ConfigProto

публичный финальный класс ConfigProto

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

Тип protobuf tensorflow.ConfigProto

Вложенные классы

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

Константы

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

Публичные методы

логическое значение	содержитDeviceCount (строковый ключ) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
логическое значение	равно (Объект obj)
логическое значение	getAllowSoftPlacement () Whether soft placement is allowed.
КластерДеф	getClusterDef () Optional list of all workers to use in this session.
КластерДефОрБилдер	getClusterDefOrBuilder () Optional list of all workers to use in this session.
статический ConfigProto	getDefaultInstance ()
КонфигПрото	getDefaultInstanceForType ()
окончательный статический com.google.protobuf.Descriptors.Descriptor	получитьдескриптор ()
Карта<String, Integer>	getDeviceCount () Вместо этого используйте getDeviceCountMap() .
интервал	getDeviceCountCount () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
Карта<String, Integer>	getDeviceCountMap () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
интервал	getDeviceCountOrDefault (строковый ключ, int defaultValue) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
интервал	getDeviceCountOrThrow (строковый ключ) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
Нить	getDeviceFilters (индекс целого числа) When any filters are present sessions will ignore all devices which do not match the filters.
com.google.protobuf.ByteString	getDeviceFiltersBytes (индекс целого числа) When any filters are present sessions will ignore all devices which do not match the filters.
интервал	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.Экспериментальный	получитьЭкспериментальный () .tensorflow.ConfigProto.Experimental experimental = 16;
ConfigProto.ExperimentalOrBuilder	getExperimentalOrBuilder () .tensorflow.ConfigProto.Experimental experimental = 16;
Параметры графического процессора	получитьGpuOptions () Options that apply to all GPUs.
GPUOptionsOrBuilder	getGpuOptionsOrBuilder () Options that apply to all GPUs.
Параметры графика	getGraphOptions () Options that apply to all graphs.
GraphOptionsOrBuilder	getGraphOptionsOrBuilder () Options that apply to all graphs.
интервал	getInterOpParallelismThreads () Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process.
интервал	getIntraOpParallelismThreads () The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads.
логическое значение	getIsolateSessionState () If true, any resources such as Variables used in the session will not be shared with other sessions.
логическое значение	getLogDevicePlacement () Whether device placements should be logged.
длинный	getOperationTimeoutInMs () Global timeout for all blocking operations in this session.
	getParserForType ()
интервал	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).
RPCOptions	getRpcOptions () Options that apply when this session uses the distributed runtime.
RPCOptionsOrBuilder	getRpcOptionsOrBuilder () Options that apply when this session uses the distributed runtime.
интервал	getSerializedSize ()
ThreadPoolOptionProto	getSessionInterOpThreadPool (индекс int) This option is experimental - it may be replaced with a different mechanism in the future.
интервал	getSessionInterOpThreadPoolCount () This option is experimental - it may be replaced with a different mechanism in the future.
Список < ThreadPoolOptionProto >	getSessionInterOpThreadPoolList () This option is experimental - it may be replaced with a different mechanism in the future.
ThreadPoolOptionProtoOrBuilder	getSessionInterOpThreadPoolOrBuilder (индекс int) This option is experimental - it may be replaced with a different mechanism in the future.
Список <? расширяет ThreadPoolOptionProtoOrBuilder >	getSessionInterOpThreadPoolOrBuilderList () This option is experimental - it may be replaced with a different mechanism in the future.
логическое значение	getShareClusterDevicesInSession () When true, WorkerSessions are created with device attributes from the full cluster.
окончательный com.google.protobuf.UnknownFieldSet	getUnknownFields ()
логическое значение	getUsePerSessionThreads () If true, use a new set of threads for this session rather than the global pool of threads.
логическое значение	имеетКластерДеф () Optional list of all workers to use in this session.
логическое значение	имеетЭкспериментальный () .tensorflow.ConfigProto.Experimental experimental = 16;
логическое значение	имеетGpuOptions () Options that apply to all GPUs.
логическое значение	имеетграфопционы () Options that apply to all graphs.
логическое значение	имеетRpcOptions () Options that apply when this session uses the distributed runtime.
интервал	хэш-код ()
последнее логическое значение	isInitialized ()
статический ConfigProto.Builder	новыйстроитель ()
статический ConfigProto.Builder	newBuilder (прототип ConfigProto )
ConfigProto.Builder	новыйБилдерФорТип ()
статический ConfigProto	parseDelimitedFrom (входной поток)
статический ConfigProto	parseDelimitedFrom (ввод InputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
статический ConfigProto	parseFrom (данные ByteBuffer, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
статический ConfigProto	parseFrom (вход com.google.protobuf.CodedInputStream)
статический ConfigProto	parseFrom (данные byte[], com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
статический ConfigProto	parseFrom (данные ByteBuffer)
статический ConfigProto	parseFrom (ввод com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
статический ConfigProto	parseFrom (данные com.google.protobuf.ByteString)
статический ConfigProto	parseFrom (ввод InputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
статический ConfigProto	parseFrom (данные com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
статический	парсер ()
ConfigProto.Builder	toBuilder ()
пустота	writeTo (вывод com.google.protobuf.CodedOutputStream)

