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Enabled DETR (Object Detection) model #1046

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@cfgfung cfgfung commented Jun 5, 2024

What does this PR do?

This PR contains the patch, example, and test codes for DETR models.

A100 CUDA BF16(Autocast) benchmarks:
n_iterations: 10
Total latency (ms): 241.29199981689453
Average latency (ms): 24.129199981689453

Gaudi2 BF16(Autocast and Graph mode) benchmarks:
n_iterations: 10
Total latency (ms): 65.3073787689209
Average latency (ms): 6.53073787689209

Before submitting

  • [N.A.] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
  • [Yes] Did you make sure to update the documentation with your changes?
  • [Yes] Did you write any new necessary tests?

@cfgfung cfgfung requested a review from regisss as a code owner June 5, 2024 21:40
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libinta commented Jun 25, 2024

@cfgfung can you rebase the PR?

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cfgfung commented Jun 25, 2024

@cfgfung can you rebase the PR?

Hi,
I have applied rebase and here is the test result

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@imangohari1 imangohari1 left a comment

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Hi @cfgfung
thank you for the work here.
Below are my suggestions for this PR. Let's work on these and do a final review.

  • I've made some changes regarding some minor clean ups and ci tests. Please review and implement them via git am < 0001* (file attached).
  • Few minor comments are give in comment.

0001-fea-Minor-CI-updates-and-clean-ups.patch

G2 results (after applying the patch)

---------------------------: System Configuration :---------------------------
Num CPU Cores : 160
CPU RAM       : 1056375224 KB
------------------------------------------------------------------------------
Detected cat with confidence 1.0 at location [344.0, 25.25, 640.0, 376.0]
Detected remote with confidence 0.996 at location [328.0, 75.5, 372.0, 188.0]
Detected remote with confidence 0.996 at location [39.0, 70.5, 176.0, 118.0]
Detected cat with confidence 1.0 at location [15.62, 52.5, 316.0, 472.0]
Detected couch with confidence 0.996 at location [-1.25, 0.94, 640.0, 472.0]

Stats:
------------------------------------------------------------
Total latency (ms): 58.38346481323242 (for n_iterations=10)
Average latency (ms): 5.838346481323242 (per iteration)
------------------------------------------------------------

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minor comments.

# Run unit and integration tests related to Image segmentation
fast_tests_object_detection:
python -m pip install .[tests]
python -m pip install timm
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if no_timm is used for the test, is this needed?


adapt_transformers_to_gaudi()

# you can specify the revision tag if you don't want the timm dependency
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not sure how to approach this here, but would be nice to able to pass/toggle between no_timm and main revisions.

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3 participants