Week 2 lab I’m having some trouble with the week 2 lab. sigmoid initialize_with_zeros propogate optimize predict are all working. All tests passed, expected output matched. In particular, for “optimize” I’m getting this output (this is not the code I wrote, this is the output to the test for…

Here: [image] Should be costs with a s at the end.

Hi @s-dorsher , Since your optimize function is working correctly, the issue can be within model or how costs are accumulated. Make sure you’re not modifying the cost function outside of optimize. Also, keep in mind that different train-test splits and weight initializations can lead to different r…

[image] saifkhanengr: Your model code should work for any number of iterations, not just 100. One common mistake in this exercise is to hard-code the number of iterations and learning rate when calling optimize function inside the model function. You should avoid it. I’m confused. Specificat…

[image] Alireza_Saei: Make sure you’re not modifying the cost function outside of optimize. Thank you. I’m not. [image] Alireza_Saei: Also, keep in mind that different train-test splits and weight initializations can lead to different results. I agree, they should. The irony is that t…

Here’s my sort of analysis When you pass w to optimize, deep copy makes a pointer to w that ties the variable associated with the argument to the function to the local variable inside the function via a pointer. Because the local variable is stored in a dict at the end, the argument to the function…

[image] s-dorsher: Within it, I call optimize, as you say. As you say, I did not and do not hard code the number of iterations. The following is what I did. num_iterations=num_iterations Yes, this is the correct way to do it when you call optimize function inside the model fucntion. Same for…

[image] s-dorsher: Because w and b are fixed, the cost function can also only be the same. We use optimize function to update the parameters. So, they are not fixed.

[image] saifkhanengr: We use optimize function to update the parameters. So, they are not fixed. I am completely aware that is how it would work if it were working correctly. It is basically solving a differential equation, though with some added complexity. However, it is obviously not worki…

[image] saifkhanengr: You don’t need to do copy or deep copy of w and b. I’m not. This is built into optimize in the part I’m not allowed to edit. Can I remove it then? Shown below [image] Yes, without revealing all of my code, I have w,b = initialize_with_zeros(shape_that_is_consistent_w…

[image] s-dorsher: params, grads, cost=optimize(w,b,...) As Raymond mentioned, it should be costs. params, grads, costs = ...

Having some trouble on week 2 lab

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

rmwkwok February 8, 2025, 12:18pm 10

Hello, @s-dorsher,

With the fact that you were getting a previous cost value, I am afraid you might just have been assigning that value to d['costs']. Check for the spelling of the variable names returned by optimize in your model().

d['costs'] takes costs.

Cheers!
Raymond

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Having some trouble on week 2 lab

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