Conv_backward shape error in test

Course Q&A Deep Learning Specialization Convolutional Neural Networks
1

I’m trying to solve this issue for like hours.

def conv_backward(dZ, cache):


                    
    
    (A_prev, W, b, hparameters) = cache

    (m, n_H_prev, n_W_prev, n_C_prev) = A_prev.shape

    (f, f, n_C_prev, n_C) = W.shape

    stride = hparameters['stride']
    pad = hparameters['pad']

    (m, n_H, n_W, n_C) = dZ.shape

    dA_prev = np.random.randn(m, n_H_prev, n_W_prev, n_C_prev)
    dW = np.random.randn(f, f, n_C_prev, n_C)
    db = np.random.randn(f, f, n_C_prev, n_C)
    
    A_prev_pad = zero_pad(A_prev, pad)
    dA_prev_pad = zero_pad(dA_prev, pad)

    for I in range(m):  # loop over the training examples

        a_prev_pad = A_prev_pad[i, :, :, :]
        da_prev_pad = dA_prev_pad[i, :, :, :]

        for h in range(n_H):  # loop over the vertical axis of the output volume
            for w in range(n_W):  # loop over the horizontal axis of the output volume
                for c in range(n_C):  # loop over the channels of the output volume

                    # Find the corners of the current "slice"
                    vert_start = h * stride
                    vert_end = vert_start + f
                    horiz_start = w * stride
                    horiz_end = horiz_start + f

                    # Use the corners to define the slice from a_prev_pad
                    a_slice = a_prev_pad[vert_start:vert_end, horiz_start:horiz_end, :]

                    # Update gradients for the window and the filter's parameters using the code formulas given above
                    da_prev_pad[vert_start:vert_end, horiz_start:horiz_end, :] += W[:,:,:,c] * dZ[i, h, w, c]

                    dW[:, :, :, c] += a_slice * dZ[i, h, w, c]
                    db[:, :, :, c] += dZ[i, h, w, c]
                    

        # Set the ith training example's dA_prev to the unpaded da_prev_pad (Hint: use X[pad:-pad, pad:-pad, :])
        dA_prev[i, :, :, :] = da_prev_pad[pad:-pad, pad:-pad, :]
    
    
    # YOUR CODE ENDS HERE
    
    # Making sure your output shape is correct
    assert(dA_prev.shape == (m, n_H_prev, n_W_prev, n_C_prev))
    
    return dA_prev, dW, db

the code give me the right results of the TEST but it give me this error

---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-66-3575597a0654> in <module>
     21 assert dA.shape == (10, 4, 4, 3), f"Wrong shape for dA  {dA.shape} != (10, 4, 4, 3)"
     22 assert dW.shape == (2, 2, 3, 8), f"Wrong shape for dW {dW.shape} != (2, 2, 3, 8)"
---> 23 assert db.shape == (1, 1, 1, 8), f"Wrong shape for db {db.shape} != (1, 1, 1, 8)"
     24 assert np.isclose(np.mean(dA), 1.4524377), "Wrong values for dA"
     25 assert np.isclose(np.mean(dW), 1.7269914), "Wrong values for dW"

AssertionError: Wrong shape for db (2, 2, 3, 8) != (1, 1, 1, 8)

what is the problem here?

2

have you been able to solve it now?