Add Benchmarking and Fine-Tuning Support for ZenFlow #982
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- Introduced `zf_benchmark.py` for model offloading benchmarking with DeepSpeed. - Added `output_table.py` to parse and display benchmark results in a tabular format. - Created `run_benchmark.sh` to automate benchmark runs with various configurations. Signed-off-by: Tingfeng Lan <[email protected]>
- Introduced `finetune_llama.py` for fine-tuning the Llama-2 model using DeepSpeed and ZenFlow. - Added `finetune_llama.sh` for automated training setup with environment variables and DeepSpeed command. - Added `zf_config.json` example for DeepSpeed configuration with ZenFlow optimizations. Signed-off-by: Tingfeng Lan <[email protected]> Co-authored-by: Yusen Wu <[email protected]>
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Signed-off-by: Tingfeng Lan <[email protected]>
Signed-off-by: Tingfeng Lan <[email protected]>
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@sfc-gh-truwase Thanks for the great suggestions — I’ve applied them all! |
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Hi @Antlera I have a question. I saw ZenFlow has CPU running parameter update. Does DeepSpeed argument Here is a link to this switch. This is a switch for CPU backend, but for CPU offload this switch should help as well. |
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Description:
This PR introduces scripts for benchmarking and fine-tuning with ZenFlow:
zf_benchmark.py: Benchmark script for evaluating offloading performance (adapted fromoffload_states.pyby @tohtana ).output_table.py: Parses and summarizes benchmark logs.run_benchmark.sh: Automates benchmark runs with configurable parameters.finetune_llama.py: Fine-tuning script for Llama-2 with DeepSpeed + ZenFlow.finetune_llama.sh: Launch script for fine-tuning with environment setup.zf_config.json: Example DeepSpeed config with ZenFlow optimizations.Note: This PR is complimentary to PR #7391 on the main repo, and should be merged with (or after) merging PR #7391.