how to compute norm.ppf() in tensorflow/Keras?

Question

I want to use inverse of cumulative distribution function (cdf) which can be done using norm.ppf() from scipy https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.norm.html#scipy.stats.norm inside a layer of a tf/keras model architecture.

Answer 1

As per documentation, tfp.distribution.Normal does have a method for calculating ppf (percent point function). It's called quantile:

scipy.stats.norm(loc=0, scale=1).ppf(0.95)

Output:

1.6448536269514722

Tensorflow:

tfp.distributions.Normal(loc=0, scale=1).quantile(0.95)

Output:

<tf.Tensor: shape=(), dtype=float32, numpy=1.6448536>