o ?e @sZdZddlZddlmZddlmZddlmZddlm Z e Z    d d d Z dS) zCProvides a proper python API for the symbols exported through swig.N) graph_pb2) config_pb2)_pywrap_tf_optimizer)clusterTgraph_to_optimizeFc Cst|tjstdt|j|dur$t|j| | |||}n1t 't }zt|j| | |||}W| n| wWdn1sPwYt|S)a Optimize the provided metagraph. For best results, the signature_def field in `metagraph` should be populated with information about input (feed) and output (fetch) tensors. Args: config_proto: a ConfigProto protobuf. metagraph: a MetagraphDef protobuf. verbose: whether to log optimization results. graph_id: a string identifying this graph. cluster: a grappler cluster object representing hardware resources available to run this graph. strip_default_attributes: whether graph node attributes having default values should be removed after all the optimization passes. This option is useful if the resulting graph will be executed by an older process that might not know some of the recently added attributes. zCArgument `config_proto` should be a tf.ConfigProto, received type: N) isinstancerZ ConfigProto TypeErrortype__name__tf_optZTF_OptimizeGraphZ tf_clusterZSerializeToString_OPTIMIZE_GRAPH_CLUSTER_LOCKgclusterZClusterZShutdownrZGraphDefZ FromString)Z config_protoZ metagraphverboseZgraph_idrZstrip_default_attributesZ out_graphrh/home/www/facesmatcher.com/pyenv/lib/python3.10/site-packages/tensorflow/python/grappler/tf_optimizer.py OptimizeGraphs,   r)TrNF)__doc__ threadingZtensorflow.core.frameworkrZtensorflow.core.protobufrZtensorflow.python.grapplerrr rr Lockr rrrrrs