ConfigProto

classe finale publique ConfigProto

 Session configuration parameters.
 The system picks appropriate values for fields that are not set.
 

tensorflow.ConfigProto de type Protobuf.ConfigProto

Classes imbriquées

classe	ConfigProto.Builder		Session configuration parameters.
classe	ConfigProto.Expérimental		Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat.
interface	ConfigProto.ExperimentalOrBuilder

Constantes

int	ALLOW_SOFT_PLACEMENT_FIELD_NUMBER
int	CLUSTER_DEF_FIELD_NUMBER
int	DEVICE_COUNT_FIELD_NUMBER
int	DEVICE_FILTERS_FIELD_NUMBER
int	EXPERIMENTAL_FIELD_NUMBER
int	GPU_OPTIONS_FIELD_NUMBER
int	GRAPH_OPTIONS_FIELD_NUMBER
int	INTER_OP_PARALLELISM_THREADS_FIELD_NUMBER
int	INTRA_OP_PARALLELISM_THREADS_FIELD_NUMBER
int	ISOLATE_SESSION_STATE_FIELD_NUMBER
int	LOG_DEVICE_PLACEMENT_FIELD_NUMBER
int	OPERATION_TIMEOUT_IN_MS_FIELD_NUMBER
int	PLACEMENT_PERIOD_FIELD_NUMBER
int	RPC_OPTIONS_FIELD_NUMBER
int	SESSION_INTER_OP_THREAD_POOL_FIELD_NUMBER
int	SHARE_CLUSTER_DEVICES_IN_SESSION_FIELD_NUMBER
int	USE_PER_SESSION_THREADS_FIELD_NUMBER

Méthodes publiques

booléen	contientDeviceCount (clé de chaîne) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
booléen	est égal (Obj objet)
booléen	getAllowSoftPlacement () Whether soft placement is allowed.
ClusterDef	getClusterDef () Optional list of all workers to use in this session.
ClusterDefOrBuilder	getClusterDefOrBuilder () Optional list of all workers to use in this session.
ConfigProto statique	getDefaultInstance ()
ConfigProto	getDefaultInstanceForType ()
final statique com.google.protobuf.Descriptors.Descriptor	getDescripteur ()
Carte<String, Integer>	getDeviceCount () Utilisez plutôt getDeviceCountMap() .
int	getDeviceCountCount () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
Carte<String, Integer>	getDeviceCountMap () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
int	getDeviceCountOrDefault (clé de chaîne, int defaultValue) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
int	getDeviceCountOrThrow (clé de chaîne) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
Chaîne	getDeviceFilters (index int) When any filters are present sessions will ignore all devices which do not match the filters.
com.google.protobuf.ByteString	getDeviceFiltersBytes (index int) When any filters are present sessions will ignore all devices which do not match the filters.
int	getDeviceFiltersCount () When any filters are present sessions will ignore all devices which do not match the filters.
com.google.protobuf.ProtocolStringList	getDeviceFiltersList () When any filters are present sessions will ignore all devices which do not match the filters.
ConfigProto.Expérimental	getExpérimental () .tensorflow.ConfigProto.Experimental experimental = 16;
ConfigProto.ExperimentalOrBuilder	getExperimentalOrBuilder () .tensorflow.ConfigProto.Experimental experimental = 16;
Options GPU	getGpuOptions () Options that apply to all GPUs.
GPUOptionsOuBuilder	getGpuOptionsOrBuilder () Options that apply to all GPUs.
Options de graphique	getGraphOptions () Options that apply to all graphs.
GraphOptionsOrBuilder	getGraphOptionsOrBuilder () Options that apply to all graphs.
int	getInterOpParallelismThreads () Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process.
int	getIntraOpParallelismThreads () The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads.
