onnxruntime

Description

This issue is to create the TabNet model and add it to the basic model zoo. TabNet is a good example of a deep learning model that will work with the tabular modality. Then, it can be trained or tested with an implementation of the CsvDataset such as AirfoilRandomAccess or AmesRandomAccess.

References

• Paper: [TabNet: Attentive Interpretable Tabular Learning](htt

这个issue主要讲一下，如何把你自己的模型添加到lite.ai.toolkit。lite.ai.toolkit集成了一些比较新的基础模型，比如人脸检测、人脸识别、抠图、人脸属性分析、图像分类、人脸关键点识别、图像着色、目标检测等等，可以直接用到具体的场景中。但是，毕竟lite.ai.toolkit的模型还是有限的，具体的场景下，可能有你经过优化的模型，比如你自己训了一个目标检测器，可能效果更好。那么，如何把你的模型加入到lite.ai.toolkit中呢？这样既能用到lite.ai.toolkit一些已有的算法能力，也能兼容您的具体场景。这个issue主要是讲这个问题。大家有疑惑的可以提在这个issue，我会尽可能回答~

is:issue is:open 请问，方便提供一下onnx文件导出的代码文件吗？用model文件夹里面跟随的文件输出结果用ncnn推理结果不对

I used following commad to export the ONNX models, and I use the 5.0 tag of ultralytics/yolov5 to train the model.pt. It raises an AttributeError: conv object has no attribute weight. How can I do for this error?

python tools/export_model.py --checkpoint_path model.pt --size_divisible 32

_Originally posted by @Deronjey in zhiqwang/yolov5-rt-stack#159 (comment)

A next step for better generation is to implement a beam search for the generation. An example of it can be seen on the huggingface repo here, and this would need adding such a function to the GenerativeT5 model in onnxt5/models.py