[Python] How to enable and disable Intel MKL in numpy Python?

I want to test and compare Numpy matrix multiplication and Eigen decomposition performance with Intel MKL and without Intel MKL.

I have installed MKL using pip install mkl (Windows 10 (64-bit), Python 3.8).

I then used examples from here for matmul and eigen decompositions.

How do I now enable and disable MKL in order to check numpy performance with MKL and without it?

Reference code:

import numpy as np
from time import time

def matrix_mul(size, n=100):
# reference: https://markus-beuckelmann.de/blog/boosting-numpy-blas.html
np.random.seed(112)
a, b = np.random.random((size, size)), np.random.random((size, size))
t = time()
for _ in range(n):
np.dot(a, b)
delta = time() - t
print('Dotted two matrices of size %dx%d in %0.4f ms.' % (size, size, delta / n * 1000))


def eigen_decomposition(size, n=10):
np.random.seed(112)
a = np.random.random((size, size))
t = time()
for _ in range(n):
np.linalg.eig(a)
delta = time() - t
print('Eigen decomposition of size %dx%d in %0.4f ms.' % (size, size, delta / n * 1000))

#Obtaining computation times:

for i in range(20):
eigen_decomposition(500)

for i in range(20):
matrix_mul(500)

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