tflite build changes

.gitignore

@@ -16,7 +16,7 @@ venv*/
 *.tar.gz
 /VARIANT
 
-# Docs API reference 
+# Docs API reference
 docs/api_reference.md
 
 ### Cmake auto tools
@@ -137,4 +137,8 @@ dkms.conf
 .idea_modules/
 
 # docs site
-site/
+site/
+
+# docker remnants
+*.iid
+*.cid

CMakeLists.txt

@@ -138,14 +138,25 @@ ENDIF()
 #----------------------------------------------------------------------------------------------
 
 IF(BUILD_TFLITE)
-    FIND_LIBRARY(TFLITE_LIBRARIES_1 NAMES tensorflow-lite
+    FIND_LIBRARY(TFLITE_LIBRARIES_1 NAMES tensorflowlite
             PATHS ${depsAbs}/libtensorflow-lite/lib)
-    FIND_LIBRARY(TFLITE_LIBRARIES_2 NAMES benchmark-lib.a
+    IF (${DEVICE} STREQUAL "gpu")
+        FIND_LIBRARY(TFLITE_LIBRARIES_2 NAMES tensorflowlite_gpu_delegate
             PATHS ${depsAbs}/libtensorflow-lite/lib)
-    SET(TFLITE_LIBRARIES ${TFLITE_LIBRARIES_1} ${TFLITE_LIBRARIES_2})
-    MESSAGE(STATUS "Found TensorFlow Lite Libraries: \"${TFLITE_LIBRARIES}\")")
+        IF (NOT APPLE)
+	    FIND_LIBRARY(OPENGL_LIBRARIES NAMES GL
+		PATHS /usr/lib/${MACH}-linux-gnu)
+	    FIND_LIBRARY(EGL_LIBRARIES NAMES EGL
+		PATHS /usr/lib/${MACH}-linux-gnu)
+        ELSE()
+		MESSAGE(FATAL_ERROR "Build for TensorFlow Lite GPU backend on Apple machines.")
+        ENDIF()
+    ENDIF()
+    SET(TFLITE_LIBRARIES ${TFLITE_LIBRARIES_1} ${TFLITE_LIBRARIES_2} ${OPENGL_LIBRARIES} ${EGL_LIBRARIES})
     IF (NOT TFLITE_LIBRARIES)
         MESSAGE(FATAL_ERROR "Could not find TensorFlow Lite")
+    ELSE()
+        MESSAGE(STATUS "Found TensorFlow Lite Libraries: \"${TFLITE_LIBRARIES}\")")
     ENDIF()
     IF (${DEVICE} STREQUAL "gpu")
         ADD_DEFINITIONS(-DRAI_TFLITE_USE_CUDA)
@@ -202,6 +213,7 @@ ENDIF()
 
 ADD_SUBDIRECTORY(src)
 ADD_SUBDIRECTORY(tests/module)
+
 ADD_LIBRARY(redisai SHARED $<TARGET_OBJECTS:redisai_obj>)
 
 TARGET_LINK_LIBRARIES(redisai ${CMAKE_DL_LIBS})
@@ -322,4 +334,4 @@ if(PACKAGE_UNIT_TESTS)
     enable_testing()
     include(GoogleTest)
     add_subdirectory(tests/unit)
-endif()
+endif()

