Add Tensorflow Lite Demo

The demo shows how to run the unmodified Tensorflow Lite on Occlum.

demo/tensorflow_lite/.gitignore

@@ -0,0 +1,7 @@
+tensorflow_src/
+deps/
+models/
+testdata/
+label_image
+benchmark_model
+minimal

demo/tensorflow_lite/README.md

@@ -0,0 +1,27 @@
+# Use Tensorflow Lite in SGX with Occlum
+
+Step 1: Download Tensorflow, build Tensorflow Lite, and download models
+```
+./download_and_build_tflite.sh
+```
+When completed, the resulting Tensorflow can be found in `tensorflow_src` directory, the Tensorflow Lite Model can be found in `models` directory
+
+Step 2.1: To run TensorFlow Lite inference demo in Occlum, run
+```
+./run_tflite_in_occlum.sh demo
+```
+
+Step 2.2: To run TensorFlow Lite inference benchmark in Occlum, run
+```
+./run_tflite_in_occlum.sh benchmark
+```
+
+Step 3.1: To run TensorFlow Lite inference demo in Linux, run
+```
+./run_tflite_in_linux.sh demo
+```
+
+Step 3.2: To run TensorFlow Lite inference benchmark in Linux, run
+```
+./run_tflite_in_linux.sh benchmark
+```

demo/tensorflow_lite/download_and_build_tflite.sh

@@ -0,0 +1,29 @@
+#!/bin/bash
+set -e
+SRC_DIR="tensorflow_src"
+
+# 1. Install dependent zlib
+mkdir -p deps/zlib
+pushd deps/zlib
+git clone https://github.com/madler/zlib .
+CC=occlum-gcc CXX=occlum-g++ ./configure --prefix=/usr/local/occlum/x86_64-linux-musl
+make
+sudo make install
+popd
+
+# 2. Build tensorflow lite and the demo program
+mkdir -p $SRC_DIR
+pushd $SRC_DIR
+git clone https://github.com/tensorflow/tensorflow .
+git checkout tags/v1.15.0-rc0 -b v1.15.0-rc0
+git apply ../patch/fix-tflite-Makefile-v1.15.0-rc0.diff
+./tensorflow/lite/tools/make/download_dependencies.sh
+make -j 3 -f tensorflow/lite/tools/make/Makefile
+popd
+
+# 3. Download tflite model and labels
+mkdir models
+curl https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz | tar xzv -C ./models
+curl https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_1.0_224_frozen.tgz  | tar xzv -C ./models  mobilenet_v1_1.0_224/labels.txt
+mv ./models/mobilenet_v1_1.0_224/labels.txt ./models/labels.txt
+rm -rf ./models/mobilenet_v1_1.0_224

