Load multiple Keras models in different processes
I still don't know the exact cause of the problem. However, I found out that my main process was loading a keras model and removing that solved my problem. I can now have multiple models running in parallel.
I have several trained Keras models, weights stored in h5 files using keras.models.save_model. They do not have the same architecture.
My goal is to load all of them in separate processes and be able to predict. I currently try doing this using a class which stores a TensorFlow session and graph object. I then use with statements at loading time and prediction time to prevent interference with any global variables.
I can create my (empty) Keras Sequential model without problems, but when I call its load_weights function, the process just freezes.
Setups with Graph and Session objects I tried:

specific Graph and Session -> process freezes on load_weights
specific Graph only -> "TypeError: Cannot interpret feed_dict key as Tensor"
specific Session only -> process freezes on load_weights

I have been through most of the related answers on SO but have not been able to find a solution or even someone with the same problem.
Thanks for your help!