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Merged
mc-nv merged 8 commits into from
Dec 5, 2025
Merged

models: Allow generate models using enroot #8557

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2f642d1
temp: condition bypass.
mc-nv Dec 4, 2025
3ec4313
feat: Convert script generation into functions
mc-nv Dec 4, 2025
8fca505
models: PyTorch + enroot
mc-nv Dec 5, 2025
5f04917
models: OpenVino + ONNX Runtime
mc-nv Dec 5, 2025
b0964c9
models: Enroot enabled
mc-nv Dec 5, 2025
bd3e553
Revert "temp: condition bypass."
mc-nv Dec 5, 2025
a1bb13c
add conditional variable
mc-nv Dec 5, 2025
8565d81
Merge branch 'main' into mchornyi/TRI-306/enroot-models
mc-nv Dec 5, 2025
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254 changes: 173 additions & 81 deletions qa/common/gen_qa_model_repository
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Original file line number Diff line number Diff line change
Expand Up @@ -69,6 +69,8 @@ PYTORCH_IMAGE=${PYTORCH_IMAGE:=nvcr.io/nvidia/pytorch:$TRITON_VERSION-py3}
TENSORRT_IMAGE=${TENSORRT_IMAGE:=nvcr.io/nvidia/tensorrt:$TRITON_VERSION-py3}
CUDA_DEVICE=${NV_GPU:=0}
MODEL_TYPE=${MODEL_TYPE:-""}
TRITON_MODELS_USE_DOCKER=${TRITON_MODELS_USE_DOCKER:-"1"}
TRITON_MODELS_USE_ENROOT=${TRITON_MODELS_USE_ENROOT:-"1"}

log_message.status "define: CI related parameters"
CI_JOB_ID=${CI_JOB_ID:=$(date +%Y%m%d_%H%M)}
Expand All @@ -80,50 +82,54 @@ DOCKER_VOLUME=${DOCKER_VOLUME:=volume.gen_qa_model_repository.${CI_JOB_ID}}
DOCKER_VOLUME_CONTAINER=${DOCKER_VOLUME}.gen_qa_model_repository.${CI_JOB_ID}
DOCKER_GPU_ARGS=${DOCKER_GPU_ARGS:-$([[ $RUNNER_GPUS =~ ^[0-9] ]] && eval $NV_DOCKER_ARGS || echo "--gpus device=$CUDA_DEVICE" )}

log_message.status "define: model output directories"
TRITON_MDLS_BLD_DIR=${TRITON_MDLS_BLD_DIR:=/mnt/$CI_JOB_ID}
TRITON_MDLS_SRC_DIR=${TRITON_MDLS_SRC_DIR:=$TRITON_MDLS_BLD_DIR/gen_srcdir}
TRITON_MDLS_QA_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_model_repository
TRITON_MDLS_QA_VARIABLE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_variable_model_repository
TRITON_MDLS_QA_IDENTITY_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_identity_model_repository
TRITON_MDLS_QA_IDENTITY_BIG_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_identity_big_model_repository
TRITON_MDLS_QA_SHAPETENSOR_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_shapetensor_model_repository
TRITON_MDLS_QA_RESHAPE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_reshape_model_repository
TRITON_MDLS_QA_SEQUENCE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_sequence_model_repository
TRITON_MDLS_QA_DYNA_SEQUENCE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_dyna_sequence_model_repository
TRITON_MDLS_QA_DYNA_SEQUENCE_IMPLICIT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_dyna_sequence_implicit_model_repository
TRITON_MDLS_QA_VARIABLE_SEQUENCE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_variable_sequence_model_repository
TRITON_MDLS_QA_ENSEMBLE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_ensemble_model_repository
TRITON_MDLS_QA_NOSHAPE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_noshape_model_repository
TRITON_MDLS_QA_TRT_PLUGIN_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_trt_plugin_model_repository
TRITON_MDLS_QA_RAGGED_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_ragged_model_repository
TRITON_MDLS_QA_TRT_FORMAT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_trt_format_model_repository
TRITON_MDLS_QA_TRT_DATA_DEPENDENT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_trt_data_dependent_model_repository
TRITON_MDLS_QA_SEQUENCE_IMPLICIT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_sequence_implicit_model_repository
TRITON_MDLS_QA_VARIABLE_SEQUENCE_IMPLICIT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_variable_sequence_implicit_model_repository
TRITON_MDLS_QA_SEQUENCE_INITIAL_STATE_IMPLICIT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_sequence_initial_state_implicit_model_repository
TRITON_MDLS_QA_VARIABLE_SEQUENCE_INITIAL_STATE_IMPLICIT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_variable_sequence_initial_state_implicit_model_repository
TRITON_MDLS_QA_TORCHTRT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/torchtrt_model_store
TRITON_MDLS_QA_SCALAR_MODELS=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_scalar_models
TRITON_MDLS_QA_DYNAMIC_BATCH_IMAGE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_dynamic_batch_image_model_repository
TRITON_MDLS_QA_CUSTOM_OPS=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_custom_ops/libtorch_custom_ops

log_message.status "define: script names"

