# Struct `tensorflow::SessionOptions` <a class="md-anchor" id="AUTOGENERATED-struct--tensorflow--sessionoptions-"></a>

Configuration information for a Session .



##Member Summary <a class="md-anchor" id="AUTOGENERATED-member-summary"></a>

* [`Env* tensorflow::SessionOptions::env`](#Env_tensorflow_SessionOptions_env)
  * The environment to use.
* [`string tensorflow::SessionOptions::target`](#string_tensorflow_SessionOptions_target)
  * The TensorFlow runtime to connect to.
* [`ConfigProto tensorflow::SessionOptions::config`](#ConfigProto_tensorflow_SessionOptions_config)
  * Configuration options.
* [`tensorflow::SessionOptions::SessionOptions()`](#tensorflow_SessionOptions_SessionOptions)

##Member Details <a class="md-anchor" id="AUTOGENERATED-member-details"></a>

#### `Env* tensorflow::SessionOptions::env` <a class="md-anchor" id="Env_tensorflow_SessionOptions_env"></a>

The environment to use.



#### `string tensorflow::SessionOptions::target` <a class="md-anchor" id="string_tensorflow_SessionOptions_target"></a>

The TensorFlow runtime to connect to.

If &apos;target&apos; is empty or unspecified, the local TensorFlow runtime implementation will be used. Otherwise, the TensorFlow engine defined by &apos;target&apos; will be used to perform all computations.

"target" can be either a single entry or a comma separated list of entries. Each entry is a resolvable address of the following format: local ip:port host:port ... other system-specific formats to identify tasks and jobs ...

NOTE: at the moment &apos;local&apos; maps to an in-process service-based runtime.

Upon creation, a single session affines itself to one of the remote processes, with possible load balancing choices when the "target" resolves to a list of possible processes.

If the session disconnects from the remote process during its lifetime, session calls may fail immediately.

#### `ConfigProto tensorflow::SessionOptions::config` <a class="md-anchor" id="ConfigProto_tensorflow_SessionOptions_config"></a>

Configuration options.



#### `tensorflow::SessionOptions::SessionOptions()` <a class="md-anchor" id="tensorflow_SessionOptions_SessionOptions"></a>




