How to predict on hold out set with variational api

Questions
3

Hi,
I had not seen it but tried it.
This works:

input_var = theano.shared(X_train[:5000, …].astype(np.float64))
target_var = theano.shared(y_train[:5000, …].astype(np.float64))

input_var_mb = pm.Minibatch(X_train, batch_size=32, dtype=np.float64)
target_var_mb = pm.Minibatch(y_train, batch_size=32, dtype=np.float64)

neural_network = build_ann(GaussWeights())

with neural_network:
inference=pm.ADVI()
mean_field = pm.fit(n=15000, method=inference, score=True, more_replacements={input_var: input_var_mb, target_var:target_var_mb})

trace = mean_field.sample(500)

with neural_network:
ppc = pm.sample_posterior_predictive(trace)

input_var.set_value(X_test[:5000, …].astype(np.float64))
target_var.set_value(y_test[:5000, …].astype(np.float64))

with neural_network:
ppc = pm.sample_posterior_predictive(trace)

Thanks

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