Move model benchmarking evaluation scripts to benchmarks folder #2016
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2016
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- 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
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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.
jainapurva
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