Test resetting model parameters via `workload.init_model_fn()` during training

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According to the rules, it is expected that the model parameters can be reset by calling workload.init_model_fn(). However, creating a new model instance, like it is currently done in the MNIST PyTorch workload, might lead to out-of-memory errors, if the loss/optimizer and potentially other objects are not deleted properly (also described here). Hence, resetting model paramerters during training should be tested and workload.init_model_fn() should potentially be adjusted.