Kai Huang 6981745fe4 Optimize kv_cache for gpt-neox model family (#9015 )

* override gptneox

* style

* move to utils

* revert

2023-09-20 19:59:19 +08:00

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All in One Benchmark Test

All in one benchmark test allows users to test all the benchmarks and record them in a result CSV. Users can provide models and related information in config.yaml.

Before running, make sure to have bigdl-llm and bigdl-nano installed.

Dependencies

pip install omageconfig
pip install pandas

Config

Config YAML file has following format

repo_id:
  - 'THUDM/chatglm-6b'
  - 'THUDM/chatglm2-6b'
  - 'meta-llama/Llama-2-7b-chat-hf'
local_model_hub: 'path to your local model hub'
warm_up: 1
num_trials: 3
in_out_pairs:
  - '32-32'
  - '1024-128'
test_api:
  - "transformer_int4"
  - "native_int4"
  - "optimize_model"
  - "pytorch_autocast_bf16"
  # - "transformer_int4_gpu"  # on arc
  # - "optimize_model_gpu"  # on arc

Run

run python run.py, this will output results to results.csv.

For SPR performance, run bash run-spr.sh.

Note

In run-spr.sh, we set optimal environment varaible by source bigdl-nano-init -c, -c stands for disabling jemalloc. Enabling jemalloc may lead to latency increasement after multiple trials.

The value of OMP_NUM_THREADS should be the same as the cpu cores specified by numactl -C.

Note

Please install torch nightly version to avoid Illegal instruction (core dumped) issue, you can follow the following command to install: pip install --pre --upgrade torch --index-url https://download.pytorch.org/whl/nightly/cpu

For ARC performance, run bash run-arc.sh.

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All in One Benchmark Test

Dependencies

Config

Run

1.5 KiB

Raw Blame History