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[Misc] add non cuda hf benchmark_througput #8653

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[Misc] add non cuda hf benchmark_througput #8653

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666e8a5
chore : add non cuda hf benchmark_througput
park12sj Sep 20, 2024
4beae50
chore : float32 load if device is cpu in run_hf
park12sj Sep 20, 2024
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11 changes: 7 additions & 4 deletions benchmarks/benchmark_throughput.py
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Original file line number Diff line number Diff line change
Expand Up @@ -232,14 +232,17 @@ def run_hf(
use_beam_search: bool,
max_batch_size: int,
trust_remote_code: bool,
device: str,
) -> float:
assert not use_beam_search
is_cuda = device == "cuda"
if is_cuda:
llm = llm.cuda()
Comment on lines +238 to +240
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Apply .cuda only when device=="cuda"

llm = AutoModelForCausalLM.from_pretrained(
model, torch_dtype=torch.float16, trust_remote_code=trust_remote_code)
model, torch_dtype=torch.float16 if is_cuda else torch.float32, trust_remote_code=trust_remote_code)
if llm.config.model_type == "llama":
# To enable padding in the HF backend.
tokenizer.pad_token = tokenizer.eos_token
llm = llm.cuda()

pbar = tqdm(total=len(requests))
start = time.perf_counter()
Expand All @@ -264,7 +267,7 @@ def run_hf(
input_ids = tokenizer(batch, return_tensors="pt",
padding=True).input_ids
llm_outputs = llm.generate(
input_ids=input_ids.cuda(),
input_ids=input_ids.cuda() if is_cuda else input_ids,
do_sample=not use_beam_search,
num_return_sequences=n,
temperature=1.0,
Expand Down Expand Up @@ -341,7 +344,7 @@ def main(args: argparse.Namespace):
assert args.tensor_parallel_size == 1
elapsed_time = run_hf(requests, args.model, tokenizer, args.n,
args.use_beam_search, args.hf_max_batch_size,
args.trust_remote_code)
args.trust_remote_code, args.device)
elif args.backend == "mii":
elapsed_time = run_mii(requests, args.model, args.tensor_parallel_size,
args.output_len)
Expand Down
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