github/ColossalAI
1
0
Fork 0
mirror of https://github.com/hpcaitech/ColossalAI.git synced 2025-08-03 00:57:06 +00:00
Code Issues Packages Projects Releases Wiki Activity

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

Browse Source 
* fix init model with random parameters

* fix example
This commit is contained in:
Bin Jia 2023-11-20 20:15:25 +08:00 committed by GitHub
parent 8921a73c90
commit 4e3959d316
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 33 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

0
colossalai/shardformer/modeling/chatglm2_6b/__init__.py Normal file
View File

22
examples/inference/benchmark.py
View File

@ -95,11 +95,27 @@ def print_details_info(timestamps, model_config, args, whole_end2end):
def benchmark_inference(args): def benchmark_inference(args):
if args.model == "toy": 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": 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": 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: else:
raise NotImplementedError raise NotImplementedError

18
examples/inference/run_benchmark.sh
View File

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