RunOptions.Experimental.Builder

public static final class 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.
tensorflow.RunOptions.Experimental type tensorflow.RunOptions.Experimental

Métodos Públicos

RunOptions.Experimental.Builder
addRepeatedField (campo com.google.protobuf.Descriptors.FieldDescriptor, valor do objeto)
RunOptions.Experimental
build ()
RunOptions.Experimental
buildPartial ()
RunOptions.Experimental.Builder
limpar ()
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 ()
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 static 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;
boleano
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.
boleano
hasRunHandlerPoolOptions ()
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
final booleano
isInitialized ()
RunOptions.Experimental.Builder
mergeFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
RunOptions.Experimental.Builder
mergeFrom (com.google.protobuf.Message other)
RunOptions.Experimental.Builder
mergeRunHandlerPoolOptions (valor RunOptions.Experimental.RunHandlerPoolOptions )
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
RunOptions.Experimental.Builder final
mergeUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)
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 unknownFields)
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)

public RunOptions.Experimental build ()

public RunOptions.Experimental buildPartial ()

public RunOptions.Experimental.Builder clear ()

public 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).
int64coletive_graph_key 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)

public RunOptions.Experimental.Builder clearRunHandlerPoolOptions ()

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

public 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;

public RunOptions.Experimental.Builder clone ()

public long 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; collect_graph_key int64 collective_graph_key = 1;

public RunOptions.Experimental getDefaultInstanceForType ()

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

public 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;

public boolean 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;

public boolean hasRunHandlerPoolOptions ()

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

public final boolean isInitialized ()

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

Lança
IOException

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

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

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

public final RunOptions.Experimental.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)

public 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).
int64coletive_graph_key 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)

public 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;

public final RunOptions.Experimental.Builder setUnknownFields (com.google.protobuf.UnknownFieldSet unknownFields)

public 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;