// helper function to sample an index from a probability array
a = np.log(a) / temperature
a = np.exp(a) / np.sum(np.exp(a))
return np.argmax(np.random.multinomial(1, a, 1))
// train the model, output generated text after each iteration
for iteration in range(1, 60):
print()
After Change
def sample(preds, temperature=1.0):
// helper function to sample an index from a probability array
preds = np.asarray(preds).astype("float64")
preds = np.log(preds) / temperature
exp_preds = np.exp(preds)
preds = exp_preds / np.sum(exp_preds)
probas = np.random.multinomial(1, preds, 1)
return np.argmax(probas)
// train the model, output generated text after each iteration
for iteration in range(1, 60):
print()
