nasm.py 文件源码

def build_decoder(self):
    """Inference Network. p(X|h)"""
    with tf.variable_scope("decoder"):
      R = tf.get_variable("R", [self.reader.vocab_size, self.h_dim])
      b = tf.get_variable("b", [self.reader.vocab_size])

      x_i = tf.diag([1.]*self.reader.vocab_size)

      e = -tf.matmul(tf.matmul(self.h, R, transpose_b=True), x_i) + b
      self.p_x_i = tf.squeeze(tf.nn.softmax(e))