tensorflow:: ClientSession
  #include <client_session.h>
  A ClientSession object lets the caller drive the evaluation of the TensorFlow graph constructed with the C++ API. 
Summary
Example:
Scope root = Scope::NewRootScope(); auto a = Placeholder(root, DT_INT32); auto c = Add(root, a, {41}); ClientSession session(root); std::vectoroutputs; Status s = session.Run({ {a, {1} } }, {c}, &outputs); if (!s.ok()) { ... } 
        Constructors and Destructors | 
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        ClientSession(const Scope & scope, const string & target)
        Create a new session to evaluate the graph contained in  
      scope by connecting to the TensorFlow runtime specified by target.  | 
    |
        ClientSession(const Scope & scope)
        Same as above, but use the empty string ("") as the target specification.  
       | 
    |
        ClientSession(const Scope & scope, const SessionOptions & session_options)
        Create a new session, configuring it with  
      session_options.  | 
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        ~ClientSession()
         | 
    
        Public types | 
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        CallableHandle
       | 
      typedefint64
        A handle to a subgraph, created with  ClientSession::MakeCallable().  | 
    
        FeedType
       | 
      typedefstd::unordered_map< Output, Input::Initializer, OutputHash >
        A data type to represent feeds to a Run call.   | 
    
        Public functions | 
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        MakeCallable(const CallableOptions & callable_options, CallableHandle *out_handle)
       | 
      
        Status
        Creates a  
      handle for invoking the subgraph defined by callable_options.  | 
    
        ReleaseCallable(CallableHandle handle)
       | 
      
        Status
        Releases resources associated with the given  
      handle in this session.  | 
    
        Run(const std::vector< Output > & fetch_outputs, std::vector< Tensor > *outputs) const 
       | 
      
        Status
        Evaluate the tensors in  
      fetch_outputs.  | 
    
        Run(const FeedType & inputs, const std::vector< Output > & fetch_outputs, std::vector< Tensor > *outputs) const 
       | 
      
        Status
        Same as above, but use the mapping in  
      inputs as feeds.  | 
    
        Run(const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs) const 
       | 
      
        Status
        Same as above. Additionally runs the operations ins  
      run_outputs.  | 
    
        Run(const RunOptions & run_options, const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs, RunMetadata *run_metadata) const 
       | 
      
        Status
        Use  
      run_options to turn on performance profiling.  | 
    
        Run(const RunOptions & run_options, const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs, RunMetadata *run_metadata, const thread::ThreadPoolOptions & threadpool_options) const 
       | 
      
        Status
        Same as above.  
       | 
    
        RunCallable(CallableHandle handle, const std::vector< Tensor > & feed_tensors, std::vector< Tensor > *fetch_tensors, RunMetadata *run_metadata)
       | 
      
        Status
        Invokes the subgraph named by  
      handle with the given options and input tensors.  | 
    
        RunCallable(CallableHandle handle, const std::vector< Tensor > & feed_tensors, std::vector< Tensor > *fetch_tensors, RunMetadata *run_metadata, const thread::ThreadPoolOptions & options)
       | 
      
        Status
        Invokes the subgraph named by  
      handle with the given options and input tensors.  | 
    
Public types
CallableHandle
int64 CallableHandle
A handle to a subgraph, created with ClientSession::MakeCallable(). 
FeedType
std::unordered_map< Output, Input::Initializer, OutputHash > FeedType
A data type to represent feeds to a Run call.
This is a map of Output objects returned by op-constructors to the value to feed them with. See Input::Initializer for details on what can be used as feed values. 
Public functions
ClientSession
ClientSession( const Scope & scope, const string & target )
Create a new session to evaluate the graph contained in scope by connecting to the TensorFlow runtime specified by target. 
ClientSession
ClientSession( const Scope & scope )
Same as above, but use the empty string ("") as the target specification.
ClientSession
ClientSession( const Scope & scope, const SessionOptions & session_options )
Create a new session, configuring it with session_options. 
MakeCallable
Status MakeCallable( const CallableOptions & callable_options, CallableHandle *out_handle )
Creates a handle for invoking the subgraph defined by callable_options. 
NOTE: This API is still experimental and may change.
ReleaseCallable
Status ReleaseCallable( CallableHandle handle )
Releases resources associated with the given handle in this session. 
NOTE: This API is still experimental and may change.
Run
Status Run( const std::vector< Output > & fetch_outputs, std::vector< Tensor > *outputs ) const
Evaluate the tensors in fetch_outputs. 
The values are returned as Tensor objects in outputs. The number and order of outputs will match fetch_outputs. 
Run
Status Run( const FeedType & inputs, const std::vector< Output > & fetch_outputs, std::vector< Tensor > *outputs ) const
Same as above, but use the mapping in inputs as feeds. 
Run
Status Run( const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs ) const
Same as above. Additionally runs the operations ins run_outputs. 
Run
Status Run( const RunOptions & run_options, const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs, RunMetadata *run_metadata ) const
Use run_options to turn on performance profiling. 
run_metadata, if not null, is filled in with the profiling results. 
Run
Status Run( const RunOptions & run_options, const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs, RunMetadata *run_metadata, const thread::ThreadPoolOptions & threadpool_options ) const
Same as above.
Additionally allows user to provide custom threadpool implementation via ThreadPoolOptions.
RunCallable
Status RunCallable( CallableHandle handle, const std::vector< Tensor > & feed_tensors, std::vector< Tensor > *fetch_tensors, RunMetadata *run_metadata )
Invokes the subgraph named by handle with the given options and input tensors. 
The order of tensors in feed_tensors must match the order of names in CallableOptions::feed() and the order of tensors in fetch_tensors will match the order of names in CallableOptions::fetch() when this subgraph was created. NOTE: This API is still experimental and may change. 
RunCallable
Status RunCallable( CallableHandle handle, const std::vector< Tensor > & feed_tensors, std::vector< Tensor > *fetch_tensors, RunMetadata *run_metadata, const thread::ThreadPoolOptions & options )
Invokes the subgraph named by handle with the given options and input tensors. 
The order of tensors in feed_tensors must match the order of names in CallableOptions::feed() and the order of tensors in fetch_tensors will match the order of names in CallableOptions::fetch() when this subgraph was created. NOTE: This API is still experimental and may change. 
~ClientSession
~ClientSession()