distillchain_cnn_deep_combine_chain_model.py 文件源码

def get_mask(self, max_frames, num_frames):
    mask_array = []
    for i in xrange(max_frames + 1):
      tmp = [0.0] * max_frames 
      for j in xrange(i):
        tmp[j] = 1.0
      mask_array.append(tmp)
    mask_array = np.array(mask_array)
    mask_init = tf.constant_initializer(mask_array)
    mask_emb = tf.get_variable("mask_emb", shape = [max_frames + 1, max_frames], 
            dtype = tf.float32, trainable = False, initializer = mask_init)
    mask = tf.nn.embedding_lookup(mask_emb, num_frames)
    return mask