Week 4 Part 1 Exercise 8

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

Relevant piece of code:
dZ = sigmoid_backward(dA, activation_cache)
dA_prev, dW, db = linear_backward(dZ, cache)

dZ = relu_backward(dA, activation_cache)
dA_prev, dW, db = linear_backward(dZ, cache)

When running the code, I receive the following error:

ValueError: not enough values to unpack (expected 3, got 2)

I don’t know what I’m doing wrong. Thanks in advance for the help.

2

Hi, that error seems to indicate that the function linear_backward is returning just two values when you are expecting to receive 3. It is a bit odd error as in exercise 7 you are also using the function:

t_dA_prev, t_dW, t_db = linear_backward(t_dZ, t_linear_cache)

Is that exercise passing all tests? If that’s the case, could you please post the full trace of the error? (not your code, the output error).

3

ValueError Traceback (most recent call last)
in
1 t_dAL, t_linear_activation_cache = linear_activation_backward_test_case()
2
----> 3 t_dA_prev, t_dW, t_db = linear_activation_backward(t_dAL, t_linear_activation_cache, activation = “sigmoid”)
4 print("With sigmoid: dA_prev = " + str(t_dA_prev))
5 print("With sigmoid: dW = " + str(t_dW))

in linear_activation_backward(dA, cache, activation)
35
36 dZ = relu_backward(dA, activation_cache)
—> 37 dA_prev, dW, db = linear_backward(dZ, cache)
38
39 # YOUR CODE ENDS HERE

in linear_backward(dZ, cache)
14 db – Gradient of the cost with respect to b (current layer l), same shape as b
15 “”"
—> 16 A_prev, W, b = cache
17 m = A_prev.shape[1]
18

ValueError: not enough values to unpack (expected 3, got 2)

Sure. I guess that I’m using interchangeably “cache” in relu_backward and in linear_backward when they are not. One of cache has 3 components and the other 2. However, I don’t know how .to feed the linear_backward function (can’t find the corresponding cache in the exercise).

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4

I’ve already figured it out. Thank anyway.

5

I have the same error and my exercises 7 and 8 passed all tests.

6

Hi, I got the exact error message for exercise 8 and I have passed all test in exercise 7. May I know how I could fix it? thanks

7

I had the same too.
You have to pass " linear_cache " as a parameter.
Good luck :relaxed:

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