virtual Status tensorflow::Session::PRunSetup(const std::vector< string > &input_names, const std::vector< string > &output_names, const std::vector< string > &target_nodes, string *handle) Sets up a graph for partial execution. All future feeds and fetches are specified by input_names and output_names. Returns handle that can be used to perform a sequence of partial feeds and fetches. NOTE: This API is still experimental and may change.

virtual Status tensorflow::Session::PRun(const string &handle, const std::vector< std::pair< string, Tensor > > &inputs, const std::vector< string > &output_names, std::vector< Tensor > *outputs) Continues the pending execution specified by handle with the provided input tensors and fills outputs for the endpoints specified in output_names. NOTE: This API is still experimental and may change.

virtual Status tensorflow::Session::Extend(const GraphDef &graph)=0 Adds operations to the graph that is already registered with the Session . The names of new operations in "graph" must not exist in the graph that is already registered.

virtual Status tensorflow::Session::Create(const GraphDef &graph)=0 Create the graph to be used for the session. Returns an error if this session has already been created with a graph. To re-use the session with a different graph, the caller must Close() the session first.

virtual Status tensorflow::Session::Close(const RunOptions &run_options)

A Session instance lets a caller drive a TensorFlow graph computation. When a Session is created with a given target, a new Session object is bound to the universe of resources specified by that target. Those resources are available to this session to perform computation described in the GraphDef. After extending the session with a graph, the caller uses the Run() API to perform the computation and potentially fetch outputs as Tensors. Example: // ... Create or load graph into "graph". // This

virtual Status tensorflow::RandomAccessFile::Read(uint64 offset, size_t n, StringPiece *result, char *scratch) const =0 Reads up to n bytes from the file starting at offset. scratch[0..n-1] may be written by this routine. Sets *result to the data that was read (including if fewer than n bytes were successfully read). May set *result to point at data in scratch[0..n-1], so scratch[0..n-1] must be live when *result is used. On OK returned status: n bytes have been stored in *result. On non-OK re

tensorflow::RandomAccessFile::RandomAccessFile()

A file abstraction for randomly reading the contents of a file. Member Details tensorflow::RandomAccessFile::RandomAccessFile() tensorflow::RandomAccessFile::~RandomAccessFile() virtual Status tensorflow::RandomAccessFile::Read(uint64 offset, size_t n, StringPiece *result, char *scratch) const =0 Reads up to n bytes from the file starting at offset. scratch[0..n-1] may be written by this routine. Sets *result to the data that was read (including if fewer than n bytes were successfully read). Ma

string tensorflow::PartialTensorShapeUtils::PartialShapeListString(const gtl::ArraySlice< PartialTensorShape > &shapes)