ConfigProto

genel son sınıf ConfigProto

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

Protobuf tipi tensorflow.ConfigProto

İç İçe Sınıflar

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

Sabitler

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

Genel Yöntemler

boolean	içerirDeviceCount (Dize anahtarı) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
boolean	eşittir (Nesne nesnesi)
boolean	getAllowSoftPlacement () Whether soft placement is allowed.
KümeDef	getClusterDef () Optional list of all workers to use in this session.
ClusterDefOrBuilder	getClusterDefOrBuilder () Optional list of all workers to use in this session.
statik Yapılandırma Protokolü	getDefaultInstance ()
Yapılandırma Protokolü	getDefaultInstanceForType ()
final statik com.google.protobuf.Descriptors.Descriptor	getDescriptor ()
Harita<Dize, Tamsayı>	getDeviceCount () Bunun yerine getDeviceCountMap() kullanın.
int	getDeviceCountCount () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
Harita<Dize, Tamsayı>	getDeviceCountMap () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
int	getDeviceCountOrDefault (Dize anahtarı, int defaultValue) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
int	getDeviceCountOrThrow (Dize tuşu) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
Sicim	getDeviceFilters (int dizini) When any filters are present sessions will ignore all devices which do not match the filters.
com.google.protobuf.ByteString	getDeviceFiltersBytes (int dizini) 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.Deneysel	getDeneysel () .tensorflow.ConfigProto.Experimental experimental = 16;
ConfigProto.ExperimentalOrBuilder	getExperimentalOrBuilder () .tensorflow.ConfigProto.Experimental experimental = 16;
GPUSeçenekleri	getGpuOptions () Options that apply to all GPUs.
GPUOptionsOrBuilder	getGpuOptionsOrBuilder () Options that apply to all GPUs.
GrafikSeçenekleri	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.
boolean	getIsulateSessionState () If true, any resources such as Variables used in the session will not be shared with other sessions.
boolean	getLogDevicePlacement () Whether device placements should be logged.
uzun	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).
RPCSeçenekleri	getRpcOptions () Options that apply when this session uses the distributed runtime.
RPCOptionsOrBuilder	getRpcOptionsOrBuilder () Options that apply when this session uses the distributed runtime.
int	getSerializedSize ()
ThreadPoolOptionProto	getSessionInterOpThreadPool (int dizini) 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.
Listele< ThreadPoolOptionProto >	getSessionInterOpThreadPoolList () This option is experimental - it may be replaced with a different mechanism in the future.
ThreadPoolOptionProtoOrBuilder	getSessionInterOpThreadPoolOrBuilder (int dizini) This option is experimental - it may be replaced with a different mechanism in the future.
Liste<? ThreadPoolOptionProtoOrBuilder'ı genişletir >	getSessionInterOpThreadPoolOrBuilderList () This option is experimental - it may be replaced with a different mechanism in the future.
boolean	getShareClusterDevicesInSession () When true, WorkerSessions are created with device attributes from the full cluster.
final com.google.protobuf.UnknownFieldSet	getUnknownFields ()
boolean	getUsePerSessionThreads () If true, use a new set of threads for this session rather than the global pool of threads.
boolean	hasClusterDef () Optional list of all workers to use in this session.
boolean	vardırDeneysel () .tensorflow.ConfigProto.Experimental experimental = 16;
boolean	hasGpuOptions () Options that apply to all GPUs.
boolean	hasGraphOptions () Options that apply to all graphs.
boolean	hasRpcOptions () Options that apply when this session uses the distributed runtime.
int	hashKodu ()
son boole değeri	Başlatıldı ()
statik ConfigProto.Builder	yeniİnşaatçı ()
statik ConfigProto.Builder	yeniBuilder ( ConfigProto prototipi)
ConfigProto.Builder	yeniBuilderForType ()
statik Yapılandırma Protokolü	parseDelimitedFrom (InputStream girişi)
statik Yapılandırma Protokolü	parseDelimitedFrom (InputStream girişi, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
statik Yapılandırma Protokolü	parseFrom (ByteBuffer verileri, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
statik Yapılandırma Protokolü	ayrıştırmaFrom (com.google.protobuf.CodedInputStream girişi)
statik Yapılandırma Protokolü	parseFrom (byte[] verileri, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
statik Yapılandırma Protokolü	parseFrom (ByteBuffer verileri)
statik Yapılandırma Protokolü	parseFrom (com.google.protobuf.CodedInputStream girişi, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
statik Yapılandırma Protokolü	ayrıştırmaFrom (com.google.protobuf.ByteString verileri)
statik Yapılandırma Protokolü	parseFrom (InputStream girişi, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
statik Yapılandırma Protokolü	parseFrom (com.google.protobuf.ByteString verileri, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
statik	ayrıştırıcı ()
ConfigProto.Builder	inşaatçıya ()
geçersiz	writeTo (com.google.protobuf.CodedOutputStream çıkışı)

