RunOptions.Experimental.Builder

classe final estática pública 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 de protobuf tensorflow.RunOptions.Experimental

Métodos Públicos

RunOptions.Experimental.Builder
addRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, valor do objeto)
RunOptions.Experimental
construir ()
RunOptions.Experimental
construirPartial ()
RunOptions.Experimental.Builder
claro ()
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 umof)
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
clonar ()
longo
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 ()
final estático com.google.protobuf.Descriptors.Descriptor
getDescriptor ()
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 final
éinicializado ()
RunOptions.Experimental.Builder
mergeFrom (entrada com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RunOptions.Experimental.Builder
mergeFrom (com.google.protobuf.Message outro)
RunOptions.Experimental.Builder
mergeRunHandlerPoolOptions (valor RunOptions.Experimental.RunHandlerPoolOptions )
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
RunOptions.Experimental.Builder final
mesclarUnknownFields (com.google.protobuf.UnknownFieldSet desconhecidoFields)
RunOptions.Experimental.Builder
setCollectiveGraphKey (valor longo) 
 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, valor do objeto)
RunOptions.Experimental.Builder
setRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, índice int, valor do objeto)
RunOptions.Experimental.Builder
setRunHandlerPoolOptions (valor 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;
RunOptions.Experimental.Builder final
setUnknownFields (com.google.protobuf.UnknownFieldSet desconhecidoFields)
RunOptions.Experimental.Builder
setUseRunHandlerPool (valor 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.

Métodos herdados

Métodos Públicos

public RunOptions.Experimental.Builder addRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, valor do objeto)

RunOptions.Experimental build público ()

public RunOptions.Experimental buildPartial ()

público RunOptions.Experimental.Builder claro ()

público 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;

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

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

public RunOptions.Experimental.Builder clearRunHandlerPoolOptions ()

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

público 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 público RunOptions.Experimental.Builder ()

público longo 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;

público RunOptions.Experimental getDefaultInstanceForType ()

final estático público com.google.protobuf.Descriptors.Descriptor getDescriptor ()

público 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;

getUseRunHandlerPool booleano público () 

 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;

hasRunHandlerPoolOptions booleano público ()

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

público final booleano isInitialized ()

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

Lança
IOException

público RunOptions.Experimental.Builder mergeFrom (com.google.protobuf.Message outro)

public RunOptions.Experimental.Builder mergeRunHandlerPoolOptions (valor RunOptions.Experimental.RunHandlerPoolOptions )

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

público final RunOptions.Experimental.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet desconhecidoFields)

público RunOptions.Experimental.Builder setCollectiveGraphKey (valor longo) 

 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, valor do objeto)

public RunOptions.Experimental.Builder setRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, índice int, valor do objeto)

público RunOptions.Experimental.Builder setRunHandlerPoolOptions (valor 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;

público final RunOptions.Experimental.Builder setUnknownFields (com.google.protobuf.UnknownFieldSet desconhecidoFields)

público RunOptions.Experimental.Builder setUseRunHandlerPool (valor 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;