InferPy
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record Keras models created in the context of a probmodel
Consider the following model:
@inf.probmodel
def vae(k, d0, d, decoder):
with inf.datamodel():
z = inf.Normal(tf.ones(k), 1,name="z")
x = inf.Normal(decoder(d0, d, z), 1, name="x")
def decoder(d0, d, z):
return inf.keras.Sequential([
tf.keras.layers.Dense(d0),
tf.keras.layers.Dense(d, activation="relu"),
], name="decoder")(z)
p = vae(k=2, d0=100, d=28*28, decoder=decoder)
We might need to access to the keras model defined:
>>> p.prior().keras()
{'decoder': <tensorflow.python.keras.engine.sequential.Sequential at 0x12d722668>}
>>> p.posterior().keras()
{'decoder': <tensorflow.python.keras.engine.sequential.Sequential at 0x12e842634>}
Like with RV, these could be the prior or posterior models.