Model load error on CV25

[AtsushiYokokawa]

The model converted with tensorflow-to-larod-cv25 does not work.
Here are the steps I tried.

• Environment

  • PC
    • OS: Windows 11 Pro (WSL: Ubuntu-20.04)
    • CPU: 11th Gen Intel(R) Core(TM) i7-11390H @ 3.40GHz 2.92 GHz
    • RAM: 16.0GB
    • GPU: Intel IRIS
    • Docker: Docker Desktop V4.17.0
    • CVTool: Ambarella_Toolchain_CNNGen_Basic_2.5.6_20231117
  • Camera
    • Camera: M3086-V
    • FW: 11.10.83

• Steps

  • Model conversion

    docker build --tag tensorflow-to-larod-cv25 --build-arg TRAIN_EPOCHS=1 .
    docker cp $(docker create tensorflow-to-larod-cv25):/env/training/models/converted_model.tflite ./converted_model.tflite
    

  • Compile with CVTool

    gen_image_list.py -f pics -o dra_image_bin/img_list.txt -ns -e .jpg -c 0 -d 0,0 -r 256,256 -bf dra_image_bin -bo dra_image_bin/dra_bin_list.txt
    # [gen_image_list] Folder input received: pics
    # [gen_image_list] Created file: dra_image_bin/img_list.txt
    # (info) using #30 thread(s) to run imgtobin
    # [info][#13] Convert 12a768fce3b51894.jpg to 12a768fce3b51894.bin ... Done
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    # [gen_image_list] Folder input received: /home/docker/dra_image_bin
    # [gen_image_list] Created file: dra_image_bin/dra_bin_list.txt
    # [gen_image_list] Converted 100 files to binary, saved in /home/docker/dra_image_bin
    

