Package SINGA using conda-build

This note is written for the repo maintainer.

To create conda package and upload, you can follow the following steps:

1. Build the docker image

To have the build environment, use the dockerfile from

For example:

docker build SINGA_DIR/singa/tool/conda/docker/cpu -t nusdbsystem/singa:conda-cpu

2. Build the container from the image and access the container

For example:

docker run -it -p 2222:22 --runtime nvidia --name singa_conda_cpu --rm nusdbsystem/singa:conda-cpu bash

3. Build conda packages

There are three versions of conda package: (i) CPU, (ii) GPU, and (iii) DIST (distributed training)

To build the specific versions, follow the steps:

(i) cd to the folder tool/conda/singa, follow the instruction in

For example, for CPU version:

cd tool/conda/singa
conda config --add channels conda-forge
conda config --add channels nusdbsystem
conda-build .  --python 3.6
anaconda -t $ANACONDA_UPLOAD_TOKEN upload -u nusdbsystem -l main /root/miniconda/conda-bld/linux-64/singa-3.1.0-cpu_py36.tar.bz2

The above will generate the SINGA package. The next step will be wrapping it to generate SINGA-CPU / SINGA-GPU / SINGA-DIST conda packages.

(ii) For different versions, cd to different folder:

For CPU version, cd to tool/conda/cpu For GPU version, cd to tool/conda/gpu For DIST version, cd to tool/conda/dist

(iii) Generate the SINGA-CPU / SINGA-GPU / SINGA-DIST anaconda package and upload.

For an example of SINGA-CPU version:

cd tool/conda/cpu
conda-build .  --python 3.6
anaconda -t $ANACONDA_UPLOAD_TOKEN upload -u nusdbsystem -l main /root/miniconda/conda-bld/linux-64/singa-cpu-3.1.0-py36.tar.bz2

Since SINGA-CPU, SINGA-GPU and SINGA-DIST packages are wrapped from SINGA package, the steps from (i) to (iii) are necessary.