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[CI/Build] Add shell script linting using shellcheck (#7925)

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Signed-off-by: Russell Bryant <rbryant@redhat.com>
This commit is contained in:
Russell Bryant
2024-11-07 13:17:29 -05:00
committed by GitHub
parent de0e61a323
commit 3be5b26a76
28 changed files with 204 additions and 129 deletions
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63
.buildkite/nightly-benchmarks/scripts/launch-server.sh
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@@ -50,31 +50,30 @@ launch_trt_server() {
git clone https://github.com/triton-inference-server/tensorrtllm_backend.git
git lfs install
cd tensorrtllm_backend
git checkout $trt_llm_version
tensorrtllm_backend_dir=$(pwd)
git checkout "$trt_llm_version"
git submodule update --init --recursive
# build trtllm engine
cd /tensorrtllm_backend
cd ./tensorrt_llm/examples/${model_type}
cd "./tensorrt_llm/examples/${model_type}"
python3 convert_checkpoint.py \
--model_dir ${model_path} \
--dtype ${model_dtype} \
--tp_size ${model_tp_size} \
--output_dir ${trt_model_path}
--model_dir "${model_path}" \
--dtype "${model_dtype}" \
--tp_size "${model_tp_size}" \
--output_dir "${trt_model_path}"
trtllm-build \
--checkpoint_dir ${trt_model_path} \
--checkpoint_dir "${trt_model_path}" \
--use_fused_mlp \
--reduce_fusion disable \
--workers 8 \
--gpt_attention_plugin ${model_dtype} \
--gemm_plugin ${model_dtype} \
--tp_size ${model_tp_size} \
--max_batch_size ${max_batch_size} \
--max_input_len ${max_input_len} \
--max_seq_len ${max_seq_len} \
--max_num_tokens ${max_num_tokens} \
--output_dir ${trt_engine_path}
--gpt_attention_plugin "${model_dtype}" \
--gemm_plugin "${model_dtype}" \
--tp_size "${model_tp_size}" \
--max_batch_size "${max_batch_size}" \
--max_input_len "${max_input_len}" \
--max_seq_len "${max_seq_len}" \
--max_num_tokens "${max_num_tokens}" \
--output_dir "${trt_engine_path}"
# handle triton protobuf files and launch triton server
cd /tensorrtllm_backend
@@ -82,15 +81,15 @@ launch_trt_server() {
cp -r all_models/inflight_batcher_llm/* triton_model_repo/
cd triton_model_repo
rm -rf ./tensorrt_llm/1/*
cp -r ${trt_engine_path}/* ./tensorrt_llm/1
cp -r "${trt_engine_path}"/* ./tensorrt_llm/1
python3 ../tools/fill_template.py -i tensorrt_llm/config.pbtxt triton_backend:tensorrtllm,engine_dir:/tensorrtllm_backend/triton_model_repo/tensorrt_llm/1,decoupled_mode:true,batching_strategy:inflight_fused_batching,batch_scheduler_policy:guaranteed_no_evict,exclude_input_in_output:true,triton_max_batch_size:2048,max_queue_delay_microseconds:0,max_beam_width:1,max_queue_size:2048,enable_kv_cache_reuse:false
python3 ../tools/fill_template.py -i preprocessing/config.pbtxt triton_max_batch_size:2048,tokenizer_dir:$model_path,preprocessing_instance_count:5
python3 ../tools/fill_template.py -i postprocessing/config.pbtxt triton_max_batch_size:2048,tokenizer_dir:$model_path,postprocessing_instance_count:5,skip_special_tokens:false
python3 ../tools/fill_template.py -i ensemble/config.pbtxt triton_max_batch_size:$max_batch_size
python3 ../tools/fill_template.py -i tensorrt_llm_bls/config.pbtxt triton_max_batch_size:$max_batch_size,decoupled_mode:true,accumulate_tokens:"False",bls_instance_count:1
