NVIDIA / NVIDIA/apex

Do I Need to Set Up Softlink On Every Training with AMP?

Open
#514 1 comment 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
9k
Forks
1.5k
Avg merge
2d 4h
Merged PRs (30d)
3

Description

I am reviewing the documentation on apex/examples/imagenet/. It states that a softlink should be set before the training execution.
(i.e
$ ln -sf /data/imagenet/train-jpeg/ train
$ ln -sf /data/imagenet/val-jpeg/ val)

I would like to deploy AMP in my own repo. Do I need to follow the example above to set up softlink with training data + validation data before I execute a training?

Also, I found that in main_amp.py, the argument "data" is a compulsory argument. (i.e. parser.add_argument('data', metavar='DIR', help='path to dataset')) Why in the example code, you don't need to specify the "data" argument? (e.g. $ python main_amp.py -a resnet50 --b 128 --workers 4 --opt-level O0 ./ )

Thank you.

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reading the documentation under apex/examples/imagenet/ and the argument definition in main_amp.py. Clarify whether the train and val softlinks are required for the example and explain how the example command supplies the compulsory data argument. Done means the documentation answers both questions consistently.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
documentation, machine-learning
Issue type
Documentation
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.