    tfparser.py -p converted_model.tflite -o car_human_model -of ./out_car_human_model -isrc "is:1,3,256,256|iq|i:input_1=./dra_image_bin/dra_bin_list.txt|ic:255.00446258|idf:0,0,0,0" -odst "o:Identity|odf:fp32" -odst "o:Identity_1|odf:fp32" -c act-force-fx16,coeff-force-fx16
    # 2024-06-26 07:18:36.574819: I tensorflow/stream_executor/platform/default/dso_loader.cc:50] Successfully opened dynamic library libcudart.so.12
    # WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
    # /usr/local/lib/python3.8/dist-packages/pandas/core/computation/expressions.py:20: UserWarning: Pandas requires version '2.7.3' or newer of 'numexpr' (version '2.7.1' currently installed).
    #   from pandas.core.computation.check import NUMEXPR_INSTALLED
    # WARNING:root:Limited tf.compat.v2.summary API due to missing TensorBoard installation.
    # WARNING:tensorflow:From /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/frameworklibs/cv2.basic.2.5.6.0.1245.ubu2004/lib/python3.8/site-packages/frameworklibs/tensorflow/tflite/tf_lite_supported_ops.py:60: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.
    # 
    # WARNING:tensorflow:From /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/frameworklibs/cv2.basic.2.5.6.0.1245.ubu2004/lib/python3.8/site-packages/frameworklibs/tensorflow/tflite/tf_lite_supported_ops.py:60: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.
    # 
    # WARNING:tensorflow:From /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/frameworklibs/cv2.basic.2.5.6.0.1245.ubu2004/lib/python3.8/site-packages/frameworklibs/tensorflow/tflite/tf_lite_supported_ops.py:61: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.
    # 
    # WARNING:tensorflow:From /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/frameworklibs/cv2.basic.2.5.6.0.1245.ubu2004/lib/python3.8/site-packages/frameworklibs/tensorflow/tflite/tf_lite_supported_ops.py:61: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.
    # 
    # WARNING:tensorflow:From /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/frameworklibs/cv2.basic.2.5.6.0.1245.ubu2004/lib/python3.8/site-packages/frameworklibs/tensorflow/tflite/tf_lite_supported_ops.py:104: The name tf.batch_to_space_nd is deprecated. Please use tf.batch_to_space instead.
    # 
    # WARNING:tensorflow:From /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/frameworklibs/cv2.basic.2.5.6.0.1245.ubu2004/lib/python3.8/site-packages/frameworklibs/tensorflow/tflite/tf_lite_supported_ops.py:104: The name tf.batch_to_space_nd is deprecated. Please use tf.batch_to_space instead.
    # 
    # WARNING:tensorflow:From /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/frameworklibs/cv2.basic.2.5.6.0.1245.ubu2004/lib/python3.8/site-packages/frameworklibs/tensorflow/tflite/tf_lite_supported_ops.py:105: The name tf.space_to_batch_nd is deprecated. Please use tf.space_to_batch instead.
    # 
    # WARNING:tensorflow:From /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/frameworklibs/cv2.basic.2.5.6.0.1245.ubu2004/lib/python3.8/site-packages/frameworklibs/tensorflow/tflite/tf_lite_supported_ops.py:105: The name tf.space_to_batch_nd is deprecated. Please use tf.space_to_batch instead.
    # 
    # INFO: 06/26/2024 07:18:41.987708 logger.py:372 [TFLite_Parser] Application logs will be written to the log directory: ./logs
    # INFO: 06/26/2024 07:18:42.127938 tf_lite_v2.py:254 [TFLite_Parser] [MAIN] TFLite model provided by the user: /home/docker/converted_model.tflite
    # INFO: 06/26/2024 07:18:42.129113 tf_lite_v2.py:255 [TFLite_Parser] [MAIN] List of user output nodes: ['Identity', 'Identity_1']
    # INFO: 06/26/2024 07:18:42.130067 tf_lite_v2.py:256 [TFLite_Parser] [MAIN] Do not use quantization data formats: False
    # INFO: 06/26/2024 07:18:42.131749 tf_lite_v2.py:257 [TFLite_Parser] [MAIN] Invoke Asymmetric adjustement: False
    # INFO: 06/26/2024 07:18:42.132419 tf_lite_v2.py:258 [TFLite_Parser] [MAIN] Schema file path: /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/frameworklibs/cv2.basic.2.5.6.0.1245.ubu2004/bin/schema.fbs
    # INFO: 06/26/2024 07:18:42.132673 tf_lite_v2.py:259 [TFLite_Parser] [MAIN] FLATC executable path: /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/frameworklibs/cv2.basic.2.5.6.0.1245.ubu2004/bin/flatc
    # INFO: 06/26/2024 07:18:42.134538 tf_lite_v2.py:260 [TFLite_Parser] [MAIN] Checkpoint path: /home/docker//reconstructed_pb_model/converted_model_ckpt
    # INFO: 06/26/2024 07:18:42.136037 tf_lite_v2.py:261 [TFLite_Parser] [MAIN] Output protobuf reconstructed: /home/docker//reconstructed_pb_model/converted_model_reconstructed.pb
    # INFO: 06/26/2024 07:18:42.136290 tf_lite_v2.py:285 [TFLite_Parser] [FLATC EXE] Converting tflite model to JSON file using flatc executable
    # INFO: 06/26/2024 07:18:43.497503 tf_lite_v2.py:427 [TFLite_Parser] [RECONSTRUCT PROTO] Convert JSON file to protobuf
    # INFO: 06/26/2024 07:18:43.731525 tf_lite_v2.py:316 [TFLite_Parser] [SET IO NODE] Input of the model: ['input_1']
    # INFO: 06/26/2024 07:18:43.731851 tf_lite_v2.py:317 [TFLite_Parser] [SET IO NODE] Output of the model: ['Identity', 'Identity_1']
    # 2024-06-26 07:18:43.736630: W tensorflow/stream_executor/platform/default/dso_loader.cc:61] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv22/tv2/release/Amalgam/cv22.basic.2.5.6.0.1245.ubu2004/lib:/usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv22/tv2/release/libvdg/cv22.basic.2.5.6.0.1245.ubu2004/lib:/usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv22/tv2/release/VpRef/cv22.basic.2.5.6.0.1245.ubu2004/lib:/usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv22/tv2/release/Zamboni/cv22.basic.2.5.6.0.1245.ubu2004/lib:/usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/AmbaCnn/cv2.basic.2.5.6.0.1245.ubu2004/lib:/usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/ApfCanon/1.13/x86_64-linux/lib:/usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/LibAmb/1.19/x86_64-linux/lib:/usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/LibApf/1.13/x86_64-linux/lib
    # 2024-06-26 07:18:43.736839: E tensorflow/stream_executor/cuda/cuda_driver.cc:282] failed call to cuInit: UNKNOWN ERROR (303)
    # 2024-06-26 07:18:43.737283: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (05ba275a9be5): /proc/driver/nvidia/version does not exist
    # 2024-06-26 07:18:43.762300: I tensorflow/core/platform/profile_utils/cpu_utils.cc:109] CPU Frequency: 2918410000 Hz
    # 2024-06-26 07:18:43.763492: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x4671360 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
    # 2024-06-26 07:18:43.763553: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
    # INFO:tensorflow:Froze 54 variables.
    # INFO: 06/26/2024 07:18:45.354419 graph_util_impl.py:334 [TFLite_Parser] Froze 54 variables.
    # INFO:tensorflow:Converted 54 variables to const ops.
    # INFO: 06/26/2024 07:18:45.377763 graph_util_impl.py:394 [TFLite_Parser] Converted 54 variables to const ops.
    # 2024-06-26 07:18:45.434623: I tensorflow/tools/graph_transforms/transform_graph.cc:318] Applying strip_unused_nodes
    # 2024-06-26 07:18:45.444534: I tensorflow/tools/graph_transforms/transform_graph.cc:318] Applying fold_constants
    # 2024-06-26 07:18:45.485948: I tensorflow/tools/graph_transforms/transform_graph.cc:318] Applying remove_nodes
    # 2024-06-26 07:18:45.489095: I tensorflow/tools/graph_transforms/remove_nodes.cc:78] Skipping replacement for Identity
    # 2024-06-26 07:18:45.489224: I tensorflow/tools/graph_transforms/remove_nodes.cc:78] Skipping replacement for Identity_1
    # 2024-06-26 07:18:45.493166: I tensorflow/tools/graph_transforms/remove_nodes.cc:78] Skipping replacement for Identity
    # 2024-06-26 07:18:45.493280: I tensorflow/tools/graph_transforms/remove_nodes.cc:78] Skipping replacement for Identity_1
    # 2024-06-26 07:18:45.500988: I tensorflow/tools/graph_transforms/transform_graph.cc:318] Applying remove_attribute
    # 2024-06-26 07:18:45.502429: I tensorflow/tools/graph_transforms/transform_graph.cc:318] Applying strip_unused_nodes
    # 2024-06-26 07:18:45.504371: I tensorflow/tools/graph_transforms/transform_graph.cc:318] Applying fold_constants
    # 2024-06-26 07:18:45.511826: I tensorflow/tools/graph_transforms/transform_graph.cc:318] Applying sort_by_execution_order
    # INFO: 06/26/2024 07:18:45.559772 tf_lite_v2.py:355 [TFLite_Parser] Reconstructed and optmized protobuf can be found here: /home/docker//reconstructed_pb_model/converted_model_reconstructed.pb
    # WARN: 06/26/2024 07:18:45.560278 tf_lite_v2.py:375 [TFLite_Parser]
    # TFLite model converted to a frozen protobuf but cannot be validated since loading the TFLite model using Interpreter fails. Please check the version of the TFLite model.
    # Reconstructed frozen protobuf is saved in the reconstructed_pb_models/ folder. Use the /home/docker//reconstructed_pb_model/converted_model_reconstructed.pb model for porting.
    # *** (info) importing amba_cnn_py @ /usr/local/amba-cv-tools-basic.2.5.6.0.1245.ubuntu-20.04/cv2/tv2/release/AmbaCnn/cv2.basic.2.5.6.0.1245.ubu2004/python/amba_cnn_py
    # *** (info) setting project cv22
    # opened session 6536 on libambacnn cv2.basic.2.5.6.0.1245.ubu2004 (9322cec*0), at 2024-06-26 07:18:45
    # libambacnn session config: target_device = cv22, gpu_id = -1, mode = default, split = False
    # [info] drc proc time  =  157.628 s @ 100 %
    # [info] drc num frames = 100
    # [info] drc proc time  = 157.628493 s
    # [info] drc pproc time = 0.001153 s
    # [info] drc total time = 290.714981 s
    # [info] dr2 time = (   1.515 calc +    1.224 stat) s x 100 frames
    

