view release on metacpan or  search on metacpan

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

  The effect is bounding the memory held by inflight TensorHandles that are
  referenced by the inflight nodes.
  A recommended value has not been established.
  A value of 0 removes the limit, which is the behavior of TensorFlow 2.11.
  When is_async is false, the value is ignored.

=back

  /* From <tensorflow/c/eager/c_api_experimental.h> */
  TF_CAPI_EXPORT extern TFE_Executor* TFE_NewExecutor(
      bool is_async, bool enable_streaming_enqueue, int in_flight_nodes_limit);

=head2 TFE_DeleteExecutor

=over 2

  Deletes the eager Executor without waiting for enqueued nodes. Please call
  TFE_ExecutorWaitForAllPendingNodes before calling this API if you want to
  make sure all nodes are finished.

=back

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

  /* 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

=over 2

  Sync pending nodes in local executors (including the context default executor
  and thread executors) and streaming requests to remote executors, and get the
  combined status.

=back

  /* From <tensorflow/c/eager/c_api_experimental.h> */
  TF_CAPI_EXPORT extern void TFE_ContextAsyncWait(TFE_Context* ctx,
                                                  TF_Status* status);

=head2 TFE_TensorHandleDevicePointer