Under Run the following code to see how the model does with mini-batch gradient descent. in week 2 all my tests passed previously, but I’m getting the following error.

ZeroDivisionError Traceback (most recent call last)

in

1 # train 3-layer model

2 layers_dims = [train_X.shape[0], 5, 2, 1]

----> 3 parameters = model(train_X, train_Y, layers_dims, optimizer = “gd”)

4

5 # Predict

in model(X, Y, layers_dims, optimizer, learning_rate, mini_batch_size, beta, beta1, beta2, epsilon, num_epochs, print_cost)

58

59 # Backward propagation

—> 60 grads = backward_propagation(minibatch_X, minibatch_Y, caches)

61

62 # Update parameters

~/work/release/W2A1/opt_utils_v1a.py in backward_propagation(X, Y, cache)

156 (z1, a1, W1, b1, z2, a2, W2, b2, z3, a3, W3, b3) = cache

157

→ 158 dz3 = 1./m * (a3 - Y)

159 dW3 = np.dot(dz3, a2.T)

160 db3 = np.sum(dz3, axis=1, keepdims = True)

ZeroDivisionError: float division by zero

Please what could be the problem