[hotfix/hybridengine] Fix init model with random parameters in benchmark (#5074)

* fix init model with random parameters

* fix example
pull/5078/head
Bin Jia 2023-11-20 20:15:25 +08:00 committed by GitHub
parent 8921a73c90
commit 4e3959d316
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3 changed files with 33 additions and 7 deletions

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@ -95,11 +95,27 @@ def print_details_info(timestamps, model_config, args, whole_end2end):
def benchmark_inference(args):
if args.model == "toy":
model = transformers.LlamaForCausalLM(transformers.LlamaConfig(num_hidden_layers=8))
model = transformers.LlamaForCausalLM(transformers.LlamaConfig(num_hidden_layers=4))
elif args.model == "7b":
model = transformers.LlamaForCausalLM(transformers.AutoConfig.from_pretrained("decapoda-research/llama-7b-hf"))
model = transformers.LlamaForCausalLM(
transformers.LlamaConfig(
hidden_size=4096,
intermediate_size=11008,
num_attention_heads=32,
num_hidden_layers=32,
num_key_value_heads=32,
)
)
elif args.model == "13b":
model = transformers.LlamaForCausalLM(transformers.AutoConfig.from_pretrained("decapoda-research/llama-13b-hf"))
model = transformers.LlamaForCausalLM(
transformers.LlamaConfig(
hidden_size=5120,
intermediate_size=13824,
num_attention_heads=40,
num_hidden_layers=40,
num_key_value_heads=40,
)
)
else:
raise NotImplementedError

View File

@ -1,6 +1,16 @@
script_dir=$(cd "$(dirname "$0")" && pwd)
cd "${script_dir}"
# toy model, 2tp*2pp 1024, 128
python ./benchmark.py \
--model="toy" \
--dtype="fp16" \
--batch_size=2 \
--seq_len=1024 \
--output_len=128 \
--mb_size=1 \
--pp_size=2 \
--tp_size=2
# 7b, fp16, 2 gpu, 1024, 128
for BATCH_SIZE in 2 4 8 16; do
@ -9,7 +19,7 @@ for BATCH_SIZE in 2 4 8 16; do
--dtype="fp16" \
--batch_size=${BATCH_SIZE} \
--seq_len=1024 \
--new_length=128 \
--output_len=128 \
--mb_size=$((${BATCH_SIZE}/2)) \
--pp_size=2 \
--tp_size=2
@ -22,7 +32,7 @@ for BATCH_SIZE in 2 4 8 16 32; do
--dtype="fp16" \
--batch_size=${BATCH_SIZE} \
--seq_len=512 \
--new_length=512 \
--output_len=512 \
--mb_size=$((${BATCH_SIZE}/2)) \
--pp_size=2 \
--tp_size=2
@ -35,7 +45,7 @@ for BATCH_SIZE in 2 4 8; do
--dtype="fp16" \
--batch_size=${BATCH_SIZE} \
--seq_len=1024 \
--new_length=128 \
--output_len=128 \
--mb_size=$((${BATCH_SIZE}/2)) \
--pp_size=2 \
--tp_size=2
@ -48,7 +58,7 @@ for BATCH_SIZE in 2 4 8 16; do
--dtype="fp16" \
--batch_size=${BATCH_SIZE} \
--seq_len=512 \
--new_length=512 \
--output_len=512 \
--mb_size=$((${BATCH_SIZE}/2)) \
--pp_size=2 \
--tp_size=2