booléen	getIsolateSessionState () If true, any resources such as Variables used in the session will not be shared with other sessions.
booléen	getLogDevicePlacement () Whether device placements should be logged.
long	getOperationTimeoutInMs () Global timeout for all blocking operations in this session.
	getParserForType ()
int	getPlacementPeriod () Assignment of Nodes to Devices is recomputed every placement_period steps until the system warms up (at which point the recomputation typically slows down automatically).
Options RPC	getRpcOptions () Options that apply when this session uses the distributed runtime.
RPCOptionsOuBuilder	getRpcOptionsOrBuilder () Options that apply when this session uses the distributed runtime.
int	getSerializedSize ()
ThreadPoolOptionProto	getSessionInterOpThreadPool (index int) This option is experimental - it may be replaced with a different mechanism in the future.
int	getSessionInterOpThreadPoolCount () This option is experimental - it may be replaced with a different mechanism in the future.
Liste < ThreadPoolOptionProto >	getSessionInterOpThreadPoolList () This option is experimental - it may be replaced with a different mechanism in the future.
ThreadPoolOptionProtoOrBuilder	getSessionInterOpThreadPoolOrBuilder (index int) This option is experimental - it may be replaced with a different mechanism in the future.
Liste<? étend ThreadPoolOptionProtoOrBuilder >	getSessionInterOpThreadPoolOrBuilderList () This option is experimental - it may be replaced with a different mechanism in the future.
booléen	getShareClusterDevicesInSession () When true, WorkerSessions are created with device attributes from the full cluster.
final com.google.protobuf.UnknownFieldSet	getUnknownFields ()
booléen	getUsePerSessionThreads () If true, use a new set of threads for this session rather than the global pool of threads.
booléen	hasClusterDef () Optional list of all workers to use in this session.
booléen	aExpérimental () .tensorflow.ConfigProto.Experimental experimental = 16;
booléen	aGpuOptions () Options that apply to all GPUs.
booléen	hasGraphOptions () Options that apply to all graphs.
booléen	aRpcOptions () Options that apply when this session uses the distributed runtime.
int	Code de hachage ()
booléen final	estInitialisé ()
statique ConfigProto.Builder	nouveauBuilder ()
statique ConfigProto.Builder	newBuilder (prototype ConfigProto )
ConfigProto.Builder	nouveauBuilderForType ()
ConfigProto statique	parseDelimitedFrom (entrée InputStream)
ConfigProto statique	parseDelimitedFrom (entrée InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ConfigProto statique	parseFrom (données ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ConfigProto statique	parseFrom (entrée com.google.protobuf.CodedInputStream)
ConfigProto statique	parseFrom (données octet[], com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ConfigProto statique	parseFrom (données ByteBuffer)
ConfigProto statique	parseFrom (entrée com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ConfigProto statique	parseFrom (données com.google.protobuf.ByteString)
ConfigProto statique	parseFrom (entrée InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ConfigProto statique	parseFrom (données com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
statique	analyseur ()
ConfigProto.Builder	toBuilder ()
vide	writeTo (sortie com.google.protobuf.CodedOutputStream)

