Add device_name classmethod in Accelerator.

[GdoongMathew]

What does this PR do?

Fixes #17355

• 1 GPU

GPU available: NVIDIA GeForce RTX 3050 4GB Laptop GPU, using: 1 devices.
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs

• 2 GPUs (Kaggle)

>>> t = Trainer(devices=2)
INFO: GPU available: Tesla T4, using: 2 devices.
INFO: TPU available: False, using: 0 TPU cores
INFO: HPU available: False, using: 0 HPUs

• No cuda GPU available

GPU available: False, using: 0 devices.
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs

• MPS

GPU available: Apple M1 Pro, using: 1 devices.
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs

• XLA (Kaggle)

GPU available: False, using: 0 devices.
TPU available: v3-8, using: 8 TPU cores
HPU available: False, using: 0 HPUs

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• Did you make sure to update the documentation with your changes? (if necessary)
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• Did you verify new and existing tests pass locally with your changes?
• Did you list all the breaking changes introduced by this pull request?
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---

📚 Documentation preview 📚: https://pytorch-lightning--21112.org.readthedocs.build/en/21112/

[GdoongMathew]

Results in Kaggle:

• CPU: https://www.kaggle.com/code/gdoong/lightning-cpu?scriptVersionId=258513715&cellId=2
• GPU x 2: https://www.kaggle.com/code/gdoong/lightning-gpu?scriptVersionId=258514966&cellId=2
• TPU: https://www.kaggle.com/code/gdoong/lightning-tpu?scriptVersionId=258515194&cellId=2

[justusschock]

How would you handle heterogeneous gpu types? E.g. say I have one 3090 and one 4090 in my workstation. This doesn't handle it at all.

[GdoongMathew]

How would you handle heterogeneous gpu types? E.g. say I have one 3090 and one 4090 in my workstation. This doesn't handle it at all.

Hi @justusschock , based on the change, the output should look something like

GPU available: RTX 3090, RTX 4090, using: 2 devices.

that being said, if the setup is more complex - for example 2 x 3090 and 1 x 4090 - the current output might not fully reflect that.

[GdoongMathew]

Hi @Borda , a friendly ping for a review ~

[Borda]

Hi @Borda , a friendly ping for a review ~

unfortunatly, I am not in a position to approve a feature type PR, lest ping @ethanwharris

[codecov]

Codecov Report

❌ Patch coverage is 74.00000% with 13 lines in your changes missing coverage. Please review.
✅ Project coverage is 79%. Comparing base (8ac4843) to head (6f185e5).
✅ All tests successful. No failed tests found.

❗ There is a different number of reports uploaded between BASE (8ac4843) and HEAD (6f185e5). Click for more details.

HEAD has 390 uploads less than BASE

Flag	BASE (8ac4843)	HEAD (6f185e5)
python3.10	12	3
cpu	120	30
lightning	60	15
pytest	60	0
lightning_fabric	30	0
python3.12	36	9
python3.11	24	6
python3.12.7	36	9
python	12	3
pytorch_lightning	30	15
pytorch2.6	6	3
pytest-full	60	30
pytorch2.5.1	6	3
pytorch2.7	6	3
pytorch2.9	6	3
pytorch2.2.2	6	3
pytorch2.1	12	6
pytorch2.8	6	3
pytorch2.3	6	3
pytorch2.4.1	6	3

Additional details and impacted files

@@            Coverage Diff            @@
##           master   #21112     +/-   ##
=========================================
- Coverage      87%      79%     -8%     
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  Files         269      266      -3     
  Lines       23799    23783     -16     
=========================================
- Hits        20618    18745   -1873     
- Misses       3181     5038   +1857