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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2018/03/29 19:06:58 UTC
[GitHub] piiswrong closed pull request #10151: WIP Do not merge: Updated to Jetpack 3.2, fix minor wheel issue
piiswrong closed pull request #10151: WIP Do not merge: Updated to Jetpack 3.2, fix minor wheel issue
URL: https://github.com/apache/incubator-mxnet/pull/10151
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:
As this is a foreign pull request (from a fork), the diff is supplied
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diff --git a/ci/docker/Dockerfile.build.jetson b/ci/docker/Dockerfile.build.jetson
index e49b48e7e1c..8b1a275752f 100755
--- a/ci/docker/Dockerfile.build.jetson
+++ b/ci/docker/Dockerfile.build.jetson
@@ -20,7 +20,7 @@
# This script assumes /work/mxnet exists and contains the mxnet code you wish to compile and
# that /work/build exists and is the target for your output.
-FROM nvidia/cuda:8.0-cudnn6-devel as cudabuilder
+FROM nvidia/cuda:9.0-cudnn7-devel as cudabuilder
FROM dockcross/linux-arm64
@@ -46,25 +46,25 @@ ENV PATH $PATH:/usr/local/cuda/bin
ENV TARGET_ARCH aarch64
ENV TARGET_OS linux
-# Install ARM depedencies based on Jetpack 3.1
-RUN JETPACK_DOWNLOAD_PREFIX=http://developer.download.nvidia.com/devzone/devcenter/mobile/jetpack_l4t/013/linux-x64 && \
- ARM_CUDA_INSTALLER_PACKAGE=cuda-repo-l4t-8-0-local_8.0.84-1_arm64.deb && \
- ARM_CUDNN_INSTALLER_PACKAGE=libcudnn6_6.0.21-1+cuda8.0_arm64.deb && \
- ARM_CUDNN_DEV_INSTALLER_PACKAGE=libcudnn6-dev_6.0.21-1+cuda8.0_arm64.deb && \
+# Install ARM depedencies based on Jetpack 3.2
+RUN JETPACK_DOWNLOAD_PREFIX=http://developer.download.nvidia.com/devzone/devcenter/mobile/jetpack_l4t/3.2GA/m892ki/JetPackL4T_32_b196/ && \
+ ARM_CUDA_INSTALLER_PACKAGE=cuda-repo-l4t-9-0-local_9.0.252-1_arm64.deb && \
+ ARM_CUDNN_INSTALLER_PACKAGE=libcudnn7_7.0.5.13-1+cuda9.0_arm64.deb && \
+ ARM_CUDNN_DEV_INSTALLER_PACKAGE=libcudnn7-dev_7.0.5.13-1+cuda9.0_arm64.deb && \
wget -nv $JETPACK_DOWNLOAD_PREFIX/$ARM_CUDA_INSTALLER_PACKAGE && \
wget -nv $JETPACK_DOWNLOAD_PREFIX/$ARM_CUDNN_INSTALLER_PACKAGE && \
wget -nv $JETPACK_DOWNLOAD_PREFIX/$ARM_CUDNN_DEV_INSTALLER_PACKAGE && \
dpkg -i $ARM_CUDA_INSTALLER_PACKAGE && \
+ apt-key add /var/cuda-repo-9-0-local/7fa2af80.pub && \
dpkg -i $ARM_CUDNN_INSTALLER_PACKAGE && \
dpkg -i $ARM_CUDNN_DEV_INSTALLER_PACKAGE && \
apt update -y && \
- apt install -y unzip cuda-cudart-cross-aarch64-8-0 cuda-cublas-cross-aarch64-8-0 \
- cuda-nvml-cross-aarch64-8-0 cuda-nvrtc-cross-aarch64-8-0 cuda-cufft-cross-aarch64-8-0 \
- cuda-curand-cross-aarch64-8-0 cuda-cusolver-cross-aarch64-8-0 cuda-cusparse-cross-aarch64-8-0 \
- cuda-misc-headers-cross-aarch64-8-0 cuda-npp-cross-aarch64-8-0 libcudnn6 && \
- cp /usr/local/cuda-8.0/targets/aarch64-linux/lib/*.so /usr/local/cuda/lib64/ && \
- cp /usr/local/cuda-8.0/targets/aarch64-linux/lib/stubs/*.so /usr/local/cuda/lib64/stubs/ && \
- cp -r /usr/local/cuda-8.0/targets/aarch64-linux/include/ /usr/local/cuda/include/ && \
