Week 2 Exercise 7

Course Q&A Deep Learning Specialization Neural Networks and Deep Learning
1

Pretty stuck, any pointers?

{moderator edit - solution code removed}

t_x = np.array([[9, 2, 5, 0, 0],

            [7, 5, 0, 0 ,0]])

print("softmax(x) = " + str(softmax(t_x)))

​

softmax_test(softmax)

softmax(x) = [[5.06442745e+02 4.61816006e-01 9.27582244e+00 6.25000000e-02
6.25000000e-02]
[9.13860965e+01 1.23677633e+01 8.33333333e-02 8.33333333e-02
8.33333333e-02]]
Error: Wrong output
2 Tests passed
1 Tests failed

AssertionError Traceback (most recent call last)
in
3 print("softmax(x) = " + str(softmax(t_x)))
4
----> 5 softmax_test(softmax)

~/work/release/W2A1/public_tests.py in softmax_test(target)
195 ]
196
→ 197 test(test_cases, target)
198
199 def L1_test(target):

~/work/release/W2A1/test_utils.py in test(test_cases, target)
24 print(‘\033[92m’, success," Tests passed")
25 print(‘\033[91m’, len(test_cases) - success, " Tests failed")
—> 26 raise AssertionError(“Not all tests were passed for {}. Check your equations and avoid using global variables inside the function.”.format(target.name))

AssertionError: Not all tests were passed for softmax. Check your equations and avoid using global variables inside the function.

2

You are summing x, but take another look at what is in the denominator of the formula for softmax: the sums are of e^x, right?

6 Likes
3

Thanks for the tip, I was making the same mistake and not understanding why one test fails. Now I wonder how the other two tests passed in the first place :slight_smile:

4

You can examine the test by clicking “File → Open” and then open the file public_tests.py. What I will guess you find is that the first two tests check the data type and shape of the answer. That is a pretty low bar for full correctness. :nerd_face: