Course1 Week 4Programming Assignment: Deep Neural Network - Application Exercise 1 - two_layer_model

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

I’m in trouble, I get this error message below. But I could get expected outputs for cost and accuracy. And after I submitted that, I couldn’t pass. Please help me, thank you in advance.

Cost after first iteration: 0.693049735659989
Cost after iteration 1: 0.6915746967050506
Cost after iteration 1: 0.6915746967050506
Cost after iteration 1: 0.6915746967050506
Cost after iteration 2: 0.6899956541494738
Error: Wrong output for variable W1.
Error: Wrong output for variable b1.
Error: Wrong output for variable W2.
Error: Wrong output for variable b2.
3 Tests passed
1 Tests failed

AssertionError Traceback (most recent call last)
in
3 print("Cost after first iteration: " + str(costs[0]))
4
----> 5 two_layer_model_test(two_layer_model)

~/work/release/W4A2/public_tests.py in two_layer_model_test(target)
75 ]
76
—> 77 multiple_test(test_cases, target)
78
79

~/work/release/W4A2/test_utils.py in multiple_test(test_cases, target)
140 print(‘\033[92m’, success," Tests passed")
141 print(‘\033[91m’, len(test_cases) - success, " Tests failed")
→ 142 raise AssertionError(“Not all tests were passed for {}. Check your equations and avoid using global variables inside the function.”.format(target.name))
143

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

2

Hi @Koyo_Fujii ,

Please make sure your code uses the input parameters defined in the two_layer_model() when passing parameters to calling functions.

3

Hi @Koyo_Fujii

This error because the implementation of function two_layer_model …please make sure you implemented it in the correct way

please feel free to ask any questions,
Thanks,
Abdelrahman

4

One specific thing to check is that you did not call the “deep” version of the initialization routine in the two layer case. There is a separate initialization function for the two layer case and it behaves slightly differently in this assignment.

1 Like
5

It was because I was using " learning_rate=0.0075" in the two layer model , I corrected it to just “learning_rate” and could implement . thank you for your advices!