Summary on Supporting PyTorch

Workflow description about ElasticDL

About start command:

elasticdl train --image_name=elasticdl:mnist: tutorials/elasticdl_local.md

setup entry: elasticdl=elasticdl_client.main:main

Create master:

elasticdl_client/api.py

Run worker:

run task (training/evaluation/prediction).Only calculate the gradient and report gradient to ps.

worker/mian.py

elastic/python/worker/worker.py

PS Client:

Push parameters to PS:elastic/python/worker/ps_client.py

---

How to print gradient information directly in PyTorch.

Usually, we train in PyTorch with an optimizer.