demo/tensorflow_lite/patch/fix-tflite-Makefile-v1.15.0-rc0.diff

@@ -0,0 +1,99 @@
+diff --git a/tensorflow/lite/tools/make/Makefile b/tensorflow/lite/tools/make/Makefile
+index 73c50d3..3cef7fa 100644
+--- a/tensorflow/lite/tools/make/Makefile
++++ b/tensorflow/lite/tools/make/Makefile
+@@ -42,7 +42,7 @@ INCLUDES := \
+ -I$(OBJDIR)
+ # This is at the end so any globally-installed frameworks like protobuf don't
+ # override local versions in the source tree.
+-INCLUDES += -I/usr/local/include
++INCLUDES += -I/usr/local/occlum/x86_64-linux-musl/include
+ 
+ # These are the default libraries needed, but they can be added to or
+ # overridden by the platform-specific settings in target makefiles.
+@@ -59,7 +59,8 @@ CXXFLAGS := -O3 -DNDEBUG -fPIC
+ CXXFLAGS += $(EXTRA_CXXFLAGS)
+ CFLAGS := ${CXXFLAGS}
+ CXXFLAGS += --std=c++11
+-LDOPTS := -L/usr/local/lib
++LDOPTS := -L/usr/local/occlum/x86_64-linux-musl/lib
++LDFLAGS := -pie $(LDOPTS)
+ ARFLAGS := -r
+ TARGET_TOOLCHAIN_PREFIX :=
+ CC_PREFIX :=
+@@ -80,6 +81,12 @@ BENCHMARK_BINARY_NAME := benchmark_model
+ MINIMAL_SRCS := \
+ 	tensorflow/lite/examples/minimal/minimal.cc
+ 
++# Add label image example.
++LABEL_IMAGE_SRCS := \
++tensorflow/lite/tools/evaluation/utils.cc \
++tensorflow/lite/examples/label_image/label_image.cc \
++tensorflow/lite/examples/label_image/bitmap_helpers.cc
++
+ # What sources we want to compile, must be kept in sync with the main Bazel
+ # build files.
+ 
+@@ -133,7 +140,8 @@ $(wildcard tensorflow/lite/*/*/*test.cc) \
+ $(wildcard tensorflow/lite/*/*/*/*test.cc) \
+ $(wildcard tensorflow/lite/kernels/*test_main.cc) \
+ $(wildcard tensorflow/lite/kernels/*test_util.cc) \
+-$(MINIMAL_SRCS)
++$(MINIMAL_SRCS) \
++$(LABEL_IMAGE_SRCS)
+ 
+ BUILD_WITH_MMAP ?= true
+ ifeq ($(BUILD_TYPE),micro)
+@@ -209,6 +217,7 @@ include $(wildcard $(MAKEFILE_DIR)/targets/*_makefile.inc)
+ 
+ ALL_SRCS := \
+ 	$(MINIMAL_SRCS) \
++	$(LABEL_IMAGE_SRCS) \
+ 	$(PROFILER_SRCS) \
+ 	$(PROFILER_SUMMARIZER_SRCS) \
+ 	$(TF_LITE_CC_SRCS) \
+@@ -225,14 +234,18 @@ LIB_PATH := $(LIBDIR)$(LIB_NAME)
+ BENCHMARK_LIB := $(LIBDIR)$(BENCHMARK_LIB_NAME)
+ BENCHMARK_BINARY := $(BINDIR)$(BENCHMARK_BINARY_NAME)
+ MINIMAL_BINARY := $(BINDIR)minimal
++LABEL_IMAGE_BINARY := $(BINDIR)label_image
+ 
+-CXX := $(CC_PREFIX)${TARGET_TOOLCHAIN_PREFIX}g++
+-CC := $(CC_PREFIX)${TARGET_TOOLCHAIN_PREFIX}gcc
++CXX := occlum-g++
++CC := occlum-gcc
+ AR := $(CC_PREFIX)${TARGET_TOOLCHAIN_PREFIX}ar
+ 
+ MINIMAL_OBJS := $(addprefix $(OBJDIR), \
+ $(patsubst %.cc,%.o,$(patsubst %.c,%.o,$(MINIMAL_SRCS))))
+ 
++LABEL_IMAGE_OBJS := $(addprefix $(OBJDIR), \
++$(patsubst %.cc,%.o,$(patsubst %.c,%.o,$(LABEL_IMAGE_SRCS))))
++
+ LIB_OBJS := $(addprefix $(OBJDIR), \
+ $(patsubst %.cc,%.o,$(patsubst %.c,%.o,$(patsubst %.cpp,%.o,$(TF_LITE_CC_SRCS)))))
+ 
+@@ -252,7 +265,7 @@ $(OBJDIR)%.o: %.cpp
+ 	$(CXX) $(CXXFLAGS) $(INCLUDES) -c $< -o $@
+ 
+ # The target that's compiled if there's no command-line arguments.
+-all: $(LIB_PATH)  $(MINIMAL_BINARY) $(BENCHMARK_BINARY)
++all: $(LIB_PATH)  $(MINIMAL_BINARY) $(LABEL_IMAGE_BINARY) $(BENCHMARK_BINARY)
+ 
+ # The target that's compiled for micro-controllers
+ micro: $(LIB_PATH)
+@@ -276,6 +289,14 @@ $(MINIMAL_BINARY): $(MINIMAL_OBJS) $(LIB_PATH)
+ 
+ minimal: $(MINIMAL_BINARY)
+ 
++$(LABEL_IMAGE_BINARY): $(LIB_PATH) $(LABEL_IMAGE_OBJS)
++	@mkdir -p $(dir $@)
++	$(CXX) $(CXXFLAGS) $(INCLUDES) \
++	-o $(LABEL_IMAGE_BINARY) $(LABEL_IMAGE_OBJS) \
++	$(LIBFLAGS) $(LIB_PATH) $(LDFLAGS) $(LIBS)
++
++label_image: $(LABEL_IMAGE_BINARY)
++
+ $(BENCHMARK_LIB) : $(LIB_PATH) $(BENCHMARK_OBJS)
+ 	@mkdir -p $(dir $@)
+ 	$(AR) $(ARFLAGS) $(BENCHMARK_LIB) $(LIB_OBJS) $(BENCHMARK_OBJS)

