ConfigProto.Builder

الفئة النهائية العامة الثابتة ConfigProto.Builder

 Session configuration parameters.
 The system picks appropriate values for fields that are not set.
 
نوع Protobuf tensorflow.ConfigProto

الأساليب العامة

ConfigProto.Builder
addAllDeviceFilters (قيم Iterable<String>)
 When any filters are present sessions will ignore all devices which do not
 match the filters.
ConfigProto.Builder
addAllSessionInterOpThreadPool (Iterable<؟ يمتد ThreadPoolOptionProto > القيم)
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ConfigProto.Builder
addDeviceFilters (قيمة السلسلة)
 When any filters are present sessions will ignore all devices which do not
 match the filters.
ConfigProto.Builder
addDeviceFiltersBytes (قيمة com.google.protobuf.ByteString)
 When any filters are present sessions will ignore all devices which do not
 match the filters.
ConfigProto.Builder
addRepeatedField (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن)
ConfigProto.Builder
addSessionInterOpThreadPool (قيمة ThreadPoolOptionProto )
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ConfigProto.Builder
addSessionInterOpThreadPool (مؤشر int، قيمة ThreadPoolOptionProto )
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ConfigProto.Builder
addSessionInterOpThreadPool ( ThreadPoolOptionProto.Builder builderForValue)
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ConfigProto.Builder
addSessionInterOpThreadPool (مؤشر int، ThreadPoolOptionProto.Builder builderForValue)
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ThreadPoolOptionProto.Builder
addSessionInterOpThreadPoolBuilder (فهرس كثافة العمليات)
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ThreadPoolOptionProto.Builder
addSessionInterOpThreadPoolBuilder ()
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ConfigProto
ConfigProto
ConfigProto.Builder
ConfigProto.Builder
ClearAllowSoftPlacement ()
 Whether soft placement is allowed.
ConfigProto.Builder
كلير كلستر ديف ()
 Optional list of all workers to use in this session.
ConfigProto.Builder
ConfigProto.Builder
مرشحات كلير ديفيس ()
 When any filters are present sessions will ignore all devices which do not
 match the filters.
ConfigProto.Builder
واضحتجريبي ()
.tensorflow.ConfigProto.Experimental experimental = 16;
ConfigProto.Builder
ClearField (حقل com.google.protobuf.Descriptors.FieldDescriptor)
ConfigProto.Builder
خيارات ClearGpu ()
 Options that apply to all GPUs.
ConfigProto.Builder
خيارات ClearGraph ()
 Options that apply to all graphs.
ConfigProto.Builder
ClearInterOpParallelismThreads ()
 Nodes that perform blocking operations are enqueued on a pool of
 inter_op_parallelism_threads available in each process.
ConfigProto.Builder
ClearIntraOpParallelismThreads ()
 The execution of an individual op (for some op types) can be
 parallelized on a pool of intra_op_parallelism_threads.
ConfigProto.Builder
ClearIsolateSessionState ()
 If true, any resources such as Variables used in the session will not be
 shared with other sessions.
ConfigProto.Builder
ClearLogDevicePlacement ()
 Whether device placements should be logged.
ConfigProto.Builder
ClearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)
ConfigProto.Builder
ClearOperationTimeoutInMs ()
 Global timeout for all blocking operations in this session.
ConfigProto.Builder
كليربلاسيمينتبيريود ()
 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).
ConfigProto.Builder
كليررببوكتيونس ()
 Options that apply when this session uses the distributed runtime.
ConfigProto.Builder
ClearSessionInterOpThreadPool ()
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ConfigProto.Builder
ClearShareClusterDevicesInSession ()
 When true, WorkerSessions are created with device attributes from the
 full cluster.
ConfigProto.Builder
ClearUsePerSessionThreads ()
 If true, use a new set of threads for this session rather than the global
 pool of threads.
ConfigProto.Builder
منطقية
يحتوي علىDeviceCount (مفتاح السلسلة)
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
منطقية
الحصول علىAllowSoftPlacement ()
 Whether soft placement is allowed.
ClusterDef
الحصول على ClusterDef ()
 Optional list of all workers to use in this session.
ClusterDef.Builder
الحصول على ClusterDefBuilder ()
 Optional list of all workers to use in this session.
ClusterDefOrBuilder
الحصول على ClusterDefOrBuilder ()
 Optional list of all workers to use in this session.
ConfigProto
النهائي الثابت com.google.protobuf.Descriptors.Descriptor
com.google.protobuf.Descriptors.Descriptor
خريطة<سلسلة، عدد صحيح>
getDeviceCount ()
استخدم getDeviceCountMap() بدلاً من ذلك.
كثافة العمليات
getDeviceCountCount ()
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
خريطة<سلسلة، عدد صحيح>
getDeviceCountMap ()
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
كثافة العمليات
getDeviceCountOrDefault (مفتاح السلسلة، int defaultValue)
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
كثافة العمليات
getDeviceCountOrThrow (مفتاح السلسلة)
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
خيط
getDeviceFilters (فهرس كثافة العمليات)
 When any filters are present sessions will ignore all devices which do not
 match the filters.
com.google.protobuf.ByteString
getDeviceFiltersBytes (فهرس كثافة العمليات)
 When any filters are present sessions will ignore all devices which do not
