TensorFlow导出

在这里，将重点关注和学习TensorFlow中的MetaGraph形成。这有助于了解TensorFlow中的导出模块。MetaGraph包含基本信息，这些信息是对先前训练过的图表进行训练，执行评估或运行推理所必需的。

以下是相同的代码片段 -

def export_meta_graph(filename = None, collection_list = None, as_text = False): 
   """this code writes `MetaGraphDef` to save_path/filename. 

   Arguments: 
   filename: Optional meta_graph filename including the path. collection_list: 
      List of string keys to collect. as_text: If `True`, 
      writes the meta_graph as an ASCII proto. 

   Returns: 
   A `MetaGraphDef` proto. """

下面是一个典型的使用模型 -

# Build the model ... 
with tf.Session() as sess: 
   # Use the model ... 
# Export the model to /tmp/my-model.meta. 
meta_graph_def = tf.train.export_meta_graph(filename = '/tmp/my-model.meta')