RunOptions.ExperimentalOrBuilder

antarmuka statis publik RunOptions.ExperimentalOrBuilder

Subkelas Tidak Langsung yang Diketahui RunOptions.Eksperimental , RunOptions.Experimental.Builder RunOptions.Eksperimental Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat.  JalankanOptions.Eksperimental.Builder Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat.

Metode Publik

abstrak panjang	dapatkanCollectiveGraphKey () If non-zero, declares that this graph is going to use collective ops and must synchronize step_ids with any other graph with this same group_key value (in a distributed computation where tasks run disjoint graphs).
abstrak RunOptions.Experimental.RunHandlerPoolOptions	getRunHandlerPoolOptions () .tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
abstrak RunOptions.Experimental.RunHandlerPoolOptionsOrBuilder	getRunHandlerPoolOptionsOrBuilder () .tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
boolean abstrak	dapatkanUseRunHandlerPool () If true, then operations (using the inter-op pool) across all session::run() calls will be centrally scheduled, optimizing for (median and tail) latency.
boolean abstrak	hasRunHandlerPoolOptions () .tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;

Metode Publik

abstrak publik getCollectiveGraphKey panjang ()

 If non-zero, declares that this graph is going to use collective
 ops and must synchronize step_ids with any other graph with this
 same group_key value (in a distributed computation where tasks
 run disjoint graphs).
 

int64 collective_graph_key = 1;

abstrak publik RunOptions.Experimental.RunHandlerPoolOptions getRunHandlerPoolOptions ()

.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;

abstrak publik RunOptions.Experimental.RunHandlerPoolOptionsOrBuilder getRunHandlerPoolOptionsOrBuilder ()

.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;

boolean abstrak publik getUseRunHandlerPool ()

 If true, then operations (using the inter-op pool) across all
 session::run() calls will be centrally scheduled, optimizing for (median
 and tail) latency.
 Consider using this option for CPU-bound workloads like inference.
 

bool use_run_handler_pool = 2;

boolean abstrak publik hasRunHandlerPoolOptions ()

.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;