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

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;