I have trained cnn model that was originally wrote on pytorch and saved in .pt
How can I analyze this model with Innvestigate tool? The tool is based on TensorFlow.
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I have a trained model saved from fastText. The model is saved with model.save_model("model.bin")
I need to load the model to BigQuery ML and run it there. BigQuery ML allows to import a TensorFlow model and that is why I want to convert my fastText model to a TensorFlow model. I have searched a lot and am conceived that it can be done but I have not really found a clear explanation on how to do it. Any help would be appreciated
TensorFlow Hub is a repository for pre-trained models. Model Garden (Model Zoo) also keeps SOTA models and provides facilities for downloading and leveraging its models like TfHub, and both of them are created by TensorFlow.
Why did Tensorflow make two concepts for a model repository?
When should we use TfHub for retrieving a well-known model, and when should we use Model Garden to download a model? What is the difference between them?
TF Hub provides trained models in SavedModel, TFLite, or TF.js format. These artifacts can be used for inference and some can be used in code for fine-tuning. TF Hub does not provide modeling library code to train your own models from scratch.
Model Garden is a modeling library for training BERT, image classification models, and more. Model Garden provides code for training your own models from scratch as well as some checkpoints to start from.
How do I find more info on how the ssd_mobilenet_v1 tflite model on TFHub was trained?
Was it trained in such a way that made it easy to convert it to tflite by avoiding certain ops not supported by tflite? Or was it trained normally, and then converted using the tflite converter with TF Select and the tips on this github issue?
Also, does anyone know if there's an equivalent mobilenet tflite model trained on OpenImagesV6? If not, what's the best starting point for training one?
I am not sure about about the exact origin of the model, but looks like it does have TFLite-compatible ops. From my experience, the best place to start for TFLite-compatible SSD models is with the TF2 Detection Zoo. You can convert any of the SSD models using these instructions.
To train your own model, you can follow these instructions that leverage Google Cloud.
I want to know analyze the CNN in NetScope CNN analyzer, but unfortunately it only accepts caffe prototxt files. So is there any way to convert the tensorflow frozen model to caffe model to generate a prototxt file?
I want to implements a faster-rcnn model using distributed tensorflow, But I have difficult to load a pretrained vgg model,How to do it? thanks
The TensorFlow tutorial on retraining inception is a good start to read. Then try to reproduce what it does starting from an already trained vgg model.