python3 ../tools/fill_template.py -i preprocessing/config.pbtxt "triton_max_batch_size:2048,tokenizer_dir:$model_path,preprocessing_instance_count:5"
python3 ../tools/fill_template.py -i postprocessing/config.pbtxt "triton_max_batch_size:2048,tokenizer_dir:$model_path,postprocessing_instance_count:5,skip_special_tokens:false"
python3 ../tools/fill_template.py -i ensemble/config.pbtxt triton_max_batch_size:"$max_batch_size"
python3 ../tools/fill_template.py -i tensorrt_llm_bls/config.pbtxt "triton_max_batch_size:$max_batch_size,decoupled_mode:true,accumulate_tokens:False,bls_instance_count:1"
cd /tensorrtllm_backend
python3 scripts/launch_triton_server.py \
--world_size=${model_tp_size} \
--world_size="${model_tp_size}" \
--model_repo=/tensorrtllm_backend/triton_model_repo &
}
@@ -98,10 +97,7 @@ launch_trt_server() {
launch_tgi_server() {
model=$(echo "$common_params" | jq -r '.model')
tp=$(echo "$common_params" | jq -r '.tp')
dataset_name=$(echo "$common_params" | jq -r '.dataset_name')
dataset_path=$(echo "$common_params" | jq -r '.dataset_path')
port=$(echo "$common_params" | jq -r '.port')
num_prompts=$(echo "$common_params" | jq -r '.num_prompts')
server_args=$(json2args "$server_params")
if echo "$common_params" | jq -e 'has("fp8")' >/dev/null; then
@@ -129,10 +125,7 @@ launch_tgi_server() {
launch_lmdeploy_server() {
model=$(echo "$common_params" | jq -r '.model')
tp=$(echo "$common_params" | jq -r '.tp')
dataset_name=$(echo "$common_params" | jq -r '.dataset_name')
dataset_path=$(echo "$common_params" | jq -r '.dataset_path')
port=$(echo "$common_params" | jq -r '.port')
num_prompts=$(echo "$common_params" | jq -r '.num_prompts')
server_args=$(json2args "$server_params")
server_command="lmdeploy serve api_server $model \
@@ -149,10 +142,7 @@ launch_sglang_server() {
model=$(echo "$common_params" | jq -r '.model')
tp=$(echo "$common_params" | jq -r '.tp')
dataset_name=$(echo "$common_params" | jq -r '.dataset_name')
dataset_path=$(echo "$common_params" | jq -r '.dataset_path')
port=$(echo "$common_params" | jq -r '.port')
num_prompts=$(echo "$common_params" | jq -r '.num_prompts')
server_args=$(json2args "$server_params")
if echo "$common_params" | jq -e 'has("fp8")' >/dev/null; then
@@ -185,10 +175,7 @@ launch_vllm_server() {
model=$(echo "$common_params" | jq -r '.model')
tp=$(echo "$common_params" | jq -r '.tp')
dataset_name=$(echo "$common_params" | jq -r '.dataset_name')
dataset_path=$(echo "$common_params" | jq -r '.dataset_path')
port=$(echo "$common_params" | jq -r '.port')
num_prompts=$(echo "$common_params" | jq -r '.num_prompts')
server_args=$(json2args "$server_params")
if echo "$common_params" | jq -e 'has("fp8")' >/dev/null; then
@@ -217,19 +204,19 @@ launch_vllm_server() {
main() {
if [[ $CURRENT_LLM_SERVING_ENGINE == "trt" ]]; then
if [[ "$CURRENT_LLM_SERVING_ENGINE" == "trt" ]]; then
launch_trt_server
fi
if [[ $CURRENT_LLM_SERVING_ENGINE == "tgi" ]]; then
if [[ "$CURRENT_LLM_SERVING_ENGINE" == "tgi" ]]; then
launch_tgi_server
fi
if [[ $CURRENT_LLM_SERVING_ENGINE == "lmdeploy" ]]; then
if [[ "$CURRENT_LLM_SERVING_ENGINE" == "lmdeploy" ]]; then
launch_lmdeploy_server
fi
if [[ $CURRENT_LLM_SERVING_ENGINE == "sglang" ]]; then
if [[ "$CURRENT_LLM_SERVING_ENGINE" == "sglang" ]]; then
launch_sglang_server
fi