Hello.
Recently I downloaded the regression model for tabular data to my machine.
I know how to run the container image and the model inside of it, but I want to avoid it due to latency (http communication and Windows-Linux overhead).
I replicated the libraries stated in 'environment.json' file that comes with model files.
Tensorflow, struct2tensor, tensorflow-addons.
Then with a python script I triggered the prediction to the 001/saved_model.pb.
No matter what I do, I end up with 'KeyError:'DecodeProtoSparseV4''.
Can anyone help me to fix it? It's obviously some discrepancy inside the model processes.
Maybe creating a custom container for cloud training process can help? If I create a custom cloud container with environment of my choice, then it's easier to replicate it on my local machine?
Anyone on this please? It seems like DecodeProtoSparseV4 is custom process that I can't replicate by installing *all* packages used in container uri, not only TensorFlow related.
Any thoughts please on how I can solve it? It's crucial for me.
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