I have completed all the steps still I am getting this error There is a mistake in the backward propagation! difference = 1.0 Error: Wrong output 0 Tests passed 1 Tests failed AssertionError Traceback (most recent call last) in 6 assert not(type(difference) == np…

Hi, @Manasvi : 6 assert not(type(difference) == np.ndarray), “You are not using np.linalg.norm for numerator or denominator” There seems to be something wrong in the way you computed either numerator or denominator. Did you use np.linalg.norm? Double-check that first and let me know if you can’t …

I get this error as well. I’ve attempted to rewrite the code and check for typos, but I think it should match the steps described in the task

I had the same problem and thought it was something to do with usage of np.linalg.norm. But it turned out I was using the wrong operation in denominator (- instead of +). You also should check carefully the dimension of matrices

yes, it is the same error. AssertionError Traceback (most recent call last) in 6 assert not(type(difference) == np.ndarray), “You are not using np.linalg.norm for numerator or denominator” 7 ----> 8 gradient_check_n_test(gradient_check_n, parameters, gradients, X, …

Hi, @lufrocea . Check the expression for gradapprox[i] in gradient_check_n and be careful with operator precedence . Hint: ()

Thanks!!! It worked. I found the error

I’m getting the same error and none of the other solutions have worked for me. I’ve double checked that I’m using np.linalg.norm as well as the precedence for the difference. Any suggestions as to what else I can check for?

Fixed for @srkrish2 too. The error was caused by this . Good luck with the rest of the course!

Gradient Checking

Course Q&A Deep Learning Specialization Improving Deep Neural Networks: Hyperparameter tun

nramon June 1, 2021, 1:35pm 6

Fixed for @Erlend. Good luck with the rest of the course

A common mistake I’ve seen is using the same expression to compute theta_plus[i] and theta_minus[i], probably because it was copied and pasted.

Gradient Checking, doubt about failed code checking on submission

Course 2: week 1 (exercise :4 )

Topic		Replies	Views
DLS Course 2 Week 1- Assignment 3- Exercise 4- gradient_check_n Improving Deep Neural Networks: Hyperparameter tun coursera-platform	5	1147	July 5, 2021
Course-2 : Week -1 Assignments, Programming Assignment: Gradient Checking Improving Deep Neural Networks: Hyperparameter tun coursera-platform	2	693	August 5, 2021
Week 1 Gradient Checking gradient_check_n Improving Deep Neural Networks: Hyperparameter tun coursera-platform	7	1904	November 12, 2023
HELP! Can't find the bug in Gradient_Checking Improving Deep Neural Networks: Hyperparameter tun coursera-platform	4	794	March 15, 2022
C2 W1 Exercise 4 - gradient_check_n Improving Deep Neural Networks: Hyperparameter tun coursera-platform	3	458	October 4, 2023

Gradient Checking

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