I get dimensions error using conv_single_step when f=5 or for the second convolutional layer but not for f=3 for the first layer. I think its due to the my for loop ranges being wrong but I don’t understand why. Could you help me out ?

Heyo, I don’t think you should get a dimension error on conv_single_step unless you’re passing the wrong slice. Can you post the error you’re getting from the tests?

I created a new cell in my notebook and then imported that test case from public_tests.py. You have to make a couple of small changes: np.random.seed(1) A_prev = np.random.randn(2, 5, 7, 4) W = np.random.randn(5, 5, 4, 8) b = np.random.randn(1, 1, 1, 8) Z, cache_conv = conv_forward(A_prev, W, b, {"…

[image] paulinpaloalto: the relevant thin I no longer receive dimensions error but a value error for the output. What are the correct outputs for that exercise?

I added the same output prints from the other test case in the notebook to the cell I showed above: print("Z's mean =\n", np.mean(Z)) print("Z[0,2,1] =\n", Z[0, 2, 1]) print("cache_conv[0][1][2][3] =\n", cache_conv[0][1][2][3]) Here’s what I get from those statements with code that passes the grad…

I have the correct cahe_conv values but i can not set the Z values for some reason meaning most of my z matrix is 0s.

The values are set inside the triple-nested for loop but disappear outside of that scope.

It is true that Z is a local variable in the conv_forward function, but it is also one of the return values of the function, right? What variable does that return value get assigned to at global scope? My guess is that the real problem is the indexing of Z within the scope of conv_forward. But in an…

Week1 Assignment 1 conv_forward

Course Q&A Deep Learning Specialization Convolutional Neural Networks

tkumbo July 3, 2021, 4:55pm 3

Course4 Week 1 Assignment 1: Conv_forward

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Week1 Assignment 1 conv_forward

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