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FAQ

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1. Error installing whl package

1.1 xxx.whl is not a supported wheel on this platform

A: Upgrade pip >= 20.3.

pip install --upgrade pip

2. Compile-time errors

2.1 Compile model reported error "System.NotSupportedException: Not Supported *** op: XXX"

A: This exception indicates that there are operators, XXX, that are not yet supported. You can create a issue in nncase Github Issue. In the current directory ***_ops.md, you can view the operators already supported in each inference framework.

If 'XXX' belongs to quantization-related operators such as FAKE_QUANT, DEQUANTIZE, QUANTIZE, it indicates that the current model is a quantized model, and 'nncase' does not currently support such models, please compile kmodel using a floating point model.

2.2 "The configured user limit (128) on the number of inotify instances has been reached, or the per-process limit on the number of open file descriptors has been reached."

A: Use sudo gedit /proc/sys/fs/inotify/max_user_instances to change 128 to a larger value.

2.3 RuntimeError: Failed to initialize hostfxr

A：Need to install dotnet-sdk-7.0.

  • Linux:

    sudo apt-get update
sudo apt-get install dotnet-sdk-7.0

  • Windows: Refer to MicroSoft official website.

2.4 "KeyNotFoundException: The given key 'K230' was not present in the dictionary"

A: Need to install nncase-kpu.

  • Linux: pip install nncase-kpu
  • Windows: Sorry for that you need to download the whl package in nncase github repo and install it manually.

Before install nncase, please make sure that the version of nncase is consistent with the version of nncase-kpu.

> pip show nncase | grep "Version:"
 Version: 2.8.0
(Linux)  > pip install nncase-kpu==2.8.0
(Windows)> pip install nncase_kpu-2.8.0-py2.py3-none-win_amd64.whl

3. Runtime errors

3.1 When inferring, the error nncase.simulator.k230.sc: not found occurs.

Or these situations:

  • "nncase.simulator.k230.sc: Permision denied."
  • "Input/output error."

A: Make sure that the path of the nncase installation is added to the PATH environment variable. You need to check whether the versions of nncase and nncase-kpu are the same.

root@a52f1cacf581:/mnt# pip list | grep nncase
nncase 2.1.1.20230721
nncase-kpu 2.1.1.20230721

If inconsistent, install the same version of the Python package pip install nncase==x.x.x.x nncase-kpu==x.x.x.x

4. Runtime error on k230 development board

4.1 data.size_bytes() == size = false (bool)

A: The above situation is usually caused by an error in the input data file of the app inference, which does not match the model input shape or the model input type. Especially when pre-processing is configured, you need to check input_shape and input_type of input data, after adding pre-processing operation, relevant nodes are added to the model, and the input node will also be changed. If input_shape , input_type are different from the original model, the newly configured shape , type should be used to generate input data.

4.2 std::bad_alloc

A: Usually it is caused by memory allocation failure, you can do the following troubleshooting.

  • Check whether the generated kmodel exceeds the currently available system memory.
  • Check App for memory leaks.

4.3 throw error when load model

The exception terminate: Invalid kmodel is thrown when attempting to load a kmodel as bellow.

interp.load_model(ifs).expect("Invalid kmodel");

A：The issue arises due to a mismatch between the nncase version used when compiling the kmodel and the current SDK version. Please refer to the SDK-nncase Version Correspondence for a lookup, and follow the Update the nncase Runtime Library Guide to resolve the problem.