Changed from torch.cuda.amp.autocast to torch.amp.autocast

[jamesmuking5]

torch.cuda.amp.autocast to be deprecated

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/vision/8508

• 📄 Preview Python docs built from this PR

Note: Links to docs will display an error until the docs builds have been completed.

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[facebook-github-bot]

Hi @jamesmuking5!

Thank you for your pull request and welcome to our community.

Action Required

In order to merge any pull request (code, docs, etc.), we require contributors to sign our Contributor License Agreement, and we don't seem to have one on file for you.

Process

In order for us to review and merge your suggested changes, please sign at https://code.facebook.com/cla. If you are contributing on behalf of someone else (eg your employer), the individual CLA may not be sufficient and your employer may need to sign the corporate CLA.

Once the CLA is signed, our tooling will perform checks and validations. Afterwards, the pull request will be tagged with CLA signed. The tagging process may take up to 1 hour after signing. Please give it that time before contacting us about it.

If you have received this in error or have any questions, please contact us at [email protected]. Thanks!

[facebook-github-bot]

Thank you for signing our Contributor License Agreement. We can now accept your code for this (and any) Meta Open Source project. Thanks!

[NicolasHug]

Thanks a lot for the PR @jamesmuking5 .

The changes LGTM but I would suggest to just replace with torch.amp.autocast("cuda", ...) since none of those are expected to be on CPU.

If you can, it'd be great to also address the rest of the occurrences or torch.cuda.amp.* (I could find the ones below), but I can do that in a follow-up PR if you prefer. Thanks!

~/dev/vision (main*) » git grep torch.cuda.amp                                                                                          nicolashug@nicolashug-fedora-PF372ZT9
references/classification/README.md:Automatic Mixed Precision (AMP) training on GPU for Pytorch can be enabled with the [torch.cuda.amp](https://pytorch.org/docs/stable/amp.html?highlight=amp#module-torch.cuda.amp).
references/classification/train.py:        with torch.cuda.amp.autocast(enabled=scaler is not None):
references/classification/train.py:    scaler = torch.cuda.amp.GradScaler() if args.amp else None
references/classification/train.py:    parser.add_argument("--amp", action="store_true", help="Use torch.cuda.amp for mixed precision training")
references/depth/stereo/cascade_evaluation.py:    with torch.cuda.amp.autocast(enabled=args.mixed_precision, dtype=torch.float16):
references/depth/stereo/train.py:    with torch.cuda.amp.autocast(enabled=args.mixed_precision, dtype=torch.float16):
references/depth/stereo/train.py:        with torch.cuda.amp.autocast(enabled=args.mixed_precision, dtype=torch.float16):
references/depth/stereo/train.py:    scaler = torch.cuda.amp.GradScaler() if args.mixed_precision else None
references/detection/engine.py:        with torch.cuda.amp.autocast(enabled=scaler is not None):
references/detection/train.py:    parser.add_argument("--amp", action="store_true", help="Use torch.cuda.amp for mixed precision training")
references/detection/train.py:    scaler = torch.cuda.amp.GradScaler() if args.amp else None
references/segmentation/train.py:        with torch.cuda.amp.autocast(enabled=scaler is not None):
references/segmentation/train.py:    scaler = torch.cuda.amp.GradScaler() if args.amp else None
references/segmentation/train.py:    parser.add_argument("--amp", action="store_true", help="Use torch.cuda.amp for mixed precision training")
references/video_classification/train.py:        with torch.cuda.amp.autocast(enabled=scaler is not None):
references/video_classification/train.py:    scaler = torch.cuda.amp.GradScaler() if args.amp else None
references/video_classification/train.py:    parser.add_argument("--amp", action="store_true", help="Use torch.cuda.amp for mixed precision training")
test/test_models.py:    with torch.cuda.amp.autocast():
test/test_models.py:        with torch.cuda.amp.autocast():
test/test_models.py:        with torch.cuda.amp.autocast(), torch.no_grad(), freeze_rng_state():
test/test_models.py:        with torch.cuda.amp.autocast(), torch.no_grad(), freeze_rng_state():
test/test_models.py:        with torch.cuda.amp.autocast():
test/test_ops.py:        with torch.cuda.amp.autocast():
test/test_ops.py:        with torch.cuda.amp.autocast():
test/test_ops.py:        with torch.cuda.amp.autocast():
test/test_ops.py:        with torch.cuda.amp.autocast():