+ apt install -y unzip cuda-cudart-dev-9-0 cuda-cublas-9-0 cuda-nvml-dev-9-0 \
+ cuda-nvrtc-dev-9-0 cuda-cufft-dev-9-0 cuda-curand-dev-9-0 cuda-cusolver-9-0 \
+ cuda-cusparse-dev-9-0 cuda-misc-headers-9-0 cuda-npp-dev-9-0 libcudnn7 && \
+ cp /usr/local/cuda-9.0/targets/aarch64-linux/lib/*.so /usr/local/cuda/lib64/ && \
+ cp /usr/local/cuda-9.0/targets/aarch64-linux/lib/stubs/*.so /usr/local/cuda/lib64/stubs/ && \
+ cp -r /usr/local/cuda-9.0/targets/aarch64-linux/include/ /usr/local/cuda/include/ && \
rm $ARM_CUDA_INSTALLER_PACKAGE $ARM_CUDNN_INSTALLER_PACKAGE $ARM_CUDNN_DEV_INSTALLER_PACKAGE
WORKDIR /work/mxnet
diff --git a/ci/docker/config/arm.crosscompile.mk b/ci/docker/config/arm.crosscompile.mk
new file mode 100644
index 00000000000..2bca9e396d7
--- /dev/null
+++ b/ci/docker/config/arm.crosscompile.mk
@@ -0,0 +1,161 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+#-------------------------------------------------------------------------------
+# Template configuration for compiling mxnet
+#
+# If you want to change the configuration, please use the following
+# steps. Assume you are on the root directory of mxnet. First copy the this
+# file so that any local changes will be ignored by git
+#
+# $ cp make/config.mk .
+#
+# Next modify the according entries, and then compile by
+#
+# $ make
+#
+# or build in parallel with 8 threads
+#
+# $ make -j8
+#-------------------------------------------------------------------------------
+
+#---------------------
+# We do not assign compilers here. Often when cross-compiling these will already
+# be set correctly.
+#--------------------
+
+export NVCC = nvcc
+
+# whether compile with options for MXNet developer
+DEV = 0
+
+# whether compile with debug
+DEBUG = 0
+
+# whether compiler with profiler
+USE_PROFILER =
+
+# the additional link flags you want to add
+# TODO: Move flags here
+ADD_LDFLAGS=-static-libstdc++
+
+# the additional compile flags you want to add
+ADD_CFLAGS =
+
+#---------------------------------------------
+# matrix computation libraries for CPU/GPU
+#---------------------------------------------
+
+# whether use CUDA during compile
+USE_CUDA = 0
+
+# add the path to CUDA library to link and compile flag
+# if you have already add them to environment variable, leave it as NONE
+# USE_CUDA_PATH = /usr/local/cuda
+USE_CUDA_PATH = NONE
+
+# whether use CuDNN R3 library
+USE_CUDNN = 0
+
+# whether use cuda runtime compiling for writing kernels in native language (i.e. Python)
+USE_NVRTC = 0
+
+# whether use opencv during compilation
+# you can disable it, however, you will not able to use
+# imbin iterator
+USE_OPENCV = 0
+
+# use openmp for parallelization
+USE_OPENMP = 1
+
+# whether use NNPACK library
+USE_NNPACK = 0
+
+# For arm builds we're using openblas
+USE_BLAS = openblas
+
+# whether use lapack during compilation
+# only effective when compiled with blas versions openblas/apple/atlas/mkl
+USE_LAPACK = 1
+
+# path to lapack library in case of a non-standard installation
+USE_LAPACK_PATH =
+
+# add path to intel library, you may need it for MKL, if you did not add the path
