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

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Merged
ver217 merged 2 commits into from
Nov 20, 2023
Merged

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

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a813b7e
fix init model with random parameters
FoolPlayer Nov 20, 2023
5d27d8b
fix example
FoolPlayer Nov 20, 2023
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Empty file added colossalai/shardformer/modeling/chatglm2_6b/__init__.py
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22 changes: 19 additions & 3 deletions examples/inference/benchmark.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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

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18 changes: 14 additions & 4 deletions examples/inference/run_benchmark.sh
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Original file line number Diff line number Diff line change
@@ -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
Expand All @@ -9,7 +19,7 @@ for BATCH_SIZE in 2 4 8 16; do
--dtype="fp16" \
--batch_size=${BATCH_SIZE} \
--seq_len=1024 \
--new_length=128 \
--output_len=128 \
--mb_size=$((${BATCH_SIZE}/2)) \
--pp_size=2 \
--tp_size=2
Expand All @@ -22,7 +32,7 @@ for BATCH_SIZE in 2 4 8 16 32; do
--dtype="fp16" \
--batch_size=${BATCH_SIZE} \
--seq_len=512 \
--new_length=512 \
--output_len=512 \
--mb_size=$((${BATCH_SIZE}/2)) \
--pp_size=2 \
--tp_size=2
Expand All @@ -35,7 +45,7 @@ for BATCH_SIZE in 2 4 8; do
--dtype="fp16" \
--batch_size=${BATCH_SIZE} \
--seq_len=1024 \
--new_length=128 \
--output_len=128 \
--mb_size=$((${BATCH_SIZE}/2)) \
--pp_size=2 \
--tp_size=2
Expand All @@ -48,7 +58,7 @@ for BATCH_SIZE in 2 4 8 16; do
--dtype="fp16" \
--batch_size=${BATCH_SIZE} \
--seq_len=512 \
--new_length=512 \
--output_len=512 \
--mb_size=$((${BATCH_SIZE}/2)) \
--pp_size=2 \
--tp_size=2
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