Deepspeed
Introduction
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. For more information, please check: Home page: https://www.deepspeed.ai Docker: docker://rocm/deepspeed
Versions
rocm4.2_ubuntu18.04_py3.6_pytorch_1.8.1
Commands
deepspeed
python
python3
python3.6
ipython
ipython3
convert-caffe2-to-onnx
convert-onnx-to-caffe2
estimator_ckpt_converter
import_pb_to_tensorboard
tensorboard
tflite_convert
mpirun
mpiexec
ompi_info
Module
You can load the modules by:
module load rocmcontainers
module load deepspeed
Example job
Warning
Using #!/bin/sh -l
as shebang in the slurm job script will cause the failure of some biocontainer modules. Please use #!/bin/bash
instead.
To run deepspeed on our clusters:
#!/bin/bash
#SBATCH -A myallocation # Allocation name
#SBATCH -t 1:00:00
#SBATCH -N 1
#SBATCH -n 1
#SBATCH --job-name=deepspeed
#SBATCH --mail-type=FAIL,BEGIN,END
#SBATCH --error=%x-%J-%u.err
#SBATCH --output=%x-%J-%u.out
module --force purge
ml rocmcontainers deepspeed