Méthodes héritées

De la classe java.lang.Object

booléen	est égal à (Objet arg0)
Classe finale<?>	obtenirClasse ()
int	Code de hachage ()
vide final	notifier ()
vide final	notifierTous ()
Chaîne	àChaîne ()
vide final	attendre (long arg0, int arg1)
vide final	attendez (long arg0)
vide final	attendez ()

Depuis l'interface org.tensorflow.proto.framework.ConfigProtoOrBuilder

booléen abstrait	contientDeviceCount (clé de chaîne) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
booléen abstrait	getAllowSoftPlacement () Whether soft placement is allowed.
résumé ClusterDef	getClusterDef () Optional list of all workers to use in this session.
résumé ClusterDefOrBuilder	getClusterDefOrBuilder () Optional list of all workers to use in this session.
Carte abstraite<String, Integer>	getDeviceCount () Utilisez plutôt getDeviceCountMap() .
abstrait entier	getDeviceCountCount () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
Carte abstraite<String, Integer>	getDeviceCountMap () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
abstrait entier	getDeviceCountOrDefault (clé de chaîne, int defaultValue) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
abstrait entier	getDeviceCountOrThrow (clé de chaîne) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
chaîne abstraite	getDeviceFilters (index int) When any filters are present sessions will ignore all devices which do not match the filters.
résumé com.google.protobuf.ByteString	getDeviceFiltersBytes (index int) When any filters are present sessions will ignore all devices which do not match the filters.
abstrait entier	getDeviceFiltersCount () When any filters are present sessions will ignore all devices which do not match the filters.
Liste abstraite<String>	getDeviceFiltersList () When any filters are present sessions will ignore all devices which do not match the filters.
résumé ConfigProto.Experimental	getExpérimental () .tensorflow.ConfigProto.Experimental experimental = 16;
résumé ConfigProto.ExperimentalOrBuilder	getExperimentalOrBuilder () .tensorflow.ConfigProto.Experimental experimental = 16;
OptionsGPU abstraites	getGpuOptions () Options that apply to all GPUs.
abstrait GPUOptionsOrBuilder	getGpuOptionsOrBuilder () Options that apply to all GPUs.
Options de graphique abstraites	getGraphOptions () Options that apply to all graphs.
résumé GraphOptionsOrBuilder	getGraphOptionsOrBuilder () Options that apply to all graphs.
abstrait entier	getInterOpParallelismThreads () Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process.
abstrait entier	getIntraOpParallelismThreads () The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads.
booléen abstrait	getIsolateSessionState () If true, any resources such as Variables used in the session will not be shared with other sessions.
booléen abstrait	getLogDevicePlacement () Whether device placements should be logged.
abstrait long	getOperationTimeoutInMs () Global timeout for all blocking operations in this session.
abstrait entier	getPlacementPeriod () Assignment of Nodes to Devices is recomputed every placement_period steps until the system warms up (at which point the recomputation typically slows down automatically).
Options RPC abstraites	getRpcOptions () Options that apply when this session uses the distributed runtime.
résumé RPCOptionsOrBuilder	getRpcOptionsOrBuilder () Options that apply when this session uses the distributed runtime.
résumé ThreadPoolOptionProto	getSessionInterOpThreadPool (index int) This option is experimental - it may be replaced with a different mechanism in the future.
abstrait entier	getSessionInterOpThreadPoolCount () This option is experimental - it may be replaced with a different mechanism in the future.
Liste abstraite < ThreadPoolOptionProto >	getSessionInterOpThreadPoolList () This option is experimental - it may be replaced with a different mechanism in the future.
résumé ThreadPoolOptionProtoOrBuilder	getSessionInterOpThreadPoolOrBuilder (index int) This option is experimental - it may be replaced with a different mechanism in the future.
Liste abstraite <? étend ThreadPoolOptionProtoOrBuilder >	getSessionInterOpThreadPoolOrBuilderList () This option is experimental - it may be replaced with a different mechanism in the future.
booléen abstrait	getShareClusterDevicesInSession () When true, WorkerSessions are created with device attributes from the full cluster.
booléen abstrait	getUsePerSessionThreads () If true, use a new set of threads for this session rather than the global pool of threads.
booléen abstrait	hasClusterDef () Optional list of all workers to use in this session.
booléen abstrait	aExpérimental () .tensorflow.ConfigProto.Experimental experimental = 16;
booléen abstrait	aGpuOptions () Options that apply to all GPUs.
booléen abstrait	hasGraphOptions () Options that apply to all graphs.
booléen abstrait	aRpcOptions () Options that apply when this session uses the distributed runtime.

Constantes

public statique final int ALLOW_SOFT_PLACEMENT_FIELD_NUMBER

Valeur constante : 7

public statique final int CLUSTER_DEF_FIELD_NUMBER

Valeur constante : 14

public statique final entier DEVICE_COUNT_FIELD_NUMBER

Valeur constante : 1

public statique final int DEVICE_FILTERS_FIELD_NUMBER

Valeur constante : 4

public statique final int EXPERIMENTAL_FIELD_NUMBER

Valeur constante : 16

public statique final int GPU_OPTIONS_FIELD_NUMBER

Valeur constante : 6

public statique final int GRAPH_OPTIONS_FIELD_NUMBER

Valeur constante : 10

public statique final int INTER_OP_PARALLELISM_THREADS_FIELD_NUMBER

Valeur constante : 5

public statique final int INTRA_OP_PARALLELISM_THREADS_FIELD_NUMBER

Valeur constante : 2

public statique final int ISOLATE_SESSION_STATE_FIELD_NUMBER

Valeur constante : 15

public statique final int LOG_DEVICE_PLACEMENT_FIELD_NUMBER

Valeur constante : 8

public statique final int OPERATION_TIMEOUT_IN_MS_FIELD_NUMBER

Valeur constante : 11

public statique final int PLACEMENT_PERIOD_FIELD_NUMBER

Valeur constante : 3

public statique final int RPC_OPTIONS_FIELD_NUMBER

Valeur constante : 13

public statique final int SESSION_INTER_OP_THREAD_POOL_FIELD_NUMBER

Valeur constante : 12

public statique final int SHARE_CLUSTER_DEVICES_IN_SESSION_FIELD_NUMBER

Valeur constante : 17

public statique final int USE_PER_SESSION_THREADS_FIELD_NUMBER

Valeur constante : 9

Méthodes publiques

public boolean containDeviceCount (clé de chaîne)