Унаследованные методы

Из класса java.lang.Object

логическое значение	равно (Объект arg0)
последний класс<?>	получитьКласс ()
интервал	хэш-код ()
окончательная пустота	уведомить ()
окончательная пустота	уведомитьВсе ()
Нить	toString ()
окончательная пустота	подождать (длинный arg0, int arg1)
окончательная пустота	подождите (длинный arg0)
окончательная пустота	ждать ()

Из интерфейса org.tensorflow.proto.framework.ConfigProtoOrBuilder

абстрактное логическое значение	содержитDeviceCount (строковый ключ) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
абстрактное логическое значение	getAllowSoftPlacement () Whether soft placement is allowed.
абстрактный кластердеф	getClusterDef () Optional list of all workers to use in this session.
абстрактный ClusterDefOrBuilder	getClusterDefOrBuilder () Optional list of all workers to use in this session.
абстрактная карта<String, Integer>	getDeviceCount () Вместо этого используйте getDeviceCountMap() .
абстрактный интервал	getDeviceCountCount () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
абстрактная карта<String, Integer>	getDeviceCountMap () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
абстрактный интервал	getDeviceCountOrDefault (строковый ключ, int defaultValue) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
абстрактный интервал	getDeviceCountOrThrow (строковый ключ) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
абстрактная строка	getDeviceFilters (индекс целого числа) When any filters are present sessions will ignore all devices which do not match the filters.
абстрактный com.google.protobuf.ByteString	getDeviceFiltersBytes (индекс целого числа) When any filters are present sessions will ignore all devices which do not match the filters.
абстрактный интервал	getDeviceFiltersCount () When any filters are present sessions will ignore all devices which do not match the filters.
абстрактный список<String>	getDeviceFiltersList () When any filters are present sessions will ignore all devices which do not match the filters.
абстрактный ConfigProto.Экспериментальный	получитьЭкспериментальный () .tensorflow.ConfigProto.Experimental experimental = 16;
абстрактный ConfigProto.ExperimentalOrBuilder	getExperimentalOrBuilder () .tensorflow.ConfigProto.Experimental experimental = 16;
абстрактные параметры графического процессора	получитьGpuOptions () Options that apply to all GPUs.
абстрактный GPUOptionsOrBuilder	getGpuOptionsOrBuilder () Options that apply to all GPUs.
абстрактные графические параметры	getGraphOptions () Options that apply to all graphs.
абстрактный GraphOptionsOrBuilder	getGraphOptionsOrBuilder () Options that apply to all graphs.
абстрактный интервал	getInterOpParallelismThreads () Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process.
абстрактный интервал	getIntraOpParallelismThreads () The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads.
абстрактное логическое значение	getIsolateSessionState () If true, any resources such as Variables used in the session will not be shared with other sessions.
абстрактное логическое значение	getLogDevicePlacement () Whether device placements should be logged.
абстрактный длинный	getOperationTimeoutInMs () Global timeout for all blocking operations in this session.
абстрактный интервал	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).
абстрактные параметры RPCOptions	getRpcOptions () Options that apply when this session uses the distributed runtime.
абстрактный RPCOptionsOrBuilder	getRpcOptionsOrBuilder () Options that apply when this session uses the distributed runtime.
абстрактный ThreadPoolOptionProto	getSessionInterOpThreadPool (индекс int) This option is experimental - it may be replaced with a different mechanism in the future.
абстрактный интервал	getSessionInterOpThreadPoolCount () This option is experimental - it may be replaced with a different mechanism in the future.
абстрактный список < ThreadPoolOptionProto >	getSessionInterOpThreadPoolList () This option is experimental - it may be replaced with a different mechanism in the future.
абстрактный ThreadPoolOptionProtoOrBuilder	getSessionInterOpThreadPoolOrBuilder (индекс int) This option is experimental - it may be replaced with a different mechanism in the future.
абстрактный список<? расширяет ThreadPoolOptionProtoOrBuilder >	getSessionInterOpThreadPoolOrBuilderList () This option is experimental - it may be replaced with a different mechanism in the future.
абстрактное логическое значение	getShareClusterDevicesInSession () When true, WorkerSessions are created with device attributes from the full cluster.
абстрактное логическое значение	getUsePerSessionThreads () If true, use a new set of threads for this session rather than the global pool of threads.
абстрактное логическое значение	имеетКластерДеф () Optional list of all workers to use in this session.
абстрактное логическое значение	имеетЭкспериментальный () .tensorflow.ConfigProto.Experimental experimental = 16;
абстрактное логическое значение	имеетGpuOptions () Options that apply to all GPUs.
абстрактное логическое значение	имеетграфопционы () Options that apply to all graphs.
абстрактное логическое значение	имеетRpcOptions () Options that apply when this session uses the distributed runtime.