+# to environment variable
+USE_INTEL_PATH = NONE
+
+# If use MKL only for BLAS, choose static link automatically to allow python wrapper
+USE_STATIC_MKL = NONE
+ifeq ($(USE_BLAS), mkl)
+USE_STATIC_MKL = 1
+endif
+
+#----------------------------
+# distributed computing
+#----------------------------
+
+# whether or not to enable multi-machine supporting
+USE_DIST_KVSTORE = 0
+
+# whether or not allow to read and write HDFS directly. If yes, then hadoop is
+# required
+USE_HDFS = 0
+
+# path to libjvm.so. required if USE_HDFS=1
+LIBJVM=$(JAVA_HOME)/jre/lib/amd64/server
+
+# whether or not allow to read and write AWS S3 directly. If yes, then
+# libcurl4-openssl-dev is required, it can be installed on Ubuntu by
+# sudo apt-get install -y libcurl4-openssl-dev
+USE_S3 = 0
+
+#----------------------------
+# additional operators
+#----------------------------
+
+# path to folders containing projects specific operators that you don't want to put in src/operators
+EXTRA_OPERATORS =
+
+#----------------------------
+# other features
+#----------------------------
+
+# Create C++ interface package
+USE_CPP_PACKAGE = 0
+
+#----------------------------
+# plugins
+#----------------------------
+
+# whether to use caffe integration. This requires installing caffe.
+# You also need to add CAFFE_PATH/build/lib to your LD_LIBRARY_PATH
+# CAFFE_PATH = $(HOME)/caffe
+# MXNET_PLUGINS += plugin/caffe/caffe.mk
+
+# whether to use torch integration. This requires installing torch.
+# You also need to add TORCH_PATH/install/lib to your LD_LIBRARY_PATH
+# TORCH_PATH = $(HOME)/torch
+# MXNET_PLUGINS += plugin/torch/torch.mk
+
+# WARPCTC_PATH = $(HOME)/warp-ctc
+# MXNET_PLUGINS += plugin/warpctc/warpctc.mk
+
+# whether to use sframe integration. This requires build sframe
+# git@github.com:dato-code/SFrame.git
+# SFRAME_PATH = $(HOME)/SFrame
+# MXNET_PLUGINS += plugin/sframe/plugin.mk
diff --git a/ci/docker/runtime_functions.sh b/ci/docker/runtime_functions.sh
index 39809f28127..95f3a33d859 100755
--- a/ci/docker/runtime_functions.sh
+++ b/ci/docker/runtime_functions.sh
@@ -37,37 +37,31 @@ clean_repo() {
build_jetson() {
set -ex
- pushd .
+ cp ci/docker/config/arm.crosscompile.mk make/config.mk
+ make \
+ USE_OPENCV=0 \
+ USE_SSE=0 \
+ USE_BLAS=openblas \
+ USE_CUDA=1 \
+ USE_CUDNN=1 \
+ ENABLE_CUDA_RTC=0 \
+ USE_NCCL=0 \
+ USE_CUDA_PATH=/usr/local/cuda/ \
+ -j$(nproc)
- #cd /work/mxnet
- #make -j$(nproc) USE_OPENCV=0 USE_BLAS=openblas USE_SSE=0 USE_CUDA=1 USE_CUDNN=1 ENABLE_CUDA_RTC=0 USE_NCCL=0 USE_CUDA_PATH=/usr/local/cuda/
- cd /work/build
- cmake\
- -DUSE_CUDA=OFF\
- -DUSE_OPENCV=OFF\
- -DUSE_OPENMP=ON\
- -DUSE_SIGNAL_HANDLER=ON\
- -DUSE_MKL_IF_AVAILABLE=OFF\
- -DUSE_LAPACK=OFF\
- -DCMAKE_BUILD_TYPE=RelWithDebInfo\
- -G Ninja /work/mxnet
- ninja
export MXNET_LIBRARY_PATH=`pwd`/libmxnet.so
cd /work/mxnet/python
python setup.py bdist_wheel --universal
-
- # Fix pathing issues in the wheel. We need to move libmxnet.so from the data folder to the root
- # of the wheel, then repackage the wheel.
