Building from source
Konduit Serving sources are hosted on GitHub. If you have git
installed, clone the konduit-serving repository using the git clone
command:
git clone https://github.com/KonduitAI/konduit-serving.git
Python module
To install the konduit
Python module from source, in the python
directory, after installing Cython, run
pip install .
To install all extensions needed for development run
pip install -e '.[tests,codegen,dev]'
The dev
dependencies use black
as a pre-commit hook to lint your code automatically. To activate this functionality, run pre-commit install
on the command line first.
Running tests
Install test dependencies using pip install 'konduit[tests]'
if you want to run tests.
On Windows, compiling the test dependencies requires Visual Studio Build Tools 14.0, which can be installed from here. You may also need to install the Windows 8.1 / 10 SDK. See Python's WindowsCompilers page for details.
The tests also require bert_mrpc_frozen.pb
to be placed in the python/tests
folder. Run the following code in python/tests
:
curl https://deeplearning4jblob.blob.core.windows.net/testresources/bert_mrpc_frozen_v1.zip --output bert.zip
unzip bert.zip
The resulting JAR will be generated at the base of the konduit
project. To copy that JAR into the tests
folder and prepare the documentation (in the docs
folder) to be tested within the testing framework, run:
cd tests
./prepare_doc_tests.sh
The tests are then run with pytest
:
cd python/tests
python -m pytest .
To quickly run unit tests (recommended before each commit), or run the full set of integration tests, you can do:
pytest -m unit
pytest -m integration
To also run documentation tests with doctest
for an individual file, simply run:
python -m doctest ../konduit/server.py -v
JAR
A Java Archive (JAR) file is used to bundle a Java program.
Manual build
Run the following commands in the root directory of konduit-serving:
python build_jar.py --os <your-platform>
where <your-platform>
is picked from windows-x86_64
,linux-x86_64
,linux-x86_64-gpu
, macosx-x86_64
, linux-armhf
and windows-x86_64-gpu
, depending on your operating system and architecture. Use the --help
flag to view the full list of arguments.
An additional --spin
argument provides the option to package Python (python
), PMML (pmml
), both (all
) or neither (minimal
). By default, both Python and PMML are packaged. Python bundling is not encouraged on ARM platforms, and PMML bundling is not encouraged if AGPL licensing is an issue.
Building with the command line interface
Once the konduit
Python package is installed, you have access to a command line interface (CLI) tool called konduit
.
The init
command:
gets the latest Konduit Serving code, then
builds the Java dependencies needed for
konduit
.
It assumes that you have git
installed on your system and that python
is available.
Run:
konduit init --os <your-platform>
where <your-platform>
is picked from windows-x86_64
, linux-x86_64
, linux-x86_64-gpu
, macosx-x86_64
, linux-armhf
and windows-x86_64-gpu
, depending on your operating system and architecture.
An additional --spin
argument provides the option to package Python (python
), PMML (pmml
), both (all
) or neither (minimal
). By default, both Python and PMML are packaged. Python bundling is not encouraged on ARM platforms, and PMML bundling is not encouraged if AGPL licensing is an issue.
To rebuild the Konduit Serving JAR without re-downloading sources, run build
instead of init
with the appropriate flags.
Known issues
konduit init
fails forlinux-86_64-gpu
(#115)
Linux builds
Generally, the Linux builds of Konduit Serving perform the following tasks on installation:
Copy Konduit Serving JAR file to
/opt/konduit/serving/
;Create the necessary environment variables; and
Install a Konduit Serving-specific Conda distribution with
install-python.sh
.
RPM (CentOS, Redhat, etc.)
Konduit Serving RPM packages are generated using the RPM Maven Plugin.
First, install required packages with yum
:
sudo yum install -y java-1.8.0-openjdk-devel which rpm-build redhat-rpm-config
This command installs the developer tools for developing Java programs using JDK 8, the which
package to locate a program file's path, tools to build RPM files and Red Hat-specific RPM configuration files.