OPENVINOSCRIPT=gen.OpenVINO.gen_qa_model_repository.v2.sh
log_message.info "OpenVINO script: " "${OPENVINOSCRIPT}"

ONNXSCRIPT=gen.ONNXRuntime.gen_qa_model_repository.v2.sh
log_message.info "ONNX script: " "${ONNXSCRIPT}"

TORCHSCRIPT=gen.PyTorch.gen_qa_model_repository.v2.sh
log_message.info "PyTorch script: " "${TORCHSCRIPT}"

TRTSCRIPT=gen.TensorRT.gen_qa_model_repository.v2.sh
log_message.info "TensorRT script: " "${TRTSCRIPT}"

log_message.status "create: OpenVINO script - ${OPENVINOSCRIPT}"
cat > $OPENVINOSCRIPT <<EOF
function define_model_output_directories() {
log_message.status "define: model output directories"
TRITON_MDLS_BLD_DIR=${TRITON_MDLS_BLD_DIR:=/mnt/$CI_JOB_ID}
TRITON_MDLS_SRC_DIR=${TRITON_MDLS_SRC_DIR:=$TRITON_MDLS_BLD_DIR/gen_srcdir}
TRITON_MDLS_QA_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_model_repository
TRITON_MDLS_QA_VARIABLE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_variable_model_repository
TRITON_MDLS_QA_IDENTITY_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_identity_model_repository
TRITON_MDLS_QA_IDENTITY_BIG_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_identity_big_model_repository
TRITON_MDLS_QA_SHAPETENSOR_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_shapetensor_model_repository
TRITON_MDLS_QA_RESHAPE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_reshape_model_repository
TRITON_MDLS_QA_SEQUENCE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_sequence_model_repository
TRITON_MDLS_QA_DYNA_SEQUENCE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_dyna_sequence_model_repository
TRITON_MDLS_QA_DYNA_SEQUENCE_IMPLICIT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_dyna_sequence_implicit_model_repository
TRITON_MDLS_QA_VARIABLE_SEQUENCE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_variable_sequence_model_repository
TRITON_MDLS_QA_ENSEMBLE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_ensemble_model_repository
TRITON_MDLS_QA_NOSHAPE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_noshape_model_repository
TRITON_MDLS_QA_TRT_PLUGIN_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_trt_plugin_model_repository
TRITON_MDLS_QA_RAGGED_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_ragged_model_repository
TRITON_MDLS_QA_TRT_FORMAT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_trt_format_model_repository
TRITON_MDLS_QA_TRT_DATA_DEPENDENT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_trt_data_dependent_model_repository
TRITON_MDLS_QA_SEQUENCE_IMPLICIT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_sequence_implicit_model_repository
TRITON_MDLS_QA_VARIABLE_SEQUENCE_IMPLICIT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_variable_sequence_implicit_model_repository
TRITON_MDLS_QA_SEQUENCE_INITIAL_STATE_IMPLICIT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_sequence_initial_state_implicit_model_repository
TRITON_MDLS_QA_VARIABLE_SEQUENCE_INITIAL_STATE_IMPLICIT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_variable_sequence_initial_state_implicit_model_repository
TRITON_MDLS_QA_TORCHTRT_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/torchtrt_model_store
TRITON_MDLS_QA_SCALAR_MODELS=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_scalar_models
TRITON_MDLS_QA_DYNAMIC_BATCH_IMAGE_MODEL=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_dynamic_batch_image_model_repository
TRITON_MDLS_QA_CUSTOM_OPS=$TRITON_MDLS_BLD_DIR/$TRITON_VERSION/qa_custom_ops/libtorch_custom_ops
}

function define_models_generation_scripts() {
log_message.status "define: script names"
SCRIPT_NAME_SUFFIX=${SCRIPT_NAME_SUFFIX:-v2}