    vas -auto -show-progress out_car_human_model/car_human_model.vas
    # car_human_model: EXPAND 68 (expansion progress: 100%)
    # car_human_model: DONE expansion
    # car_human_model: DONE validation
    # car_human_model: DONE analyzing
    # car_human_model: DONE opt
    # car_human_model: DONE buffering
    # car_human_model: SPLIT 0 (split progress: 46%)
    # car_human_model: SPLIT 1 (split progress: 55%)
    # car_human_model: SPLIT 2 (split progress: 100%)
    # car_human_model: DONE split
    # car_human_model: DONE all
    

    cavalry_gen -d vas_output -f car_human_model_cavalry.bin
    # Using cavalry_gen version latest
    # 
    # Save to file car_human_model_cavalry.bin with file size 3319784.
    

  • Test model on CV25 camera

    larod-client -g ./car_human_model_cavalry2.bin  -c ambarella-cvflow -R 10 -w 5 -i ''
    # 2024-06-26T17:54:07.971 Connecting to larod...
    # 2024-06-26T17:54:07.981 Connected
    # 2024-06-26T17:54:08.030 ERROR: When loading model synchronously (-2): Could not load model: Could not initialize net
    

• Resources

  • https://mega.nz/file/Fnl2mAab#5Pq8zQRyhuKy2X8rWPPSTZt43ma3PpAzleoRDaAB0h0

[AtsushiYokokawa]

Upload as additional information.

I compared the model output by tensorflow-to-larod-cv25 and the downloaded model using CVTool's <tf_print_graph_summary.py>.

I don't know where the cause is.

Where is the error in the procedure for running it on CV25?

convert_tflite_summary.tar.gz

Thank you.

[AtsushiYokokawa]

I looked into it from a different perspective.

I compiled it using Ambarella's CVTool using a tflite format model downloaded based on the URL in the Dockerfile.

As a result, it still couldn't work.

This leads me to believe that the CVTool command line may be incorrect.

• Resources
  • https://mega.nz/file/smVHnQJQ#rBLPNOqpMxLpU2jlKx6LVOuqNeEmr1h98m6E3XTkt18

[AtsushiYokokawa]

I was able to solve the problem.

I was able to solve the problem by compiling using CVTool2.4.x.

I confirmed the operation with tensorflow model and onnx model.

It seems that AXIS OS is probably not compatible with the latest CVTool.

I think it is necessary to specify the version of CVTool to be used in the README of tensorflow-to-larod-cv25, or to apply a patch to AXIS OS to ensure compatibility with the latest CVTool.

I will create an issue from this discussion, so please check it out.