# https://deeplearningcourses.com/c/deep-learning-prerequisites-the-numpy-stack-in-python

# https://www.udemy.com/deep-learning-prerequisites-the-numpy-stack-in-python

from __future__ import print_function, division

from builtins import range

# Note: you may need to update your version of future

# sudo pip install -U future

import numpy as np

from datetime import datetime

a = np.random.randn(100)

b = np.random.randn(100)

T = 100000

def slow_dot_product(a, b):

result = 0

for e, f in zip(a, b):

result += e*f

return result

t0 = datetime.now()

for t in range(T):

slow_dot_product(a, b)

dt1 = datetime.now() - t0

t0 = datetime.now()

for t in range(T):

a.dot(b)

dt2 = datetime.now() - t0

print("dt1 / dt2:", dt1.total_seconds() / dt2.total_seconds())