 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.  If a particular device
 type is not found in the map, the system picks an appropriate
 number.
 

map<string, int32> device_count = 1;

public booléen égal (Objet obj)

public booléen getAllowSoftPlacement ()

 Whether soft placement is allowed. If allow_soft_placement is true,
 an op will be placed on CPU if
   1. there's no GPU implementation for the OP
 or
   2. no GPU devices are known or registered
 or
   3. need to co-locate with reftype input(s) which are from CPU.
 

bool allow_soft_placement = 7;

public ClusterDef getClusterDef ()

 Optional list of all workers to use in this session.
 

.tensorflow.ClusterDef cluster_def = 14;

public ClusterDefOrBuilder getClusterDefOrBuilder ()

 Optional list of all workers to use in this session.
 

.tensorflow.ClusterDef cluster_def = 14;

public statique ConfigProto getDefaultInstance ()

public ConfigProto getDefaultInstanceForType ()

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

public Map<String, Integer> getDeviceCount ()

Utilisez plutôt getDeviceCountMap() .

public int getDeviceCountCount ()

 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.  If a particular device
 type is not found in the map, the system picks an appropriate
 number.
 

map<string, int32> device_count = 1;

public Map<String, Integer> getDeviceCountMap ()

 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.  If a particular device
 type is not found in the map, the system picks an appropriate
 number.
 

map<string, int32> device_count = 1;

public int getDeviceCountOrDefault (clé de chaîne, int defaultValue)

 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.  If a particular device
 type is not found in the map, the system picks an appropriate
 number.
 

map<string, int32> device_count = 1;

public int getDeviceCountOrThrow (clé de chaîne)

 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.  If a particular device
 type is not found in the map, the system picks an appropriate
 number.
 

map<string, int32> device_count = 1;

chaîne publique getDeviceFilters (index int)

 When any filters are present sessions will ignore all devices which do not
 match the filters. Each filter can be partially specified, e.g. "/job:ps"
 "/job:worker/replica:3", etc.
 

repeated string device_filters = 4;

public com.google.protobuf.ByteString getDeviceFiltersBytes (index int)

 When any filters are present sessions will ignore all devices which do not
 match the filters. Each filter can be partially specified, e.g. "/job:ps"
 "/job:worker/replica:3", etc.
 

repeated string device_filters = 4;

public int getDeviceFiltersCount ()

 When any filters are present sessions will ignore all devices which do not
 match the filters. Each filter can be partially specified, e.g. "/job:ps"
 "/job:worker/replica:3", etc.
 

repeated string device_filters = 4;

public com.google.protobuf.ProtocolStringList getDeviceFiltersList ()

 When any filters are present sessions will ignore all devices which do not
 match the filters. Each filter can be partially specified, e.g. "/job:ps"
 "/job:worker/replica:3", etc.
 

repeated string device_filters = 4;

public ConfigProto.Experimental getExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

public ConfigProto.ExperimentalOrBuilder getExperimentalOrBuilder ()

.tensorflow.ConfigProto.Experimental experimental = 16;

GPUOptions publiques getGpuOptions ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

public GPUOptionsOrBuilder getGpuOptionsOrBuilder ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

public GraphOptions getGraphOptions ()

 Options that apply to all graphs.
 

.tensorflow.GraphOptions graph_options = 10;

public GraphOptionsOrBuilder getGraphOptionsOrBuilder ()

 Options that apply to all graphs.
 

.tensorflow.GraphOptions graph_options = 10;

public int getInterOpParallelismThreads ()

 Nodes that perform blocking operations are enqueued on a pool of
 inter_op_parallelism_threads available in each process.
 0 means the system picks an appropriate number.
 Negative means all operations are performed in caller's thread.
 Note that the first Session created in the process sets the
 number of threads for all future sessions unless use_per_session_threads is
 true or session_inter_op_thread_pool is configured.
 

int32 inter_op_parallelism_threads = 5;

public int getIntraOpParallelismThreads ()