OPENVINOSCRIPT=gen.OpenVINO.gen_qa_model_repository.${SCRIPT_NAME_SUFFIX}.sh
log_message.info "OpenVINO script: " "${OPENVINOSCRIPT}"

ONNXSCRIPT=gen.ONNXRuntime.gen_qa_model_repository.${SCRIPT_NAME_SUFFIX}.sh
log_message.info "ONNX script: " "${ONNXSCRIPT}"

TORCHSCRIPT=gen.PyTorch.gen_qa_model_repository.${SCRIPT_NAME_SUFFIX}.sh
log_message.info "PyTorch script: " "${TORCHSCRIPT}"

TRTSCRIPT=gen.TensorRT.gen_qa_model_repository.${SCRIPT_NAME_SUFFIX}.sh
log_message.info "TensorRT script: " "${TRTSCRIPT}"

log_message.status "create: OpenVINO script - ${OPENVINOSCRIPT}"
cat > $OPENVINOSCRIPT <<EOF
#!/bin/bash
# Make all generated files accessible outside of container
umask 0000
Expand All @@ -133,9 +139,18 @@ set -e
set -x
export DEBIAN_FRONTEND=noninteractive
apt-get update && \
apt-get install -y --no-install-recommends build-essential cmake libprotobuf-dev \
protobuf-compiler python3 python3-dev python3-pip wget gnupg2 \
software-properties-common
apt-get install -y --no-install-recommends \
build-essential \
cmake \
libprotobuf-dev \
protobuf-compiler \
python3 \
python3-dev \
python3-pip \
wget \
gnupg2 \
software-properties-common

ln -s /usr/bin/python3 /usr/bin/python

pip3 install "numpy<=1.23.5" setuptools
Expand All @@ -157,16 +172,16 @@ chmod -R 777 $TRITON_MDLS_QA_RESHAPE_MODEL
# chmod -R 777 $TRITON_MDLS_QA_DYNA_SEQUENCE_MODEL
EOF

log_message.status "run: chmod a+x ${OPENVINOSCRIPT}"
chmod a+x $OPENVINOSCRIPT
log_message.status "run: chmod a+x ${OPENVINOSCRIPT}"
chmod a+x $OPENVINOSCRIPT

if [ $? -ne 0 ]; then
log_message.error "failed: chmod ${OPENVINOSCRIPT}"
exit 1
fi
if [ $? -ne 0 ]; then
log_message.error "failed: chmod ${OPENVINOSCRIPT}"
exit 1
fi

log_message.status "create: ONNX script - ${ONNXSCRIPT}"
cat > $ONNXSCRIPT <<EOF
log_message.status "create: ONNX script - ${ONNXSCRIPT}"
cat > $ONNXSCRIPT <<EOF
#!/bin/bash
# Make all generated files accessible outside of container
umask 0000
Expand Down Expand Up @@ -220,15 +235,15 @@ python3 $TRITON_MDLS_SRC_DIR/gen_qa_sequence_models.py --ensemble --variable --m
chmod -R 777 $TRITON_MDLS_QA_ENSEMBLE_MODEL
EOF

log_message.status "run: chmod a+x ${ONNXSCRIPT}"
chmod a+x ${ONNXSCRIPT}
if [ $? -ne 0 ]; then
log_message.error "failed: chmod ${ONNXSCRIPT}"
exit 1
fi
log_message.status "run: chmod a+x ${ONNXSCRIPT}"
chmod a+x ${ONNXSCRIPT}
if [ $? -ne 0 ]; then
log_message.error "failed: chmod ${ONNXSCRIPT}"
exit 1
fi

log_message.status "create: PyTorch script - ${TORCHSCRIPT}"
cat > $TORCHSCRIPT <<EOF
log_message.status "create: PyTorch script - ${TORCHSCRIPT}"
cat > $TORCHSCRIPT <<EOF
#!/bin/bash
# Make all generated files accessible outside of container
umask 0000
Expand Down Expand Up @@ -265,22 +280,23 @@ chmod -R 777 $TRITON_MDLS_QA_RAGGED_MODEL
python3 $TRITON_MDLS_SRC_DIR/gen_qa_image_models.py --resnet50 --resnet152 --vgg19 --models_dir=$TRITON_MDLS_QA_DYNAMIC_BATCH_IMAGE_MODEL
chmod -R 777 $TRITON_MDLS_QA_DYNAMIC_BATCH_IMAGE_MODEL

