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Author: borg323

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

@@ -39,8 +39,6 @@ Status UnaryOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, const
       coreml_op_type = "round";
     } else if (op_type == "Exp") {
       coreml_op_type = "exp";
-    } else if (op_type == "Log") {
-      coreml_op_type = "log";
     } else {
       return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT,
                              "UnaryOpBuilder::AddToModelBuilderImpl, unexpected op: ", op_type);
@@ -84,7 +82,7 @@ Status UnaryOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, const
 bool UnaryOpBuilder::IsOpSupportedImpl(const Node& node, const OpBuilderInputParams& input_params,
                                        const logging::Logger& /*logger*/) const {
   if (!input_params.create_mlprogram) {
-    if (node.OpType() == "Erf" || node.OpType() == "Round" || node.OpType() == "Exp" || node.OpType() == "Log") {
+    if (node.OpType() == "Erf" || node.OpType() == "Round" || node.OpType() == "Exp") {
       return false;
     }
   }

onnxruntime/core/providers/coreml/builders/op_builder_factory.cc

@@ -31,7 +31,6 @@ static OpBuilderRegistrations CreateOpBuilderRegistrations() {
   CreateUnaryOpBuilder("Round", op_registrations);
   CreateUnaryOpBuilder("Sqrt", op_registrations);
   CreateUnaryOpBuilder("Exp", op_registrations);
-  CreateUnaryOpBuilder("Log", op_registrations);
 
   // Binary elementwise ops
   CreateBinaryOpBuilder("Add", op_registrations);

tools/ci_build/github/apple/coreml_supported_mlprogram_ops.md

@@ -25,7 +25,6 @@ Keep in sync with doco generated from /docs/execution-providers/CoreML-Execution
 |ai.onnx:InstanceNormalization||
 |ai.onnx:LayerNormalization||
 |ai.onnx:LeakyRelu||
-|ai.onnx:Log||
 |ai.onnx:MatMul|Only support for transA == 0, alpha == 1.0 and beta == 1.0 is currently implemented.|
 |ai.onnx:MaxPool|Only 2D Pool is supported currently. 3D and 5D support can be added if needed.|
 |ai.onnx:Max||