 The execution of an individual op (for some op types) can be
 parallelized on a pool of intra_op_parallelism_threads.
 0 means the system picks an appropriate number.
 If you create an ordinary session, e.g., from Python or C++,
 then there is exactly one intra op thread pool per process.
 The first session created determines the number of threads in this pool.
 All subsequent sessions reuse/share this one global pool.
 There are notable exceptions to the default behavior describe above:
 1. There is an environment variable  for overriding this thread pool,
    named TF_OVERRIDE_GLOBAL_THREADPOOL.
 2. When connecting to a server, such as a remote `tf.train.Server`
    instance, then this option will be ignored altogether.
 

int32 intra_op_parallelism_threads = 2;

public booléen getIsolateSessionState ()

 If true, any resources such as Variables used in the session will not be
 shared with other sessions. However, when clusterspec propagation is
 enabled, this field is ignored and sessions are always isolated.
 

bool isolate_session_state = 15;

public booléen getLogDevicePlacement ()

 Whether device placements should be logged.
 

bool log_device_placement = 8;

public long getOperationTimeoutInMs ()

 Global timeout for all blocking operations in this session.  If non-zero,
 and not overridden on a per-operation basis, this value will be used as the
 deadline for all blocking operations.
 

int64 operation_timeout_in_ms = 11;

publique getParserForType ()

public int getPlacementPeriod ()

 Assignment of Nodes to Devices is recomputed every placement_period
 steps until the system warms up (at which point the recomputation
 typically slows down automatically).
 

int32 placement_period = 3;

RPCOptions publiques getRpcOptions ()

 Options that apply when this session uses the distributed runtime.
 

.tensorflow.RPCOptions rpc_options = 13;

public RPCOptionsOrBuilder getRpcOptionsOrBuilder ()

 Options that apply when this session uses the distributed runtime.
 

.tensorflow.RPCOptions rpc_options = 13;

public int getSerializedSize ()

public ThreadPoolOptionProto getSessionInterOpThreadPool (index int)

 This option is experimental - it may be replaced with a different mechanism
 in the future.
 Configures session thread pools. If this is configured, then RunOptions for
 a Run call can select the thread pool to use.
 The intended use is for when some session invocations need to run in a
 background pool limited to a small number of threads:
 - For example, a session may be configured to have one large pool (for
 regular compute) and one small pool (for periodic, low priority work);
 using the small pool is currently the mechanism for limiting the inter-op
 parallelism of the low priority work.  Note that it does not limit the
 parallelism of work spawned by a single op kernel implementation.
 - Using this setting is normally not needed in training, but may help some
 serving use cases.
 - It is also generally recommended to set the global_name field of this
 proto, to avoid creating multiple large pools. It is typically better to
 run the non-low-priority work, even across sessions, in a single large
 pool.
 

repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;

public int getSessionInterOpThreadPoolCount ()

 This option is experimental - it may be replaced with a different mechanism
 in the future.
 Configures session thread pools. If this is configured, then RunOptions for
 a Run call can select the thread pool to use.
 The intended use is for when some session invocations need to run in a
 background pool limited to a small number of threads:
 - For example, a session may be configured to have one large pool (for
 regular compute) and one small pool (for periodic, low priority work);
 using the small pool is currently the mechanism for limiting the inter-op
 parallelism of the low priority work.  Note that it does not limit the
 parallelism of work spawned by a single op kernel implementation.
 - Using this setting is normally not needed in training, but may help some
 serving use cases.
 - It is also generally recommended to set the global_name field of this
 proto, to avoid creating multiple large pools. It is typically better to
 run the non-low-priority work, even across sessions, in a single large
 pool.
 

repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;

liste publique < ThreadPoolOptionProto > getSessionInterOpThreadPoolList ()

 This option is experimental - it may be replaced with a different mechanism
 in the future.
 Configures session thread pools. If this is configured, then RunOptions for
 a Run call can select the thread pool to use.
 The intended use is for when some session invocations need to run in a
 background pool limited to a small number of threads:
 - For example, a session may be configured to have one large pool (for
 regular compute) and one small pool (for periodic, low priority work);
 using the small pool is currently the mechanism for limiting the inter-op
 parallelism of the low priority work.  Note that it does not limit the
 parallelism of work spawned by a single op kernel implementation.
 - Using this setting is normally not needed in training, but may help some
 serving use cases.
 - It is also generally recommended to set the global_name field of this
 proto, to avoid creating multiple large pools. It is typically better to
 run the non-low-priority work, even across sessions, in a single large
 pool.
 

repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;

public ThreadPoolOptionProtoOrBuilder getSessionInterOpThreadPoolOrBuilder (index int)