demo/tensorflow_lite/run_tflite_in_linux.sh

@@ -0,0 +1,41 @@
+#!/bin/bash
+export LD_LIBRARY_PATH=/usr/local/occlum/x86_64-linux-musl/lib:$LD_LIBRARY_PATH
+set -e
+
+show_usage() {
+    echo
+    echo "Usage: $0 demo/benchmark"
+    echo
+}
+
+copy_files() {
+    cp -f tensorflow_src/tensorflow/lite/tools/make/gen/linux_x86_64/bin/* .
+    cp -rf tensorflow_src/tensorflow/lite/examples/label_image/testdata .
+}
+
+run_demo() {
+    copy_files
+    ./label_image \
+        --tflite_model ./models/mobilenet_v1_1.0_224.tflite \
+        --labels ./models/labels.txt \
+        --image ./testdata/grace_hopper.bmp
+}
+
+run_benchmark() {
+    copy_files
+    ./benchmark_model \
+        --graph=./models/mobilenet_v1_1.0_224.tflite \
+        --warmup_runs=5
+}
+
+bin=$1
+case "$bin" in
+    demo)
+        run_demo
+        ;;
+    benchmark)
+        run_benchmark
+        ;;
+    *)
+        show_usage
+esac

demo/tensorflow_lite/run_tflite_in_occlum.sh

@@ -0,0 +1,52 @@
+#!/bin/bash
+set -e
+
+show_usage() {
+    echo
+    echo "Usage: $0 demo/benchmark"
+    echo
+}
+
+init_workspace() {
+    rm -rf occlum_workspace
+    mkdir occlum_workspace
+    cd occlum_workspace
+    occlum init
+}
+
+build_occlum() {
+    cp ../tensorflow_src/tensorflow/lite/tools/make/gen/linux_x86_64/bin/* image/bin
+    cp /usr/local/occlum/x86_64-linux-musl/lib/libz.so.1 image/lib
+    cp -r ../models image
+    cp -r ../tensorflow_src/tensorflow/lite/examples/label_image/testdata image
+    occlum build
+}
+
+run_demo() {
+    init_workspace
+    build_occlum
+    occlum run /bin/label_image \
+        --tflite_model ./models/mobilenet_v1_1.0_224.tflite \
+        --labels ./models/labels.txt \
+        --image ./testdata/grace_hopper.bmp
+}
+
+run_benchmark() {
+    init_workspace
+    build_occlum
+    occlum run /bin/benchmark_model \
+        --graph=./models/mobilenet_v1_1.0_224.tflite \
+        --warmup_runs=5
+}
+
+bin=$1
+case "$bin" in
+    demo)
+        run_demo
+        ;;
+    benchmark)
+        run_benchmark
+        ;;
+    *)
+        show_usage
+esac

etc/template/Occlum.json

@@ -1,11 +1,11 @@
 {
     "vm": {
-        "user_space_size": "128MB"
+        "user_space_size": "256MB"
     },
     "process": {
         "default_stack_size": "4MB",
-        "default_heap_size": "16MB",
-        "default_mmap_size": "32MB"
+        "default_heap_size": "32MB",
+        "default_mmap_size": "80MB"
     },
     "env": [
         "OCCLUM=yes"