AI-TensorFlow-Libtensorflow

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lib/AI/TensorFlow/Libtensorflow/Manual/CAPI.pod  view on Meta::CPAN

                                                             TF_Status* status);

=head2 TF_NewSession

=over 2

  Return a new execution session with the associated graph, or NULL on
  error. Does not take ownership of any input parameters.
  
  *`graph` must be a valid graph (not deleted or nullptr). `graph` will be
  kept alive for the lifetime of the returned TF_Session. New nodes can still
  be added to `graph` after this call.

=back

  /* From <tensorflow/c/c_api.h> */
  TF_CAPI_EXPORT extern TF_Session* TF_NewSession(TF_Graph* graph,
                                                  const TF_SessionOptions* opts,
                                                  TF_Status* status);

=head2 TF_LoadSessionFromSavedModel

lib/AI/TensorFlow/Libtensorflow/Manual/CAPI.pod  view on Meta::CPAN

  workers name). Operations created in this context can then be executed on
  any of these remote workers by setting an appropriate device.
  
  If the following is set, all servers identified by the
  ServerDef must be up when the context is created.

=back

  /* From <tensorflow/c/eager/c_api.h> */
  TF_CAPI_EXPORT extern void TFE_ContextSetServerDef(TFE_Context* ctx,
                                                     int keep_alive_secs,
                                                     const void* proto,
                                                     size_t proto_len,
                                                     TF_Status* status);

=head2 TFE_NewTensorHandle

=over 2

=back

lib/AI/TensorFlow/Libtensorflow/Manual/CAPI.pod  view on Meta::CPAN

  proto. Servers can be added to and removed from the list of remote workers
  in the context. A New set of servers identified by the ServerDef must be up
  when the context is updated.
  
  This API is for experimental usage and may be subject to change.

=back

  /* From <tensorflow/c/eager/c_api_experimental.h> */
  TF_CAPI_EXPORT extern void TFE_ContextUpdateServerDef(TFE_Context* ctx,
                                                        int keep_alive_secs,
                                                        const void* proto,
                                                        size_t proto_len,
                                                        TF_Status* status);

=head2 TFE_ContextCheckAlive

=over 2

  Checks whether a remote worker is alive or not. This will return true even if
  the context doesn't exist on the remote worker.

=back

  /* From <tensorflow/c/eager/c_api_experimental.h> */
  TF_CAPI_EXPORT extern bool TFE_ContextCheckAlive(TFE_Context* ctx,
                                                   const char* worker_name,
                                                   TF_Status* status);

=head2 TFE_ContextAsyncWait

lib/AI/TensorFlow/Libtensorflow/Manual/CAPI.pod  view on Meta::CPAN

  /* From <tensorflow/c/eager/c_api_experimental.h> */
  TF_CAPI_EXPORT extern void TFE_HostAddressSpace(TFE_Context* ctx,
                                                  TF_Buffer* buf);

=head2 TFE_OpGetAttrs

=over 2

  Fetch a reference to `op`'s attributes. The returned reference is only valid
  while `op` is alive.

=back

  /* From <tensorflow/c/eager/c_api_experimental.h> */
  TF_CAPI_EXPORT extern const TFE_OpAttrs* TFE_OpGetAttrs(const TFE_Op* op);

=head2 TFE_OpAddAttrs

=over 2