Exercise 3 - conv_forward error

Course Q&A Deep Learning Specialization Convolutional Neural Networks
9

Hi @TMosh , I checked the dimensions as you suggested and now I get at least a first result for Z.

However, I am still getting the “only size-1 arrays can be converted to Python scalars” error on the 2nd iteration:

TypeError                                 Traceback (most recent call last)
<ipython-input-41-182241fd5e53> in <module>
      6                "stride": 2}
      7 
----> 8 Z, cache_conv = conv_forward(A_prev, W, b, hparameters)
      9 print("Z's mean =\n", np.mean(Z))
     10 print("Z[0,2,1] =\n", Z[0, 2, 1])

<ipython-input-40-95aab82c1890> in conv_forward(A_prev, W, b, hparameters)
     98                     weights = W[ : , : , c : c+1 , c : c+1]
     99                     biases = b [ : , : , c : c+1 , c : c+1]
--> 100                     print(f'conv_single_step func -> {conv_single_step(a_slice_prev, weights, biases)}')
    101                     Z[i, h, w, c] = conv_single_step(a_slice_prev, weights, biases)
    102 

<ipython-input-4-0dc5d6ead47d> in conv_single_step(a_slice_prev, W, b)
     26     s = a_slice_prev * W
     27     Z = np.sum(s, dtype=np.float)
---> 28     Z += np.float(b)
     29 
     30     # YOUR CODE ENDS HERE

TypeError: only size-1 arrays can be converted to Python scalars

Maybe the problem is in the n_c vs n_c_prev dimensions. But I am stuck for several hours now. Any pointers would be appreciated (and the print is for debugging purposes only).

Thank you