When faced with an error like this:

IndexError Traceback (most recent call last)

in

----> 1 parameters, last_name = model(data.split(“\n”), ix_to_char, char_to_ix, 22001, verbose = True)

2

3 assert last_name == ‘Trodonosaurus\n’, “Wrong expected output”

4 print(“\033[92mAll tests passed!”)

in model(data_x, ix_to_char, char_to_ix, num_iterations, n_a, dino_names, vocab_size, verbose)

61 # Perform one optimization step: Forward-prop → Backward-prop → Clip → Update parameters

62 # Choose a learning rate of 0.01

—> 63 curr_loss, gradients, a_prev = optimize(X, Y, a_prev, parameters, learning_rate = 0.01)

64

65 ### END CODE HERE ###

in optimize(X, Y, a_prev, parameters, learning_rate)

32

33 # Forward propagate through time (≈1 line)

—> 34 loss, cache = rnn_forward(X, Y, a_prev, parameters)

35

36 # Backpropagate through time (≈1 line)

~/work/W1A2/utils.py in rnn_forward(X, Y, a0, parameters, vocab_size)

94 x[t] = np.zeros((vocab_size,1))

95 if (X[t] != None):

—> 96 x[t][X[t]] = 1

97

98 # Run one step forward of the RNN

IndexError: only integers, slices (`:`

), ellipsis (`...`

), numpy.newaxis (`None`

) and integer or boolean arrays are valid indices

If the most recent call is last, should I start from the beginning (oldest/first call) when looking for the bug that is causing the issues. Or should I start at the last most recent call… in this case ‘rnn_forward.’

I’ve mostly been using the last most recent parts of errors to debug thus far in the DLS courses. I’m wondering if theres any more information I can squeeze out of this error message.

Thanks