RunOptions.Experimental.Builder

classe finale statica pubblica RunOptions.Experimental.Builder

 Everything inside Experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.
Tipo di protocollo tensorflow.RunOptions.Experimental

Metodi pubblici

RunOptions.Experimental.Builder
addRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, valore oggetto)
RunOptions.Experimental
costruire ()
RunOptions.Experimental
buildPartial ()
RunOptions.Experimental.Builder
chiaro ()
RunOptions.Experimental.Builder
clearCollectiveGraphKey ()
 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).
RunOptions.Experimental.Builder
clearField (campo com.google.protobuf.Descriptors.FieldDescriptor)
RunOptions.Experimental.Builder
clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)
RunOptions.Experimental.Builder
clearRunHandlerPoolOptions ()
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
RunOptions.Experimental.Builder
clearUseRunHandlerPool ()
 If true, then operations (using the inter-op pool) across all
 session::run() calls will be centrally scheduled, optimizing for (median
 and tail) latency.
RunOptions.Experimental.Builder
clone ()
lungo
getCollectiveGraphKey ()
 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).
RunOptions.Experimental
getDefaultInstanceForType ()
com.google.protobuf.Descriptors.Descriptor statico finale
getDescrittore ()
com.google.protobuf.Descriptors.Descriptor
getDescriptorForType ()
RunOptions.Experimental.RunHandlerPoolOptions
getRunHandlerPoolOptions ()
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
RunOptions.Experimental.RunHandlerPoolOptions.Builder
getRunHandlerPoolOptionsBuilder ()
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
RunOptions.Experimental.RunHandlerPoolOptionsOrBuilder
getRunHandlerPoolOptionsOrBuilder ()
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
booleano
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.
booleano
hasRunHandlerPoolOptions ()
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
booleano finale
èinizializzato ()
RunOptions.Experimental.Builder
mergeFrom (input com.google.protobuf.CodedInputStream, estensione com.google.protobuf.ExtensionRegistryLiteRegistry)
RunOptions.Experimental.Builder
mergeFrom (com.google.protobuf.Message altro)
RunOptions.Experimental.Builder
mergeRunHandlerPoolOptions (valore RunOptions.Experimental.RunHandlerPoolOptions )
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
finale RunOptions.Experimental.Builder
mergeUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields)
RunOptions.Experimental.Builder
setCollectiveGraphKey (valore lungo)
 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).
RunOptions.Experimental.Builder
setField (campo com.google.protobuf.Descriptors.FieldDescriptor, valore oggetto)
RunOptions.Experimental.Builder
setRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, indice int, valore oggetto)
RunOptions.Experimental.Builder
setRunHandlerPoolOptions (valore RunOptions.Experimental.RunHandlerPoolOptions )
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
RunOptions.Experimental.Builder
setRunHandlerPoolOptions ( RunOptions.Experimental.RunHandlerPoolOptions.Builder builderForValue)
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
finale RunOptions.Experimental.Builder
setUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields)
RunOptions.Experimental.Builder
setUseRunHandlerPool (valore booleano)
 If true, then operations (using the inter-op pool) across all
 session::run() calls will be centrally scheduled, optimizing for (median
 and tail) latency.

Metodi ereditati

Metodi pubblici

public RunOptions.Experimental.Builder addRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, valore oggetto)

build pubblica RunOptions.Experimental ()

public RunOptions.Experimental buildPartial ()

pubblico RunOptions.Experimental.Builder chiaro ()

pubblico RunOptions.Experimental.Builder clearCollectiveGraphKey () 

 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;

public RunOptions.Experimental.Builder clearField (campo com.google.protobuf.Descriptors.FieldDescriptor)

public RunOptions.Experimental.Builder clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)

pubblico RunOptions.Experimental.Builder clearRunHandlerPoolOptions ()

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

pubblico RunOptions.Experimental.Builder clearUseRunHandlerPool () 

 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;

clone pubblico RunOptions.Experimental.Builder ()

pubblico lungo getCollectiveGraphKey () 

 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;

public RunOptions.Experimental getDefaultInstanceForType ()

public static final com.google.protobuf.Descriptors.Descriptor getDescriptor ()

pubblico com.google.protobuf.Descriptors.Descriptor getDescriptorForType ()

public RunOptions.Experimental.RunHandlerPoolOptions getRunHandlerPoolOptions ()

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

public RunOptions.Experimental.RunHandlerPoolOptions.Builder getRunHandlerPoolOptionsBuilder ()

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

public RunOptions.Experimental.RunHandlerPoolOptionsOrBuilder getRunHandlerPoolOptionsOrBuilder ()

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

pubblico booleano 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;

pubblico booleano hasRunHandlerPoolOptions ()

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

public final booleano isInitialized ()

public RunOptions.Experimental.Builder mergeFrom (input com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lancia
IOException

public RunOptions.Experimental.Builder mergeFrom (com.google.protobuf.Message altro)

pubblico RunOptions.Experimental.Builder mergeRunHandlerPoolOptions (valore RunOptions.Experimental.RunHandlerPoolOptions )

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

pubblico finale RunOptions.Experimental.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields)

public RunOptions.Experimental.Builder setCollectiveGraphKey (valore lungo) 

 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;

public RunOptions.Experimental.Builder setField (campo com.google.protobuf.Descriptors.FieldDescriptor, valore oggetto)

public RunOptions.Experimental.Builder setRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, indice int, valore oggetto)

pubblico RunOptions.Experimental.Builder setRunHandlerPoolOptions (valore RunOptions.Experimental.RunHandlerPoolOptions )

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

public RunOptions.Experimental.Builder setRunHandlerPoolOptions ( RunOptions.Experimental.RunHandlerPoolOptions.Builder builderForValue)

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

pubblico finale RunOptions.Experimental.Builder setUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)

public RunOptions.Experimental.Builder setUseRunHandlerPool (valore booleano) 

 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;