 match the filters.
كثافة العمليات
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.Experimental
الحصول التجريبي ()
.tensorflow.ConfigProto.Experimental experimental = 16;
ConfigProto.Experimental.Builder
الحصول على التجريبية ()
.tensorflow.ConfigProto.Experimental experimental = 16;
ConfigProto.ExperimentalOrBuilder
الحصول على التجريبية أو البناء ()
.tensorflow.ConfigProto.Experimental experimental = 16;
خيارات GPU
خيارات getGpu ()
 Options that apply to all GPUs.
GPUOptions.Builder
الحصول علىGpuOptionsBuilder ()
 Options that apply to all GPUs.
GPUOptionsOrBuilder
getGpuOptionsOrBuilder ()
 Options that apply to all GPUs.
خيارات الرسم البياني
خيارات الرسم البياني ()
 Options that apply to all graphs.
GraphOptions.Builder
الحصول على GraphOptionsBuilder ()
 Options that apply to all graphs.
GraphOptionsOrBuilder
الحصول على GraphOptionsOrBuilder ()
 Options that apply to all graphs.
كثافة العمليات
getInterOpParallelismThreads ()
 Nodes that perform blocking operations are enqueued on a pool of
 inter_op_parallelism_threads available in each process.
كثافة العمليات
getIntraOpParallelismThreads ()
 The execution of an individual op (for some op types) can be
 parallelized on a pool of intra_op_parallelism_threads.
منطقية
getIsolateSessionState ()
 If true, any resources such as Variables used in the session will not be
 shared with other sessions.
منطقية
getLogDevicePlacement ()
 Whether device placements should be logged.
خريطة<سلسلة، عدد صحيح>
getMutableDeviceCount ()
استخدم أدوات الوصول البديلة للطفرات بدلاً من ذلك.
طويل
الحصول علىOperationTimeoutInMs ()
 Global timeout for all blocking operations in this session.
كثافة العمليات
الحصول على فترة التنسيب ()
 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).
خيارات RPC
خيارات الحصول على Rpc ()
 Options that apply when this session uses the distributed runtime.
RPCOptions.Builder
الحصول علىRpcOptionsBuilder ()
 Options that apply when this session uses the distributed runtime.
RPCOptionsOrBuilder
getRpcOptionsOrBuilder ()
 Options that apply when this session uses the distributed runtime.
ThreadPoolOptionProto
getSessionInterOpThreadPool (فهرس كثافة العمليات)
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ThreadPoolOptionProto.Builder
getSessionInterOpThreadPoolBuilder (فهرس كثافة العمليات)
 This option is experimental - it may be replaced with a different mechanism
 in the future.
القائمة< ThreadPoolOptionProto.Builder >
getSessionInterOpThreadPoolBuilderList ()
 This option is experimental - it may be replaced with a different mechanism
 in the future.
كثافة العمليات
getSessionInterOpThreadPoolCount ()
 This option is experimental - it may be replaced with a different mechanism
 in the future.
القائمة< ThreadPoolOptionProto >
getSessionInterOpThreadPoolList ()
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ThreadPoolOptionProtoOrBuilder
getSessionInterOpThreadPoolOrBuilder (فهرس كثافة العمليات)
 This option is experimental - it may be replaced with a different mechanism
 in the future.
القائمة<؟ يمتد ThreadPoolOptionProtoOrBuilder >
getSessionInterOpThreadPoolOrBuilderList ()
 This option is experimental - it may be replaced with a different mechanism
 in the future.
منطقية
getShareClusterDevicesInSession ()
 When true, WorkerSessions are created with device attributes from the
 full cluster.
منطقية
getUsePerSessionThreads ()
 If true, use a new set of threads for this session rather than the global
 pool of threads.
منطقية
hasClusterDef ()
 Optional list of all workers to use in this session.
منطقية
تجريبي ()
.tensorflow.ConfigProto.Experimental experimental = 16;
منطقية
hasGpuOptions ()
 Options that apply to all GPUs.
منطقية
hasGraphOptions ()
 Options that apply to all graphs.
منطقية
hasRpcOptions ()
 Options that apply when this session uses the distributed runtime.
منطقية نهائية
ConfigProto.Builder
mergeClusterDef (قيمة ClusterDef )
 Optional list of all workers to use in this session.
ConfigProto.Builder
دمج تجريبي (قيمة ConfigProto.Experimental )
.tensorflow.ConfigProto.Experimental experimental = 16;
ConfigProto.Builder
دمج من (com.google.protobuf.Message أخرى)
ConfigProto.Builder
دمج من (com.google.protobuf.CodedInputStream input، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
ConfigProto.Builder
mergeGpuOptions (قيمة GPUOptions )
 Options that apply to all GPUs.
ConfigProto.Builder
mergeGraphOptions (قيمة GraphOptions )
 Options that apply to all graphs.
ConfigProto.Builder
mergeRpcOptions (قيمة RPCOptions )
 Options that apply when this session uses the distributed runtime.
النهائي ConfigProto.Builder
دمجUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields)
ConfigProto.Builder
putAllDeviceCount (قيم Map<String, Integer>)
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
ConfigProto.Builder
putDeviceCount (مفتاح السلسلة، قيمة int)
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
ConfigProto.Builder
RemoveDeviceCount (مفتاح السلسلة)
 Map from device type name (e.g., "CPU" or "GPU" ) to maximum
 number of devices of that type to use.
ConfigProto.Builder
إزالةSessionInterOpThreadPool (فهرس كثافة العمليات)
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ConfigProto.Builder
setAllowSoftPlacement (قيمة منطقية)