 This option is experimental - it may be replaced with a different mechanism
 in the future.
 Configures session thread pools. If this is configured, then RunOptions for
 a Run call can select the thread pool to use.
 The intended use is for when some session invocations need to run in a
 background pool limited to a small number of threads:
 - For example, a session may be configured to have one large pool (for
 regular compute) and one small pool (for periodic, low priority work);
 using the small pool is currently the mechanism for limiting the inter-op
 parallelism of the low priority work.  Note that it does not limit the
 parallelism of work spawned by a single op kernel implementation.
 - Using this setting is normally not needed in training, but may help some
 serving use cases.
 - It is also generally recommended to set the global_name field of this
 proto, to avoid creating multiple large pools. It is typically better to
 run the non-low-priority work, even across sessions, in a single large
 pool.
 

repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;

Liste publique <? étend ThreadPoolOptionProtoOrBuilder > getSessionInterOpThreadPoolOrBuilderList ()

 This option is experimental - it may be replaced with a different mechanism
 in the future.
 Configures session thread pools. If this is configured, then RunOptions for
 a Run call can select the thread pool to use.
 The intended use is for when some session invocations need to run in a
 background pool limited to a small number of threads:
 - For example, a session may be configured to have one large pool (for
 regular compute) and one small pool (for periodic, low priority work);
 using the small pool is currently the mechanism for limiting the inter-op
 parallelism of the low priority work.  Note that it does not limit the
 parallelism of work spawned by a single op kernel implementation.
 - Using this setting is normally not needed in training, but may help some
 serving use cases.
 - It is also generally recommended to set the global_name field of this
 proto, to avoid creating multiple large pools. It is typically better to
 run the non-low-priority work, even across sessions, in a single large
 pool.
 

repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;

public booléen getShareClusterDevicesInSession ()

 When true, WorkerSessions are created with device attributes from the
 full cluster.
 This is helpful when a worker wants to partition a graph
 (for example during a PartitionedCallOp).
 

bool share_cluster_devices_in_session = 17;

public final com.google.protobuf.UnknownFieldSet getUnknownFields ()

public booléen getUsePerSessionThreads ()

 If true, use a new set of threads for this session rather than the global
 pool of threads. Only supported by direct sessions.
 If false, use the global threads created by the first session, or the
 per-session thread pools configured by session_inter_op_thread_pool.
 This option is deprecated. The same effect can be achieved by setting
 session_inter_op_thread_pool to have one element, whose num_threads equals
 inter_op_parallelism_threads.
 

bool use_per_session_threads = 9;

public booléen hasClusterDef ()

 Optional list of all workers to use in this session.
 

.tensorflow.ClusterDef cluster_def = 14;

public booléen hasExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

public booléen hasGpuOptions ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

public booléen hasGraphOptions ()

 Options that apply to all graphs.
 

.tensorflow.GraphOptions graph_options = 10;

public booléen hasRpcOptions ()

 Options that apply when this session uses the distributed runtime.
 

.tensorflow.RPCOptions rpc_options = 13;

code de hachage int public ()

public final booléen isInitialized ()

public statique ConfigProto.Builder newBuilder ()

public statique ConfigProto.Builder newBuilder (prototype ConfigProto )

public ConfigProto.Builder newBuilderForType ()

public statique ConfigProto parseDelimitedFrom (entrée InputStream)

Jetés

IOException

public statique ConfigProto parseDelimitedFrom (entrée InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Jetés

IOException

public statique ConfigProto parseFrom (données ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Jetés

InvalidProtocolBufferException

public statique ConfigProto parseFrom (entrée com.google.protobuf.CodedInputStream)

Jetés

IOException

public statique ConfigProto parseFrom (données octet[], com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Jetés

InvalidProtocolBufferException

public statique ConfigProto parseFrom (données ByteBuffer)

Jetés

InvalidProtocolBufferException

public statique ConfigProto parseFrom (entrée com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Jetés

IOException

public statique ConfigProto parseFrom (données com.google.protobuf.ByteString)

Jetés

InvalidProtocolBufferException

public statique ConfigProto parseFrom (entrée InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Jetés

IOException

public statique ConfigProto parseFrom (données com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Jetés

InvalidProtocolBufferException

public statique analyseur ()

public ConfigProto.Builder toBuilder ()

public void writeTo (sortie com.google.protobuf.CodedOutputStream)

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IOException