Hi all. Is there an error in this exercise? In all previous exc. all test passed, and this is not supposed to have any student code:

### 6.1 - Mini-Batch Gradient Descent

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ValueError 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)

56

57 # Compute cost and add to the cost total

—> 58 cost_total += compute_cost(a3, minibatch_Y)

59

60 # Backward propagation

~/work/release/W2A1/opt_utils_v1a.py in compute_cost(a3, Y)

98 “”"

99

→ 100 logprobs = np.multiply(-np.log(a3),Y) + np.multiply(-np.log(1 - a3), 1 - Y)

101 cost_total = np.sum(logprobs)

102

ValueError: operands could not be broadcast together with shapes (1,44) (1,64)

Thank you!