- # Create a temp dir to do the work.
- # TODO: move apt call to install
+ # Fix pathing issues in the wheel. We need to move libmxnet.so from the data folder to the
+ # mxnet folder, then repackage the wheel.
WHEEL=`readlink -f dist/*.whl`
TMPDIR=`mktemp -d`
unzip -d $TMPDIR $WHEEL
rm $WHEEL
cd $TMPDIR
mv *.data/data/mxnet/libmxnet.so mxnet
- zip -r $WHEEL $TMPDIR
+ zip -r $WHEEL .
cp $WHEEL /work/build
rm -rf $TMPDIR
popd
diff --git a/docker_multiarch/Dockerfile.build.jetson b/docker_multiarch/Dockerfile.build.jetson
new file mode 100644
index 00000000000..0a7f8b95caa
--- /dev/null
+++ b/docker_multiarch/Dockerfile.build.jetson
@@ -0,0 +1,93 @@
+# -*- mode: dockerfile -*-
+# dockerfile to build libmxnet.so, and a python wheel for the Jetson TX1/TX2
+
+FROM nvidia/cuda:9.0-cudnn7-devel as cudabuilder
+
+FROM dockcross/linux-arm64
+
+ENV ARCH aarch64
+ENV NVCCFLAGS "-m64"
+ENV CUDA_ARCH "-gencode arch=compute_53,code=sm_53 -gencode arch=compute_62,code=sm_62"
+ENV BUILD_OPTS "USE_OPENCV=0 USE_BLAS=openblas USE_SSE=0 USE_CUDA=1 USE_CUDNN=1 ENABLE_CUDA_RTC=0 USE_NCCL=0 USE_CUDA_PATH=/usr/local/cuda/"
+ENV CC /usr/bin/aarch64-linux-gnu-gcc
+ENV CXX /usr/bin/aarch64-linux-gnu-g++
+ENV FC /usr/bin/aarch64-linux-gnu-gfortran-4.9
+ENV HOSTCC gcc
+
+WORKDIR /work
+
+# Build OpenBLAS
+ADD https://api.github.com/repos/xianyi/OpenBLAS/git/refs/heads/master /tmp/openblas_version.json
+RUN git clone https://github.com/xianyi/OpenBLAS.git && \
+ cd OpenBLAS && \
+ make -j$(nproc) TARGET=ARMV8 && \
+ PREFIX=/usr make install
+
+# Setup CUDA build env (including configuring and copying nvcc)
+COPY --from=cudabuilder /usr/local/cuda /usr/local/cuda
+ENV PATH $PATH:/usr/local/cuda/bin
+ENV TARGET_ARCH aarch64
+ENV TARGET_OS linux
+
+# Install ARM depedencies based on Jetpack 3.2
+RUN JETPACK_DOWNLOAD_PREFIX=http://developer.download.nvidia.com/devzone/devcenter/mobile/jetpack_l4t/3.2GA/m892ki/JetPackL4T_32_b196/ && \
+ ARM_CUDA_INSTALLER_PACKAGE=cuda-repo-l4t-9-0-local_9.0.252-1_arm64.deb && \
+ ARM_CUDNN_INSTALLER_PACKAGE=libcudnn7_7.0.5.13-1+cuda9.0_arm64.deb && \
+ ARM_CUDNN_DEV_INSTALLER_PACKAGE=libcudnn7-dev_7.0.5.13-1+cuda9.0_arm64.deb && \
+ wget -nv $JETPACK_DOWNLOAD_PREFIX/$ARM_CUDA_INSTALLER_PACKAGE && \
+ wget -nv $JETPACK_DOWNLOAD_PREFIX/$ARM_CUDNN_INSTALLER_PACKAGE && \
+ wget -nv $JETPACK_DOWNLOAD_PREFIX/$ARM_CUDNN_DEV_INSTALLER_PACKAGE && \
+ dpkg -i $ARM_CUDA_INSTALLER_PACKAGE && \
+ apt-key add /var/cuda-repo-9-0-local/7fa2af80.pub && \
+ dpkg -i $ARM_CUDNN_INSTALLER_PACKAGE && \
+ dpkg -i $ARM_CUDNN_DEV_INSTALLER_PACKAGE && \
+ apt update -y && \
+ apt install -y unzip cuda-cudart-dev-9-0 cuda-cublas-9-0 cuda-nvml-dev-9-0 \
+ cuda-nvrtc-dev-9-0 cuda-cufft-dev-9-0 cuda-curand-dev-9-0 cuda-cusolver-9-0 \
