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+ # https://deeplearningcourses.com/c/deep-learning-prerequisites-the-numpy-stack-in-python
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+ # https://www.udemy.com/deep-learning-prerequisites-the-numpy-stack-in-python
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+
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+ from __future__ import print_function , division
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+ from builtins import range
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+ # Note: you may need to update your version of future
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+ # sudo pip install -U future
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+
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+
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+ import numpy as np
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+ from datetime import datetime
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+
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+ a = np .random .randn (100 )
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+ b = np .random .randn (100 )
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+ T = 100000
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+
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+ def slow_dot_product (a , b ):
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+ result = 0
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+ for e , f in zip (a , b ):
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+ result += e * f
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+ return result
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+
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+ t0 = datetime .now ()
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+ for t in range (T ):
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+ slow_dot_product (a , b )
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+ dt1 = datetime .now () - t0
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+
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+ t0 = datetime .now ()
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+ for t in range (T ):
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+ a .dot (b )
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+ dt2 = datetime .now () - t0
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+
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+ print ("dt1 / dt2:" , dt1 .total_seconds () / dt2 .total_seconds ())
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