How to build the the project for intel x86 and x86_64 instead of armeabi v7?

[ghost]

Hi,
I want to build the project for intel x86 emulator instead of armeabi v7. Since app crashes with intel x86 CPU emulator.

I am using Ubuntu 14.04,
Android Studio 2.0
NDK 10re

Please help me on this issue.

[ghost]

I tried by changing Makefile like this

build:
ndk-build
install:
cp -r libs/armeabi-v7a/.so ../app/src/main/jniLibs/armeabi-v7a/
cp -r libs/x86/.so ../app/src/main/jniLibs/x86/
cp -r libs/x86_64/*.so ../app/src/main/jniLibs/x86_64/
clean:
rm -r obj
rm -r libs`

and changing Application.mk file as

APP_ABI := armeabi-v7a x86 x86_64
APP_STL := gnustl_static
APP_PLATFORM := android-21
NDK_TOOLCHAIN_VERSION=4.9`

then I got this error in the make

command kaushalya@kaushalya-HP-350-G1:/TensorFlowAndroidDemo-master/jni-build$ make
ndk-build
Android NDK: WARNING:jni/Android.mk:tensorflow_demo: non-system libraries in linker flags: jni/libs/armeabi-v7a/libandroid_tensorflow_lib.a jni/libs/armeabi-v7a/libre2.a jni/libs/armeabi-v7a/libprotos_all_cc.a jni/libs/armeabi-v7a/libprotobuf.a jni/libs/armeabi-v7a/libprotobuf_lite.a /home/kaushalya/android-ndk-r10e/sources/cxx-stl/gnu-libstdc++/4.9/libs/armeabi-v7a/libgnustl_static.a /home/kaushalya/android-ndk-r10e/sources/cxx-stl/gnu-libstdc++/4.9/libs/armeabi-v7a/libsupc++.a
Android NDK: This is likely to result in incorrect builds. Try using LOCAL_STATIC_LIBRARIES
Android NDK: or LOCAL_SHARED_LIBRARIES instead to list the library dependencies of the
Android NDK: current module
Android NDK: WARNING:jni/Android.mk:tensorflow_demo: non-system libraries in linker flags: jni/libs/x86/libandroid_tensorflow_lib.a jni/libs/x86/libre2.a jni/libs/x86/libprotos_all_cc.a jni/libs/x86/libprotobuf.a jni/libs/x86/libprotobuf_lite.a /home/kaushalya/android-ndk-r10e/sources/cxx-stl/gnu-libstdc++/4.9/libs/x86/libgnustl_static.a /home/kaushalya/android-ndk-r10e/sources/cxx-stl/gnu-libstdc++/4.9/libs/x86/libsupc++.a
Android NDK: This is likely to result in incorrect builds. Try using LOCAL_STATIC_LIBRARIES
Android NDK: or LOCAL_SHARED_LIBRARIES instead to list the library dependencies of the
Android NDK: current module
Android NDK: WARNING:jni/Android.mk:tensorflow_demo: non-system libraries in linker flags: jni/libs/x86_64/libandroid_tensorflow_lib.a jni/libs/x86_64/libre2.a jni/libs/x86_64/libprotos_all_cc.a jni/libs/x86_64/libprotobuf.a jni/libs/x86_64/libprotobuf_lite.a /home/kaushalya/android-ndk-r10e/sources/cxx-stl/gnu-libstdc++/4.9/libs/x86_64/libgnustl_static.a /home/kaushalya/android-ndk-r10e/sources/cxx-stl/gnu-libstdc++/4.9/libs/x86_64/libsupc++.a
Android NDK: This is likely to result in incorrect builds. Try using LOCAL_STATIC_LIBRARIES
Android NDK: or LOCAL_SHARED_LIBRARIES instead to list the library dependencies of the
Android NDK: current module
make[1]: Entering directory /home/kaushalya/TensorFlowAndroidDemo-master/jni-build' [armeabi-v7a] Compile++ arm : tensorflow_demo <= tensorflow_jni.cc [armeabi-v7a] Compile++ arm : tensorflow_demo <= imageutils_jni.cc [armeabi-v7a] Compile++ arm : tensorflow_demo <= jni_utils.cc [armeabi-v7a] Compile++ arm : tensorflow_demo <= rgb2yuv.cc [armeabi-v7a] Compile++ arm : tensorflow_demo <= yuv2rgb.cc [armeabi-v7a] SharedLibrary : libtensorflow_demo.so [armeabi-v7a] Install : libtensorflow_demo.so => libs/armeabi-v7a/libtensorflow_demo.so [x86] Compile++ : tensorflow_demo <= tensorflow_jni.cc i686-linux-android-g++: error: unrecognized command line option '-mfpu=vfpv3-d16' i686-linux-android-g++: error: unrecognized command line option '-mfloat-abi=softfp' i686-linux-android-g++: error: unrecognized command line option '-mfpu=neon' make[1]: *** [obj/local/x86/objs/tensorflow_demo/./tensorflow_jni.o] Error 1 make[1]: Leaving directory/home/kaushalya/TensorFlowAndroidDemo-master/jni-build'
make: *** [build] Error 2
kaushalya@kaushalya-HP-350-G1:/TensorFlowAndroidDemo-master/jni-build$

Please help me, you are the one who can help me on this Miyoshi

[miyosuda]

I've replied this at TensorFlow issue thread
tensorflow/tensorflow#2035 (comment)

[ghost]

Can you please answer my last 2 comments before thread closes in tensorflow#issue2035_comment0 and tensorflow#issue2035_comment1 in this thread.