How to load metadata from MongoDB and convert it to a TensorFlow dataset efficiently?
I have a problem that all metadata for my dataset is stored in MongoDB and I have to read it, validate it, then convert it into a TensorFlow dataset (plus do some preprocessing optionally). I looked into tfio.experimental.mongodb.MongoDBIODataset, but unfortunately you cannot specify a query inside of it. I’m currently tring tf.py_function, but it has some strong limitations. I was wondering if there’s any better way to load documents efficiently.