Convolution as Matrix Multiplication

CNNMatMul.py

from __future__ import division
from sympy import *
x, y, z, t = symbols('x y z t')
k, m, n = symbols('k m n', integer=True)
f, g, h = symbols('f g h', cls=Function)
init_printing()

a, b, c, d, e, f, g, h, i, v, x, y, z = symbols('a, b, c, d, e, f, g, h, i, v, x, y, z', real=True)
M = Matrix([[a, b, c], [d, e, f], [g, h, i]])
K = Matrix([[v, x], [y, z]])
Mc =  Matrix([[a, b, d, e], [b, c, e, f], [d, e, g, h], [e, f, h, i]])
Kc = Matrix([v, x, y, z])
mc_vars = [a, b, c, d, e, f, g, h, i]
kc_vars = [v, x, y, z]

import random

mc_rand_vars = [random.random() for _ in range(len(mc_vars))]
kc_rand_vars = [random.random() for _ in range(len(kc_vars))]
M1 = M.subs({x: val for x, val in zip(mc_vars, mc_rand_vars)})
K1 = K.subs({x: val for x, val in zip(kc_vars, kc_rand_vars)})
Mc1 = Mc.subs({x: val for x, val in zip(mc_vars, mc_rand_vars)})
Kc1 = Kc.subs({x: val for x, val in zip(kc_vars, kc_rand_vars)})
a, b = M1.condition_number(), K1.condition_number()
c, d = Mc1.condition_number(), Kc1.condition_number()