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Move model benchmarking #2016

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Move model benchmarking #2016

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pytorch-bot bot commented Apr 4, 2025

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2016

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

❌ 1 New Failure

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@jainapurva jainapurva requested a review from Copilot April 4, 2025 06:14
@facebook-github-bot facebook-github-bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Apr 4, 2025
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Copilot reviewed 8 out of 16 changed files in this pull request and generated 1 comment.

Files not reviewed (8)
  • benchmarks/models/llama/benchmark_results.txt: Language not supported
  • benchmarks/models/llama/benchmarks.sh: Language not supported
  • benchmarks/models/llama/bsr_bench_results.txt: Language not supported
  • benchmarks/models/llama/bsr_benchmarks.sh: Language not supported
  • benchmarks/models/llama/demo_summarize.sh: Language not supported
  • benchmarks/models/llama/evals.sh: Language not supported
  • benchmarks/models/sam/benchmark.sh: Language not supported
  • benchmarks/models/sam/results.csv: Language not supported
Comments suppressed due to low confidence (1)

benchmarks/models/llama/_eval.py:335

  • [nitpick] The variable name 'input' shadows the built-in function. Consider renaming it to 'model_input' or a similar descriptive name.
input = self.input_prep_func(inps)

quantizer = Int4WeightOnlyGPTQQuantizer(group_size=groupsize, device=device)
model.setup_caches(max_batch_size=1, max_seq_length=calibration_seq_length)
model = quantizer.quantize(model, inputs).to(device)
else:
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The else clause attached to the 'if "int4wo" in quantization and "gptq" in quantization:' block may execute unexpectedly when other quantization conditions are met. Consider restructuring these conditionals using elif to ensure each quantization case is handled independently.

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