Add ML Program support for basic activation ops (microsoft#21326)

### Description

Add support for:

- Sigmoid
- Relu
- Tanh

### Motivation and Context
Enable support for Autodesk model

Author: vraspar

onnxruntime/core/providers/coreml/builders/impl/activation_op_builder.cc

@@ -26,6 +26,8 @@ class ActivationOpBuilder : public BaseOpBuilder {
                          const logging::Logger& logger) const override;
 
   int GetMinSupportedOpSet(const Node& node) const override;
+
+  bool SupportsMLProgram() const override { return true; }
 };
 
 void ActivationOpBuilder::AddInitializersToSkip(ModelBuilder& model_builder, const Node& node) const {
@@ -74,33 +76,61 @@ Status AddPReluWeight(ModelBuilder& model_builder, const Node& node,
 Status ActivationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
                                                   const Node& node,
                                                   const logging::Logger& logger) const {
-  std::unique_ptr<COREML_SPEC::NeuralNetworkLayer> layer = model_builder.CreateNNLayer(node);
-
   const auto& op_type(node.OpType());
-  if (op_type == "Sigmoid") {
-    layer->mutable_activation()->mutable_sigmoid();
-  } else if (op_type == "Tanh") {
-    layer->mutable_activation()->mutable_tanh();
-  } else if (op_type == "Relu") {
-    layer->mutable_activation()->mutable_relu();
-  } else if (op_type == "PRelu") {
-    auto* prelu = layer->mutable_activation()->mutable_prelu();
-    ORT_RETURN_IF_ERROR(AddPReluWeight(model_builder, node, logger, *prelu));
-  } else if (op_type == "LeakyRelu") {
-    NodeAttrHelper helper(node);
-    const auto alpha = helper.Get("alpha", 0.01f);
-
-    auto* leaky_relu = layer->mutable_activation()->mutable_leakyrelu();
-    leaky_relu->set_alpha(alpha);
-  } else {
-    return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT,
-                           "ActivationOpBuilder::AddToModelBuilderImpl, unknown op: ", op_type);
-  }
 
-  *layer->mutable_input()->Add() = node.InputDefs()[0]->Name();
-  *layer->mutable_output()->Add() = node.OutputDefs()[0]->Name();
+#if defined(COREML_ENABLE_MLPROGRAM)
+  if (model_builder.CreateMLProgram()) {
+    using namespace CoreML::Specification::MILSpec;
+    // https://apple.github.io/coremltools/source/coremltools.converters.mil.mil.ops.defs.html#module-coremltools.converters.mil.mil.ops.defs.iOS15.activation
+    std::string_view coreml_op_type;
+    if (op_type == "Sigmoid") {
+      coreml_op_type = "sigmoid";
+    } else if (op_type == "Tanh") {
+      coreml_op_type = "tanh";
+    } else if (op_type == "Relu") {
+      coreml_op_type = "relu";
+    } else {
+      return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT,
+                             "ActivationOpBuilder::AddToModelBuilderImpl, unknown op: ", op_type);
+    }
+
+    std::unique_ptr<Operation> op = model_builder.CreateOperation(node, coreml_op_type);
+    AddOperationInput(*op, "x", node.InputDefs()[0]->Name());
+    AddOperationOutput(*op, *node.OutputDefs()[0]);
+
+    model_builder.AddOperation(std::move(op));
+
+  } else
+#endif  // (COREML_ENABLE_MLPROGRAM)
+  {
+    std::unique_ptr<COREML_SPEC::NeuralNetworkLayer> layer = model_builder.CreateNNLayer(node);
+
+    if (op_type == "Sigmoid") {
+      layer->mutable_activation()->mutable_sigmoid();
+    } else if (op_type == "Tanh") {
+      layer->mutable_activation()->mutable_tanh();
+    } else if (op_type == "Relu") {
+      layer->mutable_activation()->mutable_relu();
+    } else if (op_type == "PRelu") {
+      auto* prelu = layer->mutable_activation()->mutable_prelu();
+      ORT_RETURN_IF_ERROR(AddPReluWeight(model_builder, node, logger, *prelu));
+    } else if (op_type == "LeakyRelu") {
+      NodeAttrHelper helper(node);
+      const auto alpha = helper.Get("alpha", 0.01f);
+
+      auto* leaky_relu = layer->mutable_activation()->mutable_leakyrelu();
+      leaky_relu->set_alpha(alpha);
+    } else {
+      return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT,
+                             "ActivationOpBuilder::AddToModelBuilderImpl, unknown op: ", op_type);
+    }
+
+    *layer->mutable_input()->Add() = node.InputDefs()[0]->Name();
+    *layer->mutable_output()->Add() = node.OutputDefs()[0]->Name();
+
+    model_builder.AddLayer(std::move(layer));
+  }
 
-  model_builder.AddLayer(std::move(layer));
   return Status::OK();
 }
 
@@ -165,9 +195,20 @@ bool IsPReluOpSupported(const Node& node, const OpBuilderInputParams& input_para
 bool ActivationOpBuilder::IsOpSupportedImpl(const Node& node, const OpBuilderInputParams& input_params,
                                             const logging::Logger& logger) const {
   const auto& op_type = node.OpType();
-  if (op_type == "PRelu") {
-    return IsPReluOpSupported(node, input_params, logger);
+
+#if defined(COREML_ENABLE_MLPROGRAM)
+  if (input_params.create_mlprogram) {
+    if (op_type == "PRelu" || op_type == "LeakyRelu") {
+      return false;
+    }
+  } else
+#endif  // (COREML_ENABLE_MLPROGRAM)
+  {
+    if (op_type == "PRelu") {
+      return IsPReluOpSupported(node, input_params, logger);
+    }
   }
+
   return true;
 }
 

tools/ci_build/github/apple/coreml_supported_mlprogram_ops.md

@@ -18,3 +18,5 @@ Keep in sync with doco generated from /docs/execution-providers/CoreML-Execution
 |ai.onnx:Relu||
 |ai.onnx:Reshape||
 |ai.onnx:Sub||
+|ai.onnx:Sigmoid||
+|ai:onnx:Tanh||