Kalıtsal Yöntemler

Java.lang.Object sınıfından

boolean	eşittir (Nesne arg0)
son Sınıf<?>	getClass ()
int	hashKodu ()
son boşluk	bildir ()
son boşluk	tümünü bildir ()
Sicim	toString ()
son boşluk	bekle (uzun arg0, int arg1)
son boşluk	bekle (uzun arg0)
son boşluk	Beklemek ()

org.tensorflow.proto.framework.ConfigProtoOrBuilder arayüzünden

soyut boole	içerirDeviceCount (Dize anahtarı) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
soyut boole	getAllowSoftPlacement () Whether soft placement is allowed.
özet ClusterDef	getClusterDef () Optional list of all workers to use in this session.
özet ClusterDefOrBuilder	getClusterDefOrBuilder () Optional list of all workers to use in this session.
soyut Harita<Dize, Tamsayı>	getDeviceCount () Bunun yerine getDeviceCountMap() kullanın.
soyut int	getDeviceCountCount () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
soyut Harita<Dize, Tamsayı>	getDeviceCountMap () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
soyut int	getDeviceCountOrDefault (Dize anahtarı, int defaultValue) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
soyut int	getDeviceCountOrThrow (Dize tuşu) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
soyut Dize	getDeviceFilters (int dizini) When any filters are present sessions will ignore all devices which do not match the filters.
abstract com.google.protobuf.ByteString	getDeviceFiltersBytes (int dizini) When any filters are present sessions will ignore all devices which do not match the filters.
soyut int	getDeviceFiltersCount () When any filters are present sessions will ignore all devices which do not match the filters.
özet Liste<String>	getDeviceFiltersList () When any filters are present sessions will ignore all devices which do not match the filters.
özet ConfigProto.Experimental	getDeneysel () .tensorflow.ConfigProto.Experimental experimental = 16;
özet ConfigProto.ExperimentalOrBuilder	getExperimentalOrBuilder () .tensorflow.ConfigProto.Experimental experimental = 16;
özet GPUSeçenekleri	getGpuOptions () Options that apply to all GPUs.
özet GPUOptionsOrBuilder	getGpuOptionsOrBuilder () Options that apply to all GPUs.
soyut GrafikSeçenekleri	getGraphOptions () Options that apply to all graphs.
soyut GraphOptionsOrBuilder	getGraphOptionsOrBuilder () Options that apply to all graphs.
soyut int	getInterOpParallelismThreads () Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process.
soyut int	getIntraOpParallelismThreads () The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads.
soyut boole	getIsulateSessionState () If true, any resources such as Variables used in the session will not be shared with other sessions.
soyut boole	getLogDevicePlacement () Whether device placements should be logged.
soyut uzun	getOperationTimeoutInMs () Global timeout for all blocking operations in this session.
soyut 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).
özet RPC Seçenekleri	getRpcOptions () Options that apply when this session uses the distributed runtime.
özet RPCOptionsOrBuilder	getRpcOptionsOrBuilder () Options that apply when this session uses the distributed runtime.
özet ThreadPoolOptionProto	getSessionInterOpThreadPool (int dizini) This option is experimental - it may be replaced with a different mechanism in the future.
soyut int	getSessionInterOpThreadPoolCount () This option is experimental - it may be replaced with a different mechanism in the future.
özet Listesi< ThreadPoolOptionProto >	getSessionInterOpThreadPoolList () This option is experimental - it may be replaced with a different mechanism in the future.
özet ThreadPoolOptionProtoOrBuilder	getSessionInterOpThreadPoolOrBuilder (int dizini) This option is experimental - it may be replaced with a different mechanism in the future.
özet Liste<? ThreadPoolOptionProtoOrBuilder'ı genişletir >	getSessionInterOpThreadPoolOrBuilderList () This option is experimental - it may be replaced with a different mechanism in the future.
soyut boole	getShareClusterDevicesInSession () When true, WorkerSessions are created with device attributes from the full cluster.
soyut boole	getUsePerSessionThreads () If true, use a new set of threads for this session rather than the global pool of threads.
soyut boole	hasClusterDef () Optional list of all workers to use in this session.
soyut boole	vardırDeneysel () .tensorflow.ConfigProto.Experimental experimental = 16;
soyut boole	hasGpuOptions () Options that apply to all GPUs.
soyut boole	hasGraphOptions () Options that apply to all graphs.
soyut boole	hasRpcOptions () Options that apply when this session uses the distributed runtime.