export TORCH_EXTENSIONS_DIR="/root/.cache/torch_extensions/"
export TORCH_EXTENSIONS_DIR=/tmp/.cache/torch_extensions/
mkdir -p \${TORCH_EXTENSIONS_DIR}
python3 $TRITON_MDLS_SRC_DIR/gen_qa_custom_ops_models.py --libtorch --models_dir=$TRITON_MDLS_QA_CUSTOM_OPS
mkdir -p $TRITON_MDLS_QA_CUSTOM_OPS/libtorch_modulo/
cp \${TORCH_EXTENSIONS_DIR}/custom_modulo/custom_modulo.so $TRITON_MDLS_QA_CUSTOM_OPS/libtorch_modulo/.
chmod -R 777 $TRITON_MDLS_QA_CUSTOM_OPS
EOF

log_message.status "run: chmod a+x ${TORCHSCRIPT}"
chmod a+x ${TORCHSCRIPT}
if [ $? -ne 0 ]; then
log_message.error "failed: chmod ${TORCHSCRIPT}"
exit 1
fi
log_message.status "run: chmod a+x ${TORCHSCRIPT}"
chmod a+x ${TORCHSCRIPT}
if [ $? -ne 0 ]; then
log_message.error "failed: chmod ${TORCHSCRIPT}"
exit 1
fi

log_message.status "create: TensorRT script - ${TRTSCRIPT}"
cat > $TRTSCRIPT <<EOF
log_message.status "create: TensorRT script - ${TRTSCRIPT}"
cat > $TRTSCRIPT <<EOF
#!/bin/bash
# Make all generated files accessible outside of container
umask 0000
Expand Down Expand Up @@ -337,17 +353,23 @@ LD_PRELOAD=$TRITON_MDLS_QA_TRT_PLUGIN_MODEL/libcustomHardmaxPlugin.so python3 $T
chmod -R 777 $TRITON_MDLS_QA_TRT_PLUGIN_MODEL
EOF

log_message.status "run: chmod a+x ${TRTSCRIPT}"
chmod a+x ${TRTSCRIPT}
if [ $? -ne 0 ]; then
log_message.error "failed: chmod ${TRTSCRIPT}"
exit 1
fi
log_message.status "run: chmod a+x ${TRTSCRIPT}"
chmod a+x ${TRTSCRIPT}
if [ $? -ne 0 ]; then
log_message.error "failed: chmod ${TRTSCRIPT}"
exit 1
fi

}

log_message.status "check: engine installation"
if which docker ; then
if [ "$TRITON_MODELS_USE_DOCKER" -eq 1 ] && which docker ; then
log_message.info "Docker is installed."

define_model_output_directories

SCRIPT_NAME_SUFFIX=docker.v2 define_models_generation_scripts

if ! docker volume inspect $DOCKER_VOLUME > /dev/null 2>&1; then
log_message.status "docker volume: $DOCKER_VOLUME does not exist. Creating..."
docker volume create $DOCKER_VOLUME --label RUNNER_ID=$RUNNER_ID --label PROJECT_NAME=$PROJECT_NAME
Expand Down Expand Up @@ -498,9 +520,79 @@ if which docker ; then
docker volume rm $DOCKER_VOLUME
fi # [ -z $CI ]

elif which enroot ; then
elif [ "$TRITON_MODELS_USE_ENROOT" -eq 1 ] && which enroot ; then
log_message.info "NVIDIA Enroot is installed." ;

TRITON_MDLS_BLD_DIR="/tmp/$CI_JOB_ID" define_model_output_directories

SCRIPT_NAME_SUFFIX=enroot.v1 define_models_generation_scripts

log_message.status "cleanup models folder if exists: $TRITON_MDLS_BLD_DIR"
rm -rf $TRITON_MDLS_BLD_DIR

log_message.status "create models directory structure in: $TRITON_MDLS_BLD_DIR"
mkdir -p \
$TRITON_MDLS_BLD_DIR \
$TRITON_MDLS_SRC_DIR \
$TRITON_MDLS_QA_MODEL \
$TRITON_MDLS_QA_VARIABLE_MODEL \
$TRITON_MDLS_QA_IDENTITY_MODEL \
$TRITON_MDLS_QA_IDENTITY_BIG_MODEL \
$TRITON_MDLS_QA_SHAPETENSOR_MODEL \
$TRITON_MDLS_QA_RESHAPE_MODEL \
$TRITON_MDLS_QA_SEQUENCE_MODEL \
$TRITON_MDLS_QA_DYNA_SEQUENCE_MODEL \
$TRITON_MDLS_QA_DYNA_SEQUENCE_IMPLICIT_MODEL \
$TRITON_MDLS_QA_VARIABLE_SEQUENCE_MODEL \
$TRITON_MDLS_QA_ENSEMBLE_MODEL \
$TRITON_MDLS_QA_NOSHAPE_MODEL \
$TRITON_MDLS_QA_TRT_PLUGIN_MODEL \
$TRITON_MDLS_QA_RAGGED_MODEL \
$TRITON_MDLS_QA_TRT_FORMAT_MODEL \
$TRITON_MDLS_QA_TRT_DATA_DEPENDENT_MODEL \
$TRITON_MDLS_QA_SEQUENCE_IMPLICIT_MODEL \
$TRITON_MDLS_QA_VARIABLE_SEQUENCE_IMPLICIT_MODEL \
$TRITON_MDLS_QA_SEQUENCE_INITIAL_STATE_IMPLICIT_MODEL \
$TRITON_MDLS_QA_VARIABLE_SEQUENCE_INITIAL_STATE_IMPLICIT_MODEL \
$TRITON_MDLS_QA_TORCHTRT_MODEL \
$TRITON_MDLS_QA_SCALAR_MODELS \
$TRITON_MDLS_QA_DYNAMIC_BATCH_IMAGE_MODEL

log_message.status "copy scripts to: $TRITON_MDLS_SRC_DIR"
cp -rv $TRITON_MDLS_BASE_SCRIPT_DIR/* $TRITON_MDLS_SRC_DIR/

log_message.status "enroot import: $UBUNTU_IMAGE to ubuntu.$CI_JOB_ID.enroot.sqsh"
enroot import --output /tmp/ubuntu.$CI_JOB_ID.enroot.sqsh docker://$UBUNTU_IMAGE


log_message.status "enroot create: openvino.ubuntu.$CI_JOB_ID"
enroot create --name openvino.ubuntu.$CI_JOB_ID /tmp/ubuntu.$CI_JOB_ID.enroot.sqsh
log_message.info "enroot start: openvino.ubuntu.$CI_JOB_ID"
enroot start --root --rw -m /tmp:/tmp openvino.ubuntu.$CI_JOB_ID bash -xe $TRITON_MDLS_SRC_DIR/$OPENVINOSCRIPT


log_message.status "enroot create: onnxruntime.ubuntu.$CI_JOB_ID"
enroot create --name onnxruntime.ubuntu.$CI_JOB_ID /tmp/ubuntu.$CI_JOB_ID.enroot.sqsh
log_message.info "enroot start: onnxruntime.ubuntu.$CI_JOB_ID"
enroot start --root --rw -m /tmp:/tmp onnxruntime.ubuntu.$CI_JOB_ID bash -xe $TRITON_MDLS_SRC_DIR/$ONNXSCRIPT


log_message.status "enroot import: $PYTORCH_IMAGE to /tmp/pytorch.$CI_JOB_ID.enroot.sqsh"
enroot import --output /tmp/pytorch.$CI_JOB_ID.enroot.sqsh docker://$PYTORCH_IMAGE

log_message.status "enroot create: pytorch.$CI_JOB_ID"
enroot create --name pytorch.$CI_JOB_ID /tmp/pytorch.$CI_JOB_ID.enroot.sqsh
log_message.status "enroot start: pytorch.$CI_JOB_ID"
enroot start --rw -m /tmp:/tmp pytorch.$CI_JOB_ID bash -xe $TRITON_MDLS_SRC_DIR/$TORCHSCRIPT

log_message.status "enroot import: $TENSORRT_IMAGE to /tmp/tensorrt.$CI_JOB_ID.enroot.sqsh"
enroot import --output /tmp/tensorrt.$CI_JOB_ID.enroot.sqsh docker://$TENSORRT_IMAGE
log_message.status "enroot create: tensorrt.$CI_JOB_ID"
enroot create --name tensorrt.$CI_JOB_ID /tmp/tensorrt.$CI_JOB_ID.enroot.sqsh
log_message.status "enroot start: tensorrt.$CI_JOB_ID"
enroot start --rw -m /tmp:/tmp tensorrt.$CI_JOB_ID bash -xe $TRITON_MDLS_SRC_DIR/$TRTSCRIPT

else
log_message.warning "Neither Docker nor NVIDIA Enroot is installed." ;
log_message.warning "Please install either Docker or NVIDIA Enroot to generate the models." ;
log_message.warning "Please install Docker or NVIDIA Enroot to generate the models." ;
fi
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