+ cuda-cusparse-dev-9-0 cuda-misc-headers-9-0 cuda-npp-dev-9-0 libcudnn7 && \
+ cp /usr/local/cuda-9.0/targets/aarch64-linux/lib/* /usr/local/cuda/lib64/ && \
+ cp /usr/local/cuda-9.0/lib64/* /usr/local/cuda/lib64/ && \
+ cp /usr/local/cuda-9.0/targets/aarch64-linux/lib/stubs/*.so /usr/local/cuda/lib64/stubs/ && \
+ cp -r /usr/local/cuda-9.0/targets/aarch64-linux/include/ /usr/local/cuda/include/ && \
+ rm $ARM_CUDA_INSTALLER_PACKAGE $ARM_CUDNN_INSTALLER_PACKAGE $ARM_CUDNN_DEV_INSTALLER_PACKAGE
+
+# Build MXNet
+RUN git clone --recurse https://github.com/apache/incubator-mxnet.git mxnet
+
+WORKDIR /work/mxnet
+
+# Add ARM specific settings
+ADD arm.crosscompile.mk make/config.mk
+
+# Build and link
+RUN make -j$(nproc) $BUILD_OPTS
+
+# Create a binary wheel for easy installation.
+# When using tool.py output will be in the jetson folder.
+# Scp the .whl file to your target device, and install via
+# pip install
+WORKDIR /work/mxnet/python
+RUN python setup.py bdist_wheel --universal
+
+# Copy build artifacts to output folder for tool.py script
+RUN mkdir -p /work/build & cp dist/*.whl /work/build && cp ../lib/* /work/build
+
+# Fix pathing issues in the wheel. We need to move libmxnet.so from the data folder to the root
+# of the wheel, then repackage the wheel.
+# Create a temp dir to do the work.
+WORKDIR /work/build
+RUN apt-get install -y unzip && \
+ mkdir temp && \
+ cp *.whl temp
+
+# Extract the wheel, move the libmxnet.so file, repackage the wheel.
+WORKDIR /work/build/temp
+RUN unzip *.whl && \
+ rm *.whl && \
+ mv *.data/data/mxnet/libmxnet.so mxnet && \
+ zip -r ../temp.zip *
+
+# Replace the existing wheel with our fixed version.
+WORKDIR /work/build
+RUN rm -rf temp && \
+ for f in *.whl; do rm "$f" && mv temp.zip "$f"; done
diff --git a/docker_multiarch/arm.crosscompile.mk b/docker_multiarch/arm.crosscompile.mk
new file mode 100644
index 00000000000..2bca9e396d7
--- /dev/null
+++ b/docker_multiarch/arm.crosscompile.mk
@@ -0,0 +1,161 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+#-------------------------------------------------------------------------------
+# Template configuration for compiling mxnet
+#
+# If you want to change the configuration, please use the following
+# steps. Assume you are on the root directory of mxnet. First copy the this
+# file so that any local changes will be ignored by git
+#
+# $ cp make/config.mk .
+#
+# Next modify the according entries, and then compile by
+#
+# $ make
+#
+# or build in parallel with 8 threads
+#
+# $ make -j8
+#-------------------------------------------------------------------------------
+
+#---------------------
+# We do not assign compilers here. Often when cross-compiling these will already
+# be set correctly.
