98d49754edd5b5757fb7c37c8a3cdc9a65d6f238,examples/lstm_text_generation.py,,sample,#Any#Any#,63

Before Change

    if random.random() > diversity:
        return np.argmax(a)
    while 1:
        i = random.randint(0, len(a)-1)
        if a[i] > random.random():
            return i

// train the model, output generated text after each iteration

After Change

// helper function to sample an index from a probability array
def sample(a, temperature=1.0):
    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):

Instances