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.
 
Protobuf type tensorflow.RunOptions.Experimental

Public Methods

RunOptions.Experimental.Builder
addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
RunOptions.Experimental
build()
RunOptions.Experimental
RunOptions.Experimental.Builder
clear()
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(com.google.protobuf.Descriptors.FieldDescriptor field)
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()
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).
RunOptions.Experimental
final static com.google.protobuf.Descriptors.Descriptor
com.google.protobuf.Descriptors.Descriptor
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;
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.
boolean
hasRunHandlerPoolOptions()
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
final boolean
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(RunOptions.Experimental.RunHandlerPoolOptions value)
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
final RunOptions.Experimental.Builder
mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
RunOptions.Experimental.Builder
setCollectiveGraphKey(long value)
 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(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
RunOptions.Experimental.Builder
setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
RunOptions.Experimental.Builder
setRunHandlerPoolOptions(RunOptions.Experimental.RunHandlerPoolOptions value)
.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;
final RunOptions.Experimental.Builder
setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
RunOptions.Experimental.Builder
setUseRunHandlerPool(boolean value)
 If true, then operations (using the inter-op pool) across all
 session::run() calls will be centrally scheduled, optimizing for (median
 and tail) latency.

Inherited Methods

boolean
equals(Object arg0)
final Class<?>
getClass()
int
hashCode()
final void
notify()
final void
notifyAll()
String
toString()
final void
wait(long arg0, int arg1)
final void
wait(long arg0)
final void
wait()
org.tensorflow.proto.framework.RunOptions.ExperimentalOrBuilder
abstract 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).
abstract RunOptions.Experimental.RunHandlerPoolOptions
getRunHandlerPoolOptions()
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
abstract RunOptions.Experimental.RunHandlerPoolOptionsOrBuilder
getRunHandlerPoolOptionsOrBuilder()
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;
abstract 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.
abstract boolean
hasRunHandlerPoolOptions()
.tensorflow.RunOptions.Experimental.RunHandlerPoolOptions run_handler_pool_options = 3;

Public Methods

public RunOptions.Experimental.Builder addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor field, Object value)

public RunOptions.Experimental build ()

public RunOptions.Experimental buildPartial ()

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).
 
int64 collective_graph_key = 1;

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

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 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;

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)

Throws
IOException

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

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

.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 (long value)

 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 (com.google.protobuf.Descriptors.FieldDescriptor field, Object value)

public RunOptions.Experimental.Builder setRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)

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

.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 (boolean value)

 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;