policy_output.py 文件源码

def _sample_discrete_actions(batch_probs):
    """Sample a batch of actions from a batch of action probabilities.

    Args:
      batch_probs (ndarray): batch of action probabilities BxA
    Returns:
      List consisting of sampled actions
    """
    action_indices = []

    # Subtract a tiny value from probabilities in order to avoid
    # "ValueError: sum(pvals[:-1]) > 1.0" in numpy.multinomial
    batch_probs = batch_probs - np.finfo(np.float32).epsneg

    for i in range(batch_probs.shape[0]):
        histogram = np.random.multinomial(1, batch_probs[i])
        action_indices.append(int(np.nonzero(histogram)[0]))
    return action_indices