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LLM: add chatglm3-6b to latency benchmark test. (#9442)

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Cengguang Zhang 2023-11-13 17:24:37 +08:00 committed by GitHub
parent 0e5ab5ebfc
commit ece5805572
1 changed files with 9 additions and 7 deletions
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16
python/llm/dev/benchmark/all-in-one/run.py
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@ -35,6 +35,8 @@ LLAMA_IDS = ['meta-llama/Llama-2-7b-chat-hf','meta-llama/Llama-2-13b-chat-hf',
'decapoda-research/llama-65b-hf','lmsys/vicuna-7b-v1.5',
'lmsys/vicuna-13b-v1.3','project-baize/merged-baize-30b']
CHATGLM_IDS = ['THUDM/chatglm-6b', 'THUDM/chatglm2-6b', 'THUDM/chatglm3-6b']
results = []
@ -135,7 +137,7 @@ def run_transformer_int4(repo_id,
# Load model in 4 bit,
# which convert the relevant layers in the model into INT4 format
st = time.perf_counter()
if repo_id in ['THUDM/chatglm-6b', 'THUDM/chatglm2-6b']:
if repo_id in CHATGLM_IDS:
model = AutoModel.from_pretrained(model_path, load_in_low_bit=low_bit, trust_remote_code=True, torch_dtype='auto')
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
elif repo_id in LLAMA_IDS:
@ -196,7 +198,7 @@ def run_pytorch_autocast_bf16(repo_id,
model_path = get_model_path(repo_id, local_model_hub)
st = time.perf_counter()
if repo_id in ['THUDM/chatglm-6b', 'THUDM/chatglm2-6b']:
if repo_id in CHATGLM_IDS:
# TODO: need verify chatglm family run bf16.
print("Currently pytorch do not support bfloat16 on cpu for chatglm models. Will skip it")
return
@ -263,7 +265,7 @@ def run_optimize_model(repo_id,
# Load model in 4 bit,
# which convert the relevant layers in the model into INT4 format
st = time.perf_counter()
if repo_id in ['THUDM/chatglm-6b', 'THUDM/chatglm2-6b']:
if repo_id in CHATGLM_IDS:
model = AutoModel.from_pretrained(model_path, torch_dtype='auto', low_cpu_mem_usage=True, trust_remote_code=True)
model = optimize_model(model, low_bit=low_bit)
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
@ -331,7 +333,7 @@ def run_transformer_int4_gpu(repo_id,
# Load model in 4 bit,
# which convert the relevant layers in the model into INT4 format
st = time.perf_counter()
if repo_id in ['THUDM/chatglm-6b', 'THUDM/chatglm2-6b']:
if repo_id in CHATGLM_IDS:
model = AutoModel.from_pretrained(model_path, load_in_low_bit=low_bit, optimize_model=True,
trust_remote_code=True, use_cache=True)
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
@ -410,7 +412,7 @@ def run_optimize_model_gpu(repo_id,
# Load model in 4 bit,
# which convert the relevant layers in the model into INT4 format
st = time.perf_counter()
if repo_id in ['THUDM/chatglm-6b', 'THUDM/chatglm2-6b']:
if repo_id in CHATGLM_IDS:
model = AutoModel.from_pretrained(model_path, torch_dtype='auto', low_cpu_mem_usage=True,
trust_remote_code=True, use_cache=True)
model = optimize_model(model, low_bit=low_bit)
@ -486,7 +488,7 @@ def run_ipex_fp16_gpu(repo_id,
import intel_extension_for_pytorch as ipex
model_path = get_model_path(repo_id, local_model_hub)
st = time.perf_counter()
if repo_id in ['THUDM/chatglm-6b', 'THUDM/chatglm2-6b']:
if repo_id in CHATGLM_IDS:
model = AutoModel.from_pretrained(model_path, trust_remote_code=True, use_cache=True)
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
model = model.half().to('xpu')
@ -569,7 +571,7 @@ def run_deepspeed_transformer_int4_cpu(repo_id,
st = time.perf_counter()
# Note: only tested cpu Llama2-7b
# Native Huggingface transformers loading to enable deepspeed init
if repo_id in ['THUDM/chatglm-6b', 'THUDM/chatglm2-6b']:
if repo_id in CHATGLM_IDS:
model = AutoModel.from_pretrained(model_path, trust_remote_code=True, use_cache=True)
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
elif repo_id in LLAMA_IDS: