DLS course 1 Week 4 programming assignment one

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

Hi There,

I cant figure out why I’m getting this bug. It has something to do with the caching. Not sure if I’m allowed to share my code or not.

[ValidateApp | INFO] Validating ‘/home/jovyan/work/submitted/courseraLearner/W4A1/Building_your_Deep_Neural_Network_Step_by_Step.ipynb’
[ValidateApp | INFO] Executing notebook with kernel: python3
Tests failed on 1 cell(s)! These tests could be hidden. Please check your submission.

The following cell failed:

t_AL, t_Y_assess, t_caches = L_model_backward_test_case()
grads = L_model_backward(t_AL, t_Y_assess, t_caches)

print("dA0 = " + str(grads['dA0']))
print("dA1 = " + str(grads['dA1']))
print("dW1 = " + str(grads['dW1']))
print("dW2 = " + str(grads['dW2']))
print("db1 = " + str(grads['db1']))
print("db2 = " + str(grads['db2']))

L_model_backward_test(L_model_backward)

The error was:

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-20-3ace16762626> in <module>
      1 t_AL, t_Y_assess, t_caches = L_model_backward_test_case()
----> 2 grads = L_model_backward(t_AL, t_Y_assess, t_caches)
      3 
      4 print("dA0 = " + str(grads['dA0']))
      5 print("dA1 = " + str(grads['dA1']))

<ipython-input-19-ecec27d3ac08> in L_model_backward(AL, Y, caches)
     59         # YOUR CODE STARTS HERE
     60         current_cache = caches[l]
---> 61         dA_prev_temp, dW_temp, db_temp = linear_activation_backward(dAL, cu...
     62         grads["dA" + str(l)] = dA_prev_temp
     63         grads["dW" + str(l + 1)] = dW_temp

<ipython-input-17-32d5362f61a8> in linear_activation_backward(dA, cache, activation...
     22         # dA_prev, dW, db =  ...
     23         # YOUR CODE STARTS HERE
---> 24         dZ= relu_backward(dA, activation_cache)
     25         dA_prev, dW, db =linear_backward(dZ, linear_cache)
     26         # YOUR CODE ENDS HERE

~/work/submitted/courseraLearner/W4A1/dnn_utils.py in relu_backward(dA, cache)
     54 
     55     # When z <= 0, you should set dz to 0 as well.
---> 56     dZ[Z <= 0] = 0
     57 
     58     assert (dZ.shape == Z.shape)

IndexError: boolean index did not match indexed array along dimension 0; dimension ...
2

That means that the dA value and the activation cache value that are being passed down to linear_activation_backwards do not match. It looks like within the loop over the hidden layers, you are always passing dAL, which is only for the output layer, right?

3

Thanks for the clarification!