[Core] Expose a session option to disable NCHWc layout optimizations

include/onnxruntime/core/session/onnxruntime_session_options_config_keys.h

@@ -264,6 +264,14 @@ static const char* const kOrtSessionOptionsConfigIntraOpThreadAffinities = "sess
 // The model will be saved to filename post_layout_transform_step_<step_number>.onnx.
 static const char* const kDebugLayoutTransformation = "session.debug_layout_transformation";
 
+// Disables NCHWc layout transformation throughout the graph
+// If contrib ops are disabled, NCHWc layout transformation is disabled by default
+//
+// Option values:
+// - "0": NCHWc layout transformation is not disabled. [DEFAULT]
+// - "1": NCHWc layout transformation is disabled.
+static const char* const kOrtSessionOptionsDisableNchwcLayoutTransformation = "session.disable_nchwc_layout_transformation";
+
 // Graph nodes that are not supported by the execution providers (EPs) explicitly added to the session are
 // assigned (i.e., "fallback") to the CPU EP by default.
 //

onnxruntime/core/optimizer/graph_transformer_utils.cc

@@ -412,8 +412,11 @@ InlinedVector<std::unique_ptr<GraphTransformer>> GenerateTransformers(
 
     case TransformerLevel::Level3: {
 #ifndef DISABLE_CONTRIB_OPS
-      // Register the NCHWc layout transformer if supported by the platform.
-      if (MlasNchwcGetBlockSize() > 1) {
+      // Register the NCHWc layout transformer if supported by the platform and if user didn't explicitly disable it.
+      const bool disable_nchwc = session_options.config_options.GetConfigOrDefault(kOrtSessionOptionsDisableNchwcLayoutTransformation, "0") == "1";
+          session_options.config_options.GetConfigOrDefault(kOrtSessionOptionsAvx2PrecisionMode, "0") == "1" && MlasPlatformU8S8Overflow();
+
+      if (MlasNchwcGetBlockSize() > 1 && !disable_nchwc) {
         transformers.emplace_back(std::make_unique<NchwcTransformer>());
       }
 

onnxruntime/core/optimizer/nchwc_transformer.cc

@@ -13,7 +13,7 @@ namespace onnxruntime {
 
 class NchwcTransformerImpl {
  public:
-  NchwcTransformerImpl(Graph& graph) noexcept : graph_(graph) {}
+  NchwcTransformerImpl(Graph& graph, const logging::Logger& logger) noexcept : graph_(graph), logger_(logger) {}
 
   void Transform(Node& node);
   void Finalize(bool& modified);
@@ -160,6 +160,8 @@ class NchwcTransformerImpl {
   // NHWC to NCHW format.
   Node* transpose_from_nhwc_node_{nullptr};
   NodeArg* transpose_from_nhwc_output_arg_{nullptr};
+
+  const logging::Logger& logger_;
 };
 
 size_t NchwcTransformerImpl::RemoveOutputEdges(Node& node) {
@@ -335,6 +337,16 @@ void NchwcTransformerImpl::TransformConv(Node& node) {
 
   const int64_t output_channels = conv_W_tensor_proto->dims(0);
   const int64_t input_channels = conv_W_tensor_proto->dims(1);
+  const int64_t kH = conv_W_tensor_proto->dims(2);
+  const int64_t kW = conv_W_tensor_proto->dims(3);
+
+  if (kH >= 7 || kW >= 7) {
+    LOGS(logger_, WARNING) << "NCHWc Conv with large kernel (" << kH << "x" << kW
+                            << ") detected in node '" << node.Name()
+                            << "'. Please benchmark your target workload on the target hardware with "
+                            << "NCHWc layout optimizations enabled (default) and disabled (via session options)."
+                            << "On certain hardware, large kernel convolutions may perform worse with NCHWc layout.";
+  }
 
   int64_t group_count;
   const auto* group_attr = graph_utils::GetNodeAttribute(node, "group");
@@ -1227,7 +1239,7 @@ void NchwcTransformerImpl::Finalize(bool& modified) {
 }
 
 Status NchwcTransformer::ApplyImpl(Graph& graph, bool& modified, int graph_level, const logging::Logger& logger) const {
-  NchwcTransformerImpl impl(graph);
+  NchwcTransformerImpl impl(graph, logger);
   GraphViewer graph_viewer(graph);
 
   for (auto index : graph_viewer.GetNodesInTopologicalOrder()) {