Adds ONNX Optimizer, Version Converter and IR.

.travis.yml

@@ -708,6 +708,11 @@ matrix:
         env: PROJ=ale OS=macosx-x86_64
         install: true
         script: ./ci/install-travis.sh
+      - os: osx
+        osx_image: xcode8.3
+        env: PROJ=onnx OS=macosx-x86_64
+        install: true
+        script: ./ci/install-travis.sh
       - os: osx
         osx_image: xcode7.3
         env: PROJ=liquidfun OS=macosx-x86_64

onnx/README.md

@@ -35,15 +35,15 @@ We can use [Maven 3](http://maven.apache.org/) to download and install automatic
     <modelVersion>4.0.0</modelVersion>
     <groupId>org.bytedeco.javacpp-presets.onnx</groupId>
     <artifactId>loadmodel</artifactId>
-    <version>1.4.3</version>
+    <version>1.4.4-SNAPSHOT</version>
     <properties>
         <exec.mainClass>LoadModel</exec.mainClass>
     </properties>
     <dependencies>
         <dependency>
             <groupId>org.bytedeco.javacpp-presets</groupId>
             <artifactId>onnx-platform</artifactId>
-            <version>1.3.0-1.4.3</version>
+            <version>1.3.0-1.4.4-SNAPSHOT</version>
         </dependency>
     </dependencies>
 </project>
@@ -65,6 +65,17 @@ public class LoadModel {
         ModelProto model = new ModelProto();
         ParseProtoFromBytes(model, new BytePointer(bytes), bytes.length);
 
+        check_model(model);
+
+        InferShapes(model);
+
+        StringVector passes = new StringVector("eliminate_nop_transpose", "eliminate_nop_pad", "fuse_consecutive_transposes", "fuse_transpose_into_gemm");
+        Optimize(model, passes);
+
+        check_model(model);
+
+        ConvertVersion(model, 8);
+
         System.out.println(model.graph().input_size());
     }
 }

onnx/cppbuild.sh

@@ -43,21 +43,26 @@ make install
 cd ../onnx-$ONNX
 rm -df third_party/pybind11
 ln -sf $INSTALL_PATH/pybind11-$PYBIND third_party/pybind11
+# work around issue in Xcode's version of Clang
+sedinplace 's/const std::string /std::string /g' onnx/defs/schema.h
 
 #to build with "Traditional ML" support. Untested.
 export ONNX_ML=1
 export CMAKE_BUILD_DIR=.setuptools-cmake-build/
 export CMAKE_ARGS=-DBUILD_SHARED_LIBS=ON
 python3 setup.py --quiet build
 
-mkdir -p ../include/onnx ../include/onnx/common ../include/onnx/defs ../include/onnx/optimizer/ ../include/onnx/version_converter
+mkdir -p ../include/onnx ../include/onnx/common ../include/onnx/defs ../include/onnx/optimizer/ ../include/onnx/optimizer/passes ../include/onnx/version_converter ../include/onnx/version_converter/adapters ../include/onnx/shape_inference
 
 cp onnx/*.h ../include/onnx/
 cp onnx/common/*.h ../include/onnx/common/
 cp onnx/defs/*.h ../include/onnx/defs/
 cp onnx/optimizer/*.h ../include/onnx/optimizer/
+cp onnx/optimizer/passes/*.h ../include/onnx/optimizer/passes/
 cp onnx/version_converter/*.h ../include/onnx/version_converter/
+cp onnx/version_converter/adapters/*.h ../include/onnx/version_converter/adapters/
+cp onnx/shape_inference/*.h ../include/onnx/shape_inference/
 cp $CMAKE_BUILD_DIR/onnx/*.h ../include/onnx/
-cp $CMAKE_BUILD_DIR/*.so ../lib
+cp $CMAKE_BUILD_DIR/libonnx* ../lib
 
 cd ../..

onnx/platform/pom.xml

@@ -31,6 +31,12 @@
       <version>${project.version}</version>
       <classifier>${javacpp.platform.linux-x86_64}</classifier>
     </dependency>
+    <dependency>
+      <groupId>${project.groupId}</groupId>
+      <artifactId>${javacpp.moduleId}</artifactId>
+      <version>${project.version}</version>
+      <classifier>${javacpp.platform.macosx-x86_64}</classifier>
+    </dependency>
   </dependencies>
 
   <build>
@@ -43,7 +49,7 @@
             <configuration>
               <archive>
                 <manifestEntries>
-                  <Class-Path>${javacpp.moduleId}.jar ${javacpp.moduleId}-linux-x86_64.jar</Class-Path>
+                  <Class-Path>${javacpp.moduleId}.jar ${javacpp.moduleId}-linux-x86_64.jar ${javacpp.moduleId}-macosx-x86_64.jar</Class-Path>
                 </manifestEntries>
               </archive>
             </configuration>