nade.py 文件源码

def _cond_prob(self, a, w_dec_i, b_dec_i):
    """Gets the conditional probability for a single dimension.

    Args:
      a: Model's hidden state, sized `[batch_size, num_hidden]`.
      w_dec_i: The decoder weight terms for the dimension, sized
          `[num_hidden, 1]`.
      b_dec_i: The decoder bias terms, sized `[batch_size, 1]`.

    Returns:
      The conditional probability of the dimension, sized `[batch_size, 1]`.
    """
    # Decode hidden units to get conditional probability.
    h = tf.sigmoid(a)
    p_cond_i = tf.sigmoid(b_dec_i + tf.matmul(h, w_dec_i))
    return p_cond_i