In the root folder of the konduit-serving
project, run the following command to build RPM files using Maven Wrapper:
./mvnw clean package -Ppython,pmml,uberjar,tar,rpm -Dmaven.test.skip=true -Djavacpp.platform=linux-x86_64 -Dchip=cpu
The Maven Wrapper mvnw
script allows Maven to be used even if mvn
is not available on the system PATH. This command runs the Maven goals clean
and install
with the following arguments:
maven.test.skip=true
Profiles:
uberjar,tar,rpm
(ensure this is specified without spaces in between). The profilespython
andpmml
are optional.chip
:cpu
(usegpu
to enable CUDA support)javacpp.platform
:linux-x86_64
The clean install
command first deletes previously compiled Java sources and resources; then compiles, tests and packages the Java project and copies it into the relevant folder. The path where the RPM file is saved depends on the spin.version
(default custom
) and the chip (cpu
or gpu
) .
Use the YUM command yum localinstall
to install the RPM file.
# replace <spin.version> with the spin version specified
cd konduit-serving-rpm/target/rpm/konduit-serving-<spin.version>-cpu/RPMS/x86_64/
sudo yum localinstall -y *.rpm
DEB (for Ubuntu and other Debian-based systems)
Konduit Serving Debian packages are generated with the jdeb library.
Install JDK 8 using apt-get
:
sudo apt-get install openjdk-8-jdk curl
In the root directory of the Konduit Serving project, run the mvnw
script with parameters:
./mvnw clean package -Ppython,pmml,uberjar,tar,deb -Dmaven.test.skip=true -Djavacpp.platform=linux-x86_64 -Dchip=cpu
maven.test.skip=true
Enable the profiles
uberjar,tar,deb
(ensure this is specified without spaces in between). Thepython
andpmml
profiles are optional.chip
:cpu
(usegpu
to enable CUDA support)javacpp.platform
:linux-x86_64
Finally, use dpkg
to install the built package:
sudo dpkg -i konduit-serving-deb/target/konduit-serving-custom-cpu_0.1.0-SNAPSHOT.deb
Note that dpkg
does not support dependencies. If you run into missing dependencies, run
sudo apt-get install -f
to install dependencies. Alternately, use the gdebi
package to install the local DEB package (see this StackExchange thread for details), or simply use apt-get install
to install the local package (apt 1.1 and above):
cd konduit-serving-deb/target
sudo apt-get install ./*.deb
Tarball
Konduit Serving can also be built as a tarball, where the JAR file and associated scripts are packaged in a gzip-compressed tar file. To build a Konduit Serving tar file, run the following Maven Wrapper command in the root folder of the Konduit Serving project:
./mvnw clean package -Ppython,pmml,uberjar,tar -Dmaven.test.skip=true -Djavacpp.platform=linux-x86_64 -Dchip=cpu
This generates two compressed files in the target
directory of the konduit-serving-tar
folder: a tar (.tar.gz
) and a zip (.zip)
file. In addition to the JAR file, the tar file contains a script to install a Conda distribution (ìnstall-python.sh
) and a script to set environment variables (bin/konduit-serving
).
After extracting the tar file, first run the konduit-serving
shell script:
cd bin
chmod u+x konduit-serving # allow user to execute script
./konduit-serving
then the ìnstall-python.sh
script:
cd ..
chmod u+x install-python.sh
./install-python.sh
Konduit Serving Conda distribution
The following packages are included in this Conda distribution:
Package
Version
NumPy
1.16.4
Jupyter
1.0.0
SciPy
1.3.3
requests
2.22.0
pandas
0.24.2
TensorFlow
1.15.0
Keras
2.2.4
konduit
0.1.3rc1
scikit-learn
0.22
matplotlib
3.1.2
PyTorch
1.3.1
torchvision
0.4.2
CUDA Toolkit
10.1
OpenJDK
8
Note that packages are sourced from the following Anaconda channels, in descending order of priority: pytorch, conda-forge, anaconda, konduitai.
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