Hello! I am really struggeling with assignment 1exercise 3. I checked it a million times, and it says the output is not right. I will describe what I did.

- I selected the dimensions for W and A_prev (all the notations and order has been kep consistent throughout).
- I took out from hyperparameters, the pad and stride
- I calculated the size of n_H and n_W using the formula.
- I initialized Z using the dimension:(nr. of training examples, n_H, n_W , the number of filters)
- I padded A_prev using the previously calculated function to get the new padded image
- In the for loops, I loop over nr. of training examples, n_H, n_W and numbr of filters.
- In loop 1: I select the current training example
- In loop 2: I define the vertical edges by adding f to the the increment h
- In loop3: I define the horizontal edges by adding f to the increment w
- In loop4: a) I select the slice that I want to be convoluted using from from the current training example >a_prev_pad[vertical,horzontal,everything]

b) I get the weights and biases from W and b by using W[everything, everything, everything, everything, increment for number of filters] → select the filter that want to apply

c) apply conv_single_step(a_slice_prev, weights, biases) to get a scalar Z

The dimensions seem to be fine, the calculations too. I have no idea what to do. I am stuck on this for 3 days already and I can t move on beacause this function is required for the next exercise. I would greatly appreciate any help. Thank you!