Sabitler

genel statik final int ALLOW_SOFT_PLACEMENT_FIELD_NUMBER

Sabit Değer: 7

genel statik final int CLUSTER_DEF_FIELD_NUMBER

Sabit Değer: 14

genel statik final int DEVICE_COUNT_FIELD_NUMBER

Sabit Değer: 1

genel statik final int DEVICE_FILTERS_FIELD_NUMBER

Sabit Değer: 4

genel statik final int EXPERIMENTAL_FIELD_NUMBER

Sabit Değer: 16

genel statik final int GPU_OPTIONS_FIELD_NUMBER

Sabit Değer: 6

genel statik final int GRAPH_OPTIONS_FIELD_NUMBER

Sabit Değer: 10

genel statik final int INTER_OP_PARALLELISM_THREADS_FIELD_NUMBER

Sabit Değer: 5

genel statik final int INTRA_OP_PARALLELISM_THREADS_FIELD_NUMBER

Sabit Değer: 2

genel statik final int ISOLATE_SESSION_STATE_FIELD_NUMBER

Sabit Değer: 15

genel statik final int LOG_DEVICE_PLACEMENT_FIELD_NUMBER

Sabit Değer: 8

genel statik final int OPERATION_TIMEOUT_IN_MS_FIELD_NUMBER

Sabit Değer: 11

genel statik final int PLACEMENT_PERIOD_FIELD_NUMBER

Sabit Değer: 3

genel statik final int RPC_OPTIONS_FIELD_NUMBER

Sabit Değer: 13

genel statik final int SESSION_INTER_OP_THREAD_POOL_FIELD_NUMBER

Sabit Değer: 12

genel statik final int SHARE_CLUSTER_DEVICES_IN_SESSION_FIELD_NUMBER

Sabit Değer: 17

genel statik final int USE_PER_SESSION_THREADS_FIELD_NUMBER

Sabit Değer: 9

Genel Yöntemler

public boolean includeDeviceCount (Dize anahtarı)

 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;

genel boole eşittir (Object obj)

genel boolean 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;

genel ClusterDef getClusterDef ()

 Optional list of all workers to use in this session.
 

.tensorflow.ClusterDef cluster_def = 14;

herkese açık ClusterDefOrBuilder getClusterDefOrBuilder ()

 Optional list of all workers to use in this session.
 

.tensorflow.ClusterDef cluster_def = 14;

genel statik ConfigProto getDefaultInstance ()

public ConfigProto getDefaultInstanceForType ()

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

genel Harita<String, Integer> getDeviceCount ()

Bunun yerine getDeviceCountMap() kullanın.

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;

genel Harita<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 (Dize anahtarı, 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 (Dize anahtarı)

 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 String getDeviceFilters (int dizini)

 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 (int dizini)

 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;

genel GPUOptions getGpuOptions ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

genel GPUOptionsOrBuilder getGpuOptionsOrBuilder ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

genel GraphOptions getGraphOptions ()

 Options that apply to all graphs.
 

.tensorflow.GraphOptions graph_options = 10;

genel 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;

genel boolean getIsulateSessionState ()

 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;

genel boolean getLogDevicePlacement ()

 Whether device placements should be logged.
 

bool log_device_placement = 8;

genel uzun 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;

halk 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;

genel RPCOptions 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 ()

genel ThreadPoolOptionProto getSessionInterOpThreadPool (int dizini)

 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;

genel Liste< 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;

genel ThreadPoolOptionProtoOrBuilder getSessionInterOpThreadPoolOrBuilder (int dizini)

 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;

genel liste<? ThreadPoolOptionProtoOrBuilder'ı genişletir > 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;

genel boolean 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;

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

genel boolean 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;

genel boolean hasClusterDef ()

 Optional list of all workers to use in this session.
 

.tensorflow.ClusterDef cluster_def = 14;

public boolean hasDeneysel ()

.tensorflow.ConfigProto.Experimental experimental = 16;

genel boolean hasGpuOptions ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

genel boolean hasGraphOptions ()

 Options that apply to all graphs.
 

.tensorflow.GraphOptions graph_options = 10;

genel boolean hasRpcOptions ()

 Options that apply when this session uses the distributed runtime.
 

.tensorflow.RPCOptions rpc_options = 13;

genel int hashCode ()

genel final boolean isInitialized ()

genel statik ConfigProto.Builder newBuilder ()

genel statik ConfigProto.Builder newBuilder ( ConfigProto prototipi)

genel ConfigProto.Builder newBuilderForType ()

public static ConfigProto parseDelimitedFrom (InputStream girişi)

Atar

IO İstisnası

public static ConfigProto parseDelimitedFrom (InputStream girişi, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Atar

IO İstisnası

genel statik ConfigProto parseFrom (ByteBuffer verileri, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Atar

Geçersiz ProtokolBufferException

genel statik ConfigProto ayrıştırmaFrom (com.google.protobuf.CodedInputStream girişi)

Atar

IO İstisnası

public static ConfigProto parseFrom (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Atar

Geçersiz ProtokolBufferException

genel statik ConfigProto parseFrom (ByteBuffer verileri)

Atar

Geçersiz ProtokolBufferException

genel statik ConfigProto parseFrom (com.google.protobuf.CodedInputStream girişi, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Atar

IO İstisnası

genel statik ConfigProto ayrıştırmaFrom (com.google.protobuf.ByteString verileri)

Atar

Geçersiz ProtokolBufferException

public static ConfigProto parseFrom (InputStream girişi, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Atar

IO İstisnası

genel statik ConfigProto ayrıştırmaFrom (com.google.protobuf.ByteString verileri, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Atar

Geçersiz ProtokolBufferException

genel statik ayrıştırıcı ()

genel ConfigProto.Builder toBuilder ()

genel geçersiz writeTo (com.google.protobuf.CodedOutputStream çıkışı)

Atar

IO İstisnası