Константы

общедоступный статический окончательный int ALLOW_SOFT_PLACEMENT_FIELD_NUMBER

Постоянное значение: 7

общедоступный статический окончательный int CLUSTER_DEF_FIELD_NUMBER

Постоянное значение: 14

общедоступный статический окончательный int DEVICE_COUNT_FIELD_NUMBER

Постоянное значение: 1

общедоступный статический финал int DEVICE_FILTERS_FIELD_NUMBER

Постоянное значение: 4

общедоступный статический окончательный int EXPERIMENTAL_FIELD_NUMBER

Постоянное значение: 16

общедоступный статический окончательный int GPU_OPTIONS_FIELD_NUMBER

Постоянное значение: 6

общедоступный статический окончательный int GRAPH_OPTIONS_FIELD_NUMBER

Постоянное значение: 10

общедоступный статический окончательный int INTER_OP_PARALLELISM_THREADS_FIELD_NUMBER

Постоянное значение: 5

общедоступный статический окончательный int INTRA_OP_PARALLELISM_THREADS_FIELD_NUMBER

Постоянное значение: 2

общедоступный статический окончательный int ISOLATE_SESSION_STATE_FIELD_NUMBER

Постоянное значение: 15

общедоступный статический окончательный int LOG_DEVICE_PLACEMENT_FIELD_NUMBER

Постоянное значение: 8

общедоступный статический окончательный int OPERATION_TIMEOUT_IN_MS_FIELD_NUMBER

Постоянное значение: 11

общедоступный статический окончательный int PLACEMENT_PERIOD_FIELD_NUMBER

Постоянное значение: 3

общедоступный статический окончательный int RPC_OPTIONS_FIELD_NUMBER

Постоянное значение: 13

общедоступный статический финал int SESSION_INTER_OP_THREAD_POOL_FIELD_NUMBER

Постоянное значение: 12

общедоступный статический окончательный int SHARE_CLUSTER_DEVICES_IN_SESSION_FIELD_NUMBER

