Function softmax

nlp_class2/logistic.py:56–59

(a)

  lr = 1e-1
  
  def softmax(a):
    a = a - a.max()
    exp_a = np.exp(a)
    return exp_a / exp_a.sum(axis=1, keepdims=True)

  # what is the loss if we set W = log(bigram_probs)?
  W_bigram = np.log(bigram_probs)