pymc.Minibatch.eval

Minibatch.eval(inputs_to_values=None)

Evaluate the Variable.

Parameters

inputs_to_values

A dictionary mapping Aesara Variables to values.

Notes

eval() will be slow the first time you call it on a variable – it needs to call function() to compile the expression behind the scenes. Subsequent calls to eval() on that same variable will be fast, because the variable caches the compiled function.

This way of computing has more overhead than a normal Aesara function, so don’t use it too much in real scripts.

Examples

>>> import numpy as np
>>> import aesara.tensor as at
>>> x = at.dscalar('x')
>>> y = at.dscalar('y')
>>> z = x + y
>>> np.allclose(z.eval({x : 16.3, y : 12.1}), 28.4)
True

We passed eval() a dictionary mapping symbolic Aesara Variables to the values to substitute for them, and it returned the numerical value of the expression.