README.md

@@ -69,7 +69,7 @@ redis-cli
 
 ## Building
 
-You should obtain the module's source code and submodule using git like so: 
+You should obtain the module's source code and submodule using git like so:
 
 ```sh
 git clone --recursive https://github.com/RedisAI/RedisAI
@@ -96,6 +96,8 @@ ALL=1 make -C opt clean build
 
 Note: in order to use the PyTorch backend on Linux, at least `gcc 4.9.2` is required.
 
+[See this document](docs/developer-backends.md) for building AI backends.
+
 ### Running the server
 
 You will need a redis-server version 5.0.7 or greater. This should be

docs/developer-backends.md

@@ -0,0 +1,19 @@
+# RedisAI dependency builds
+
+Platform dependency build systems are located in this folder. Dependencies are to be pre-built, and published to S3. To do so, they rely *(ultimately)* on running **make build publish** in a given directory. The goal is for this to be true on all target platforms (x86_64, arm64), though at this time it's only true for: tensorflowlite.
+
+## Background
+
+Items are built in docker images, for the target platform whenever possible. If needed (i.e a future planned MacOS build) items are built on the dedicated hardware. There are design wrinkles to each build. Though the ideal is to build a base docker (see the [automata repository](https://github.com/redislabsmodules/automata). That base docker is then used as the base build system injector for the dependency itself.  A docker image is built from the base docker, accepting externalized variables such as the dependency version. Compilation of external requirements takes place in a build file, mounted inside the docker image.
+
+Ideally a per-platform Docker file (i.e Dockerfile.x64, Dockerfile.arm) will exist in the underlying folder, assuming building within a docker is tenable.
+
+--------------
+
+## tensorflowlite (tflite)
+
+### arm64
+
+The arm build of tflite currently occurs on **jetson arm devices** only, as portions of the root filesystem of the Jetson device are mounted during the build. Given the symlinks that exist on the device between things in /usr/lib to /etc/alternatives, and in turn to /usr/local/cuda, which is itself a symlink to /usr/local/cuda-10.2, this is the current philosophy.
+
+WThe *build_arm* target in the [Makefile](Makefile) describes the process in detail. The code to build the base docker build image can be found in the [automata repository](https://github.com/RedisLabsModules/automata/tree/master/dockers/buildsystem/bazelbuilder). The *bazelbuilder* image is published to the [redisfab dockerhub repositories](https://hub.docker.com/r/redisfab/).

docs/developer.md

@@ -106,7 +106,7 @@ Within the `backends` folder you will find the implementations code required to
 * **ONNX**: `onnxruntime.h` and `onnxruntime.c` exporting the functions to to register the ONNXRuntime backend
 
 ## Building and Testing
-You can compile and build the module from its source code - refer to the [Building and Running section](quickstart.md#building-and-running) of the Quickstart page for instructions on how to do that.
+You can compile and build the module from its source code - refer to the [Building and Running section](quickstart.md#building-and-running) of the Quickstart page for instructions on how to do that, or view the  detailed instructions on [building backends](developer-backends.md).
 
 **Running Tests**
 

get_deps.sh

@@ -145,7 +145,7 @@ fi # WITH_TF
 
 ################################################################################# LIBTFLITE
 
-TFLITE_VERSION="2.0.0"
+TFLITE_VERSION="2.4.1"
 
 if [[ $WITH_TFLITE != 0 ]]; then
 	[[ $FORCE == 1 ]] && rm -rf $LIBTFLITE
@@ -156,26 +156,24 @@ if [[ $WITH_TFLITE != 0 ]]; then
 		LIBTF_URL_BASE=https://s3.amazonaws.com/redismodules/tensorflow
 		if [[ $OS == linux ]]; then
 			TFLITE_OS="linux"
-			# if [[ $GPU != 1 ]]; then
-			# 	TFLITE_BUILD="cpu"
-			# else
-			# 	TFLITE_BUILD="gpu"
-			# fi
+			 if [[ $GPU != 1 ]]; then
+			 	TFLITE_PLATFORM="cpu"
+			 else
+			 	TFLITE_PLATFORM="cuda"
+			 fi
 
 			if [[ $ARCH == x64 ]]; then
 				TFLITE_ARCH=x86_64
 			elif [[ $ARCH == arm64v8 ]]; then
 				TFLITE_ARCH=arm64
-			elif [[ $ARCH == arm32v7 ]]; then
-				TFLITE_ARCH=arm
 			fi
 		elif [[ $OS == macos ]]; then
 			TFLITE_OS=darwin
 			# TFLITE_BUILD=cpu
 			TFLITE_ARCH=x86_64
 		fi
 
-		LIBTFLITE_ARCHIVE=libtensorflowlite-${TFLITE_OS}-${TFLITE_ARCH}-${TFLITE_VERSION}.tar.gz
+		LIBTFLITE_ARCHIVE=libtensorflowlite-${TFLITE_OS}-${TFLITE_PLATFORM}-${TFLITE_ARCH}-${TFLITE_VERSION}.tar.gz
 
 		[[ ! -f $LIBTFLITE_ARCHIVE || $FORCE == 1 ]] && wget -q $LIBTF_URL_BASE/$LIBTFLITE_ARCHIVE
 

opt/Makefile

@@ -135,7 +135,8 @@ CMAKE_FLAGS += \
 	-DUSE_COVERAGE=$(USE_COVERAGE) \
 	-DUSE_PROFILE=$(USE_PROFILE) \
 	-DREDISAI_GIT_SHA=\"$(GIT_SHA)\" \
-	-DDEVICE=$(DEVICE)
+	-DDEVICE=$(DEVICE) \
+	-DMACH=$(shell uname -m)
 
 ifeq ($(WITH_TF),0)
 CMAKE_FLAGS += -DBUILD_TF=off

opt/build/tflite/Dockerfile.x64

@@ -1,29 +1,34 @@
+ARG BAZEL_VERSION=3.1.0
+ARG TFLITE_ARCH=x86_64
 
-ARG OS=debian:buster
+ARG OS=redisfab/ubuntu1804-${TFLITE_ARCH}-bazel${BAZEL_VERSION}
 
-ARG FTLITE_VER=2.0.0
+# cuda | cpu
+ARG REDISAI_PLATFORM=cuda
+
+ARG TFLITE_VERSION=2.4.0
 
 #----------------------------------------------------------------------------------------------
 FROM ${OS}
 
 ARG FTLITE_VER
-
-WORKDIR /build
-
-RUN set -e ;\
-	apt-get -qq update ;\
-	apt-get -q install -y git ca-certificates curl wget unzip python3 ;\
-	apt-get -q install -y git build-essential zlib1g-dev
-
-RUN git clone --single-branch --branch v${FTLITE_VER} --depth 1 https://github.com/tensorflow/tensorflow.git
-
-ADD ./opt/build/tflite/build /build/
-ADD ./opt/readies/ /build/readies/
-ADD ./opt/build/tflite/collect.py /build/
-
-RUN set -e ;\
-	cd tensorflow/tensorflow/lite/tools/make ;\
-	./download_dependencies.sh ;\
-	./build_lib.sh
-
-RUN ./collect.py --version ${FTLITE_VER} --dest /build/dest
+ARG TFLITE_VERSION
+ARG TFLITE_ARCH
+ARG REDISAI_PLATFORM
+
+ADD ./opt/build/tflite /tflite
+
+RUN apt-get -qq update && apt-get install -yqq python3
+RUN apt-get install -qqy git \
+            unzip \
+            wget \
+            curl \
+            build-essential \
+            zlib1g-dev \
+            libegl1-mesa-dev \
+            libgles2-mesa-dev \
+            python3-distutils \
+            python3-numpy
+RUN ln -s /usr/bin/python3 /usr/bin/python
+WORKDIR /tflite
+RUN bash build.sh ${TFLITE_ARCH} ${TFLITE_VERSION} ${REDISAI_PLATFORM}