+#--------------------
+
+export NVCC = nvcc
+
+# whether compile with options for MXNet developer
+DEV = 0
+
+# whether compile with debug
+DEBUG = 0
+
+# whether compiler with profiler
+USE_PROFILER =
+
+# the additional link flags you want to add
+# TODO: Move flags here
+ADD_LDFLAGS=-static-libstdc++
+
+# the additional compile flags you want to add
+ADD_CFLAGS =
+
+#---------------------------------------------
+# matrix computation libraries for CPU/GPU
+#---------------------------------------------
+
+# whether use CUDA during compile
+USE_CUDA = 0
+
+# add the path to CUDA library to link and compile flag
+# if you have already add them to environment variable, leave it as NONE
+# USE_CUDA_PATH = /usr/local/cuda
+USE_CUDA_PATH = NONE
+
+# whether use CuDNN R3 library
+USE_CUDNN = 0
+
+# whether use cuda runtime compiling for writing kernels in native language (i.e. Python)
+USE_NVRTC = 0
+
+# whether use opencv during compilation
+# you can disable it, however, you will not able to use
+# imbin iterator
+USE_OPENCV = 0
+
+# use openmp for parallelization
+USE_OPENMP = 1
+
+# whether use NNPACK library
+USE_NNPACK = 0
+
+# For arm builds we're using openblas
+USE_BLAS = openblas
+
+# whether use lapack during compilation
+# only effective when compiled with blas versions openblas/apple/atlas/mkl
+USE_LAPACK = 1
+
+# path to lapack library in case of a non-standard installation
+USE_LAPACK_PATH =
+
+# add path to intel library, you may need it for MKL, if you did not add the path
+# to environment variable
+USE_INTEL_PATH = NONE
+
+# If use MKL only for BLAS, choose static link automatically to allow python wrapper
+USE_STATIC_MKL = NONE
+ifeq ($(USE_BLAS), mkl)
+USE_STATIC_MKL = 1
+endif
+
+#----------------------------
+# distributed computing
+#----------------------------
+
+# whether or not to enable multi-machine supporting
+USE_DIST_KVSTORE = 0
+
+# whether or not allow to read and write HDFS directly. If yes, then hadoop is
+# required
+USE_HDFS = 0
+
+# path to libjvm.so. required if USE_HDFS=1
+LIBJVM=$(JAVA_HOME)/jre/lib/amd64/server
+
+# whether or not allow to read and write AWS S3 directly. If yes, then
+# libcurl4-openssl-dev is required, it can be installed on Ubuntu by
+# sudo apt-get install -y libcurl4-openssl-dev
+USE_S3 = 0
+
+#----------------------------
+# additional operators
+#----------------------------
+
+# path to folders containing projects specific operators that you don't want to put in src/operators
+EXTRA_OPERATORS =
+
+#----------------------------
+# other features
+#----------------------------
+
+# Create C++ interface package
+USE_CPP_PACKAGE = 0
+
+#----------------------------
+# plugins
+#----------------------------
+
+# whether to use caffe integration. This requires installing caffe.
+# You also need to add CAFFE_PATH/build/lib to your LD_LIBRARY_PATH
+# CAFFE_PATH = $(HOME)/caffe
+# MXNET_PLUGINS += plugin/caffe/caffe.mk
+
+# whether to use torch integration. This requires installing torch.
+# You also need to add TORCH_PATH/install/lib to your LD_LIBRARY_PATH
+# TORCH_PATH = $(HOME)/torch
+# MXNET_PLUGINS += plugin/torch/torch.mk
+
+# WARPCTC_PATH = $(HOME)/warp-ctc
+# MXNET_PLUGINS += plugin/warpctc/warpctc.mk
+
+# whether to use sframe integration. This requires build sframe
+# git@github.com:dato-code/SFrame.git
+# SFRAME_PATH = $(HOME)/SFrame
+# MXNET_PLUGINS += plugin/sframe/plugin.mk
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