Постоянное значение: 17

общедоступный статический окончательный int USE_PER_SESSION_THREADS_FIELD_NUMBER

Постоянное значение: 9

Публичные методы

общедоступное логическое значение containsDeviceCount (строковый ключ)

 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;

общедоступное логическое значение равно (Object obj)

общедоступное логическое значение 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;

общественный 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;

общедоступный статический ConfigProto getDefaultInstance ()

общедоступный ConfigProto getDefaultInstanceForType ()

общедоступный статический окончательный com.google.protobuf.Descriptors.Descriptor getDescriptor ()

общедоступная карта<String, Integer> getDeviceCount ()

Вместо этого используйте 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;

общедоступная карта<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 (строковый ключ, 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 (строковый ключ)

 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;

общедоступная строка getDeviceFilters (индекс 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 (индекс 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;

общедоступный ConfigProto.Experimental getExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

общедоступный ConfigProto.ExperimentalOrBuilder getExperimentalOrBuilder ()

.tensorflow.ConfigProto.Experimental experimental = 16;

общедоступные GPUOptions getGpuOptions ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

общедоступный GPUOptionsOrBuilder getGpuOptionsOrBuilder ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

общедоступные GraphOptions getGraphOptions ()

 Options that apply to all graphs.
 

.tensorflow.GraphOptions graph_options = 10;

общедоступный 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;

общедоступное логическое значение 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;

общедоступное логическое значение getLogDevicePlacement ()

 Whether device placements should be logged.
 

bool log_device_placement = 8;

общедоступный длинный 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;

общественный 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;

общедоступные RPCOptions getRpcOptions ()

 Options that apply when this session uses the distributed runtime.
 

.tensorflow.RPCOptions rpc_options = 13;

общедоступный RPCOptionsOrBuilder getRpcOptionsOrBuilder ()

 Options that apply when this session uses the distributed runtime.
 

.tensorflow.RPCOptions rpc_options = 13;

public int getSerializedSize ()

public ThreadPoolOptionProto getSessionInterOpThreadPool (индекс 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;

общедоступный список < 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 (индекс 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;

общедоступный список<? расширяет 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;

общедоступное логическое значение 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;

публичный финал com.google.protobuf.UnknownFieldSet getUnknownFields ()

общедоступное логическое значение 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;

общедоступное логическое значение hasClusterDef ()

 Optional list of all workers to use in this session.
 

.tensorflow.ClusterDef cluster_def = 14;

общедоступное логическое значение hasExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

общедоступное логическое значение hasGpuOptions ()

 Options that apply to all GPUs.
 

.tensorflow.GPUOptions gpu_options = 6;

общедоступное логическое значение hasGraphOptions ()

 Options that apply to all graphs.
 

.tensorflow.GraphOptions graph_options = 10;

общедоступное логическое значение hasRpcOptions ()

 Options that apply when this session uses the distributed runtime.
 

.tensorflow.RPCOptions rpc_options = 13;

public int hashCode ()

публичное окончательное логическое значение isInitialized ()

общедоступный статический ConfigProto.Builder newBuilder ()

общедоступный статический ConfigProto.Builder newBuilder (прототип ConfigProto )

общедоступный ConfigProto.Builder newBuilderForType ()

общедоступный статический ConfigProto parseDelimitedFrom (вход InputStream)

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общедоступный статический ConfigProto parseDelimitedFrom (ввод InputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

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общедоступный статический ConfigProto parseFrom (данные ByteBuffer, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

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общедоступный статический ConfigProto parseFrom (вход com.google.protobuf.CodedInputStream)

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общедоступный статический ConfigProto parseFrom (данные byte[], com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

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общедоступный статический ConfigProto parseFrom (данные ByteBuffer)

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общедоступный статический ConfigProto parseFrom (ввод com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

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общедоступный статический ConfigProto parseFrom (данные com.google.protobuf.ByteString)

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общедоступный статический ConfigProto parseFrom (ввод InputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

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общедоступный статический ConfigProto parseFrom (данные com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

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общественный статический парсер ()

общедоступный ConfigProto.Builder toBuilder ()

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

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