Part Number: SK-AM62A-LP
Tool/software:
Describe the bug
I followed the edgeai-modelmaker instructions step by step, the model can be trained and converted into onnx file but there are some issues generating artifacts. The artifacts folder under
/local_data/home/mattmak/edgeai-tensorlab/edgeai-modelmaker/data/projects/htt-warehouse-20250313/run/20250314--141431/yolox_s_lite/compilation/AM62A/work/od-8220
is empty. The run.log is attached, please look at it. Seems like the problem is related TIDLCompilationProvider.
INFO:20250314-141038: running - od-8220
INFO:20250314-141038: pipeline_config - {'task_type': 'detection', 'dataset_category': 'coco', 'calibration_dataset': <edgeai_benchmark.datasets.modelmaker_datasets.ModelMakerDetectionDataset object at 0x7f2bff641e40>, 'input_dataset': <edgeai_benchmark.datasets.modelmaker_datasets.ModelMakerDetectionDataset object at 0x7f2bff5e1390>, 'preprocess': <edgeai_benchmark.preprocess.PreProcessTransforms object at 0x7f2b19ce5660>, 'session': <edgeai_benchmark.sessions.onnxrt_session.ONNXRTSession object at 0x7f2b19ce56c0>, 'postprocess': <edgeai_benchmark.postprocess.PostProcessTransforms object at 0x7f2b19ce5960>, 'metric': {'label_offset_pred': 1}, 'model_info': {'metric_reference': {'accuracy_ap[.5:.95]%': None}, 'model_shortlist': 10, 'compact_name': 'yolox-s-lite-mmdet-coco-640x640', 'shortlisted': True, 'recommended': True}}
INFO:20250314-141038: import - od-8220 - this may take some time.../local_data/home/mattmak/.pyenv/versions/3.10.16/envs/benchmark2/lib/python3.10/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py:65: UserWarning: Specified provider 'TIDLCompilationProvider' is not in available provider names.Available providers: 'CPUExecutionProvider'
warnings.warn(
EP Error Unknown Provider Type: TIDLCompilationProvider when using ['TIDLCompilationProvider', 'CPUExecutionProvider']
Falling back to ['CPUExecutionProvider'] and retrying.
================================ import model =============
INFO:20250314-141038: import completed - od-8220 - 1 sec
SUCCESS:20250314-141038: benchmark results - {}
INFO:20250314-141038: running - od-8220
INFO:20250314-141038: pipeline_config - {'task_type': 'detection', 'dataset_category': 'coco', 'calibration_dataset': <edgeai_benchmark.datasets.modelmaker_datasets.ModelMakerDetectionDataset object at 0x7f2bff641e40>, 'input_dataset': <edgeai_benchmark.datasets.modelmaker_datasets.ModelMakerDetectionDataset object at 0x7f2bff5e1390>, 'preprocess': <edgeai_benchmark.preprocess.PreProcessTransforms object at 0x7f2b19ce5660>, 'session': <edgeai_benchmark.sessions.onnxrt_session.ONNXRTSession object at 0x7f2b19ce56c0>, 'postprocess': <edgeai_benchmark.postprocess.PostProcessTransforms object at 0x7f2b19ce5960>, 'metric': {'label_offset_pred': 1}, 'model_info': {'metric_reference': {'accuracy_ap[.5:.95]%': None}, 'model_shortlist': 10, 'compact_name': 'yolox-s-lite-mmdet-coco-640x640', 'shortlisted': True, 'recommended': True}}
INFO:20250314-141038: infer - od-8220 - this may take some time...
infer : od-8220 | 0%| || 0/107 [00:00<?, ?it/s]
infer : od-8220 | | 0% 0/107| [< ]
infer : od-8220 | 100%|##########|| 107/107 [00:08<00:00, 12.88it/s]
INFO:20250314-141047: infer completed - od-8220 - 9 sec
SUCCESS:20250314-141047: benchmark results - {'infer_path': 'od-8220', 'accuracy_ap[.5:.95]%': 6.353999, 'accuracy_ap50%': 13.545679, 'num_subgraphs': 0, 'infer_time_core_ms': 0.0, 'infer_time_subgraph_ms': 0.0, 'ddr_transfer_mb': 0.0, 'perfsim_time_ms': 0.0, 'perfsim_ddr_transfer_mb': 0.0, 'perfsim_gmacs': 0.0}
SUCCESS: ModelMaker - Compilation completed.
According to run.log, the TIDL (Texas Instruments Deep Learning) provider, which is required for hardware acceleration on the AM62A target, could not be initialized. As a result, the process falls back to the CPUExecutionProvider.
Below is my pip list, FYI# All necessary imports at the beginning
Package Version Editable project location
------------------------ -------------------- ----------------------------------------------------------------------------------
absl-py 2.1.0
addict 2.4.0
aenum 3.1.15
aliyun-python-sdk-core 2.15.2
aliyun-python-sdk-kms 2.16.5
attrs 24.2.0
autocfg 0.0.8
autocommand 2.2.2
backports.tarfile 1.2.0
cachetools 5.5.0
caffe2onnx 1.0.2
certifi 2024.8.30
cffi 1.17.1
charset-normalizer 3.3.2
click 8.1.7
cloudpickle 3.0.0
colorama 0.4.6
colored 2.2.4
coloredlogs 15.0.1
contourpy 1.3.0
crcmod 1.7
cryptography 43.0.1
cycler 0.12.1
Cython 3.0.11
dataclasses 0.6
debugpy 1.8.6
decorator 5.1.1
dill 0.3.8
distro 1.9.0
dlr 1.13.0
edgeai_benchmark 10.0.0+0cab45c /local_data/home/mattmak/edgeai-tensorlab/edgeai-benchmark
edgeai_modelmaker 10.0.0+0cab45c /local_data/home/mattmak/edgeai-tensorlab/edgeai-modelmaker
edgeai-torchmodelopt 10.0.0 /local_data/home/mattmak/edgeai-tensorlab/edgeai-modeloptimization/torchmodelopt
edgeai_xvision 9.0.0 /local_data/home/mattmak/edgeai-tensorlab/edgeai-torchvision/references/edgeailite
exceptiongroup 1.2.2
filelock 3.14.0
flatbuffers 1.12
fonttools 4.54.1
fsspec 2024.2.0
gluoncv 0.10.5.post0
google-auth 2.35.0
google-auth-oauthlib 0.4.6
graphviz 0.20.3
grpcio 1.66.1
h5py 3.12.1
huggingface-hub 0.29.1
humanfriendly 10.0
idna 3.10
imageio 2.37.0
importlib_metadata 8.5.0
importlib_resources 6.4.0
inflect 7.3.1
iniconfig 2.0.0
jaraco.collections 5.1.0
jaraco.context 5.3.0
jaraco.functools 4.0.1
jaraco.text 3.12.1
Jinja2 3.1.3
jmespath 0.10.0
joblib 1.4.2
json-tricks 3.17.3
kiwisolver 1.4.7
lazy_loader 0.4
loguru 0.7.3
Markdown 3.7
markdown-it-py 3.0.0
MarkupSafe 2.1.5
matplotlib 3.9.2
mdurl 0.1.2
ml_dtypes 0.5.1
mmcv 2.2.0
mmdeploy 1.3.1 /local_data/home/mattmak/edgeai-tensorlab/edgeai-mmdeploy
mmdet 3.3.0 /local_data/home/mattmak/edgeai-tensorlab/edgeai-mmdetection
mmengine 0.10.5
model-index 0.1.11
more-itertools 10.3.0
mpmath 1.3.0
multiprocess 0.70.16
munkres 1.1.4
networkx 3.2.1
ninja 1.11.1.1
numpy 1.23.0
nvidia-cublas-cu11 11.11.3.6
nvidia-cuda-cupti-cu11 11.8.87
nvidia-cuda-nvrtc-cu11 11.8.89
nvidia-cuda-runtime-cu11 11.8.89
nvidia-cudnn-cu11 9.1.0.70
nvidia-cufft-cu11 10.9.0.58
nvidia-curand-cu11 10.3.0.86
nvidia-cusolver-cu11 11.4.1.48
nvidia-cusparse-cu11 11.7.5.86
nvidia-nccl-cu11 2.20.5
nvidia-nvtx-cu11 11.8.86
oauthlib 3.2.2
onnx 1.14.0
onnx_graphsurgeon 0.3.26
onnx-simplifier 0.4.36
onnxruntime 1.15.0
onnxruntime-tidl 1.14.0+10000005
onnxscript 0.2.0
onnxsim 0.4.35
opencv-python 4.10.0.84
opencv-python-headless 4.10.0.84
opendatalab 0.0.10
openmim 0.3.9
openxlab 0.1.2
ordered-set 4.1.0
osrt_model_tools 1.2
oss2 2.17.0
packaging 24.1
pandas 2.2.3
pillow 11.1.0
Pillow-SIMD 9.5.0.post2
pip 25.0.1
platformdirs 4.3.6
pluggy 1.5.0
plyfile 1.1
portalocker 3.1.1
prettytable 3.11.0
progiter 2.0.0
progressbar 2.5
protobuf 3.20.3
psutil 6.0.0
pyasn1 0.6.1
pyasn1_modules 0.4.1
pybind11 2.13.6
pybind11_global 2.13.6
pycocotools 2.0.8
pycparser 2.22
pycryptodome 3.20.0
pydot 3.0.2
Pygments 2.18.0
pyparsing 3.1.4
pytest 8.3.3
python-dateutil 2.9.0.post0
pytz 2023.4
PyYAML 6.0.2
requests 2.28.2
requests-oauthlib 2.0.0
rich 13.4.2
rsa 4.9
safetensors 0.5.2
scikit-image 0.24.0
scikit-learn 1.5.2
scipy 1.13.1
seaborn 0.13.2
setuptools 76.0.0
shapely 2.0.6
six 1.16.0
sympy 1.13.1
tabulate 0.9.0
tensorboard 2.11.2
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
termcolor 2.4.0
terminaltables 3.1.10
tflite 2.10.0
tflite-runtime 2.12.0
thop 0.1.1.post2209072238
threadpoolctl 3.5.0
tifffile 2025.1.10
timm 1.0.15
tomli 2.0.1
torch 2.4.0+cu118
torchaudio 2.4.0+cu118
torchinfo 1.8.0
torchvision 0.19.0+cu118
tornado 6.4.1
tqdm 4.65.2
triton 3.0.0
tvm 0.12.0
typeguard 4.3.0
typing_extensions 4.12.2
tzdata 2024.2
urllib3 1.26.20
wcwidth 0.2.13
Werkzeug 3.0.4
wheel 0.44.0
wurlitzer 3.1.1
yacs 0.1.8
yapf 0.40.2
yolox 0.1.0 /local_data/home/mattmak/edgeai-tensorlab/edgeai-yolox
zipp 3.20.2
**Expected behavior and Actual Behaviour**
Artifacts should be generated. But now the generated artifacts folder is empty.
**Additional context**
In the previous version of edgeai-tensorlab (r10.0), there were indeed some bugs but I fixed all of them and then everything was fine. However, for version r10.1 (the most updated one), I encounter the problem mentioned here, which I had never had before.
