6.2: Converting Python saved models with the TensorFlow.js command line converter

When entering the command: "!pip3 install tensorflowjs" I got the following error: "ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
pydantic 2.2.1 requires typing-extensions>=4.6.1, but you have typing-extensions 4.5.0 which is incompatible.
pydantic-core 2.6.1 requires typing-extensions!=4.7.0,>=4.6.0, but you have typing-extensions 4.5.0 which is incompatible.
statsmodels 0.14.0 requires packaging>=21.3, but you have packaging 20.9 which is incompatible.
xarray 2023.7.0 requires packaging>=21.3, but you have packaging 20.9 which is incompatible.
Successfully installed flax-0.6.2 keras-2.13.1 packaging-20.9 tensorboard-2.13.0 tensorflow-2.13.0 tensorflow-decision-forests-1.5.0 tensorflow-estimator-2.13.0 tensorflowjs-4.10.0 typing-extensions-4.5.0 wurlitzer-3.0.3
WARNING: The following packages were previously imported in this runtime:
[keras,packaging,tensorboard,tensorflow]
You must restart the runtime in order to use newly installed versions."
I had to manually install the correct versions of the packages to get it to work (just like I had to do for my WSL2 install).

Although I've been enjoying this series, it is disheartening that this particular video that was made by Google developers and uses Google Colab no longer works after only 3 months. When following the instructions on Colab, the code returns a "TF-TRT Warning: Could not find TensorRT" error when attempting to run the tensorflowjs_converter. I can't find any resolutions to this issue, and can't move forward if we're going to be building on these concepts in the next video.

Great tutorial, I'd add that GraphModel is not fine-tunable, so you can not re-train it. The pb models that convert to GraphModels are then only useful for inference (to test the model).

I think it is said but just to make it obvious, if you want to fine tune / re-train / use transfer learning, you need Layer Models and for that you need "tf-models-here.h5" or the js versions.