLoc(), outputTypes, inputs, attributes);
       frontend_symbols_.AddMapping(legalize_name(node.output()[0]),
@@ -360,8 +360,9 @@ private:
   }
 
   template <typename T>
-  void ImportNodeMultipleOuts(
+  void ImportNodeMultipleOuts(const onnx::NodeProto &node, int nIn, int nOut,
-      const onnx::NodeProto &node, int nIn, int nOut) {
+                              bool variadicIn = false,
+                              bool variadicOut = false) {
     std::vector<mlir::Value> inputs;
     for (const auto &item : node.input()) {
       if (frontend_symbols_.ContainKey(legalize_name(item))) {
@@ -379,7 +380,8 @@ private:
 
     llvm::StringRef OpName = node.op_type();
 
-    if (nIn == inputs.size() && nOut == outputTypes.size()) {
+    if ((variadicIn || nIn == inputs.size()) &&
+        (variadicOut || nOut == outputTypes.size())) {
       auto op =
           builder_.create<T>(UnknownLoc(), outputTypes, inputs, attributes);
       for (int i = 0; i < node.output().size(); i++) {

src/builder/op_build_table.inc

@@ -36,7 +36,7 @@
     }else if (OpName == "Compress") {
        ImportNodeOneOut<mlir::ONNXCompressOp>(node, 2, 1);
     }else if (OpName == "Concat") {
-       ImportNodeOneOut<mlir::ONNXConcatOp>(node, 1, 1);
+       ImportNodeOneOut<mlir::ONNXConcatOp>(node, 1, 1, true, false);
     }else if (OpName == "ConcatFromSequence") {
        ImportNodeOneOut<mlir::ONNXConcatFromSequenceOp>(node, 1, 1);
     }else if (OpName == "Constant") {
@@ -138,7 +138,7 @@
     }else if (OpName == "MatMulInteger") {
        ImportNodeOneOut<mlir::ONNXMatMulIntegerOp>(node, 4, 1);
     }else if (OpName == "Max") {
-       ImportNodeOneOut<mlir::ONNXMaxOp>(node, 1, 1);
+       ImportNodeOneOut<mlir::ONNXMaxOp>(node, 1, 1, true, false);
     }else if (OpName == "MaxPool") {
        ImportNodeMaxPool(node, 1, 2);
     }else if (OpName == "MaxRoiPool") {
@@ -146,11 +146,11 @@
     }else if (OpName == "MaxUnpool") {
        ImportNodeOneOut<mlir::ONNXMaxUnpoolOp>(node, 3, 1);
     }else if (OpName == "Mean") {
-       ImportNodeOneOut<mlir::ONNXMeanOp>(node, 1, 1);
+       ImportNodeOneOut<mlir::ONNXMeanOp>(node, 1, 1, true, false);
     }else if (OpName == "MeanVarianceNormalization") {
        ImportNodeOneOut<mlir::ONNXMeanVarianceNormalizationOp>(node, 1, 1);
     }else if (OpName == "Min") {
-       ImportNodeOneOut<mlir::ONNXMinOp>(node, 1, 1);
+       ImportNodeOneOut<mlir::ONNXMinOp>(node, 1, 1, true, false);
     }else if (OpName == "Mod") {
        ImportNodeOneOut<mlir::ONNXModOp>(node, 2, 1);
     }else if (OpName == "Mul") {
@@ -240,7 +240,7 @@
     }else if (OpName == "SequenceAt") {
        ImportNodeOneOut<mlir::ONNXSequenceAtOp>(node, 2, 1);
     }else if (OpName == "SequenceConstruct") {
-       ImportNodeOneOut<mlir::ONNXSequenceConstructOp>(node, 1, 1);
+       ImportNodeOneOut<mlir::ONNXSequenceConstructOp>(node, 1, 1, true, false);
     }else if (OpName == "SequenceEmpty") {
        ImportNodeOneOut<mlir::ONNXSequenceEmptyOp>(node, 0, 1);
     }else if (OpName == "SequenceErase") {
@@ -286,7 +286,7 @@
     }else if (OpName == "Sub") {
        ImportNodeOneOut<mlir::ONNXSubOp>(node, 2, 1);
     }else if (OpName == "Sum") {
-       ImportNodeOneOut<mlir::ONNXSumOp>(node, 1, 1);
+       ImportNodeOneOut<mlir::ONNXSumOp>(node, 1, 1, true, false);
     }else if (OpName == "Tan") {
        ImportNodeOneOut<mlir::ONNXTanOp>(node, 1, 1);
     }else if (OpName == "Tanh") {

src/dialect/onnx/gen_doc.py

@@ -384,6 +384,8 @@ def gen_code(schema,fefile) :
         #("Transpose", "ImportNodeTranspose")
         ])
 
+    handle_variadic = False
+
     line_indent = '  '
     fefile.write('    '+'}else if (OpName == "'+schema.name+'") {\n')
     op_type_str='mlir::ONNX'+schema.name+'Op'
@@ -399,7 +401,22 @@ def gen_code(schema,fefile) :
         fefile.write('       '+'ImportNodeOneOut<'+op_type_str+'>(node, '
           +str(len(schema.inputs))
           +', ' +str(len(schema.outputs)))
-    fefile.write(');\n')
+
+    variadicIn = 'false'
+    variadicOut = 'false'
+    for input in schema.inputs:
+        if OpSchema.FormalParameterOption.Variadic == input.option:
+            if input.isHomogeneous:
+                variadicIn = 'true'
+                handle_variadic = True
+    for output in schema.outputs:
+        if OpSchema.FormalParameterOption.Variadic == output.option:
+            if output.isHomogeneous:
+                variadicOut = 'true'
+    if not handle_variadic:
+        fefile.write(');\n')
+    else:
+        fefile.write(', '+variadicIn+', '+variadicOut+');\n')
 
 def gen_attr_ins(schema, isfirst) :
     special_defaults = dict([

test/backend/test.py

@@ -104,14 +104,14 @@ test_to_enable = [
     "test_leakyrelu_example_cpu",
 
     # Max Op:
-    # "test_max_example_cpu", <- error
+    "test_max_example_cpu",
     "test_max_one_input_cpu",
-    # "test_max_two_inputs_cpu", <- error
+    "test_max_two_inputs_cpu",
 
     # Min Op:
-    # "test_min_example_cpu", <- error
+    "test_min_example_cpu",
     "test_min_one_input_cpu",
-    # "test_min_two_inputs_cpu", <- error
+    "test_min_two_inputs_cpu",
 
     # Mul Op:
     "test_mul_cpu",
@@ -139,9 +139,9 @@ test_to_enable = [
     "test_softmax_large_number_cpu",
 
     # Sum Op:
-    #"test_sum_example_cpu", <- error
+    "test_sum_example_cpu",
     "test_sum_one_input_cpu",
-    #"test_sum_two_inputs_cpu", <- error
+    "test_sum_two_inputs_cpu",
 
     # Reciprocal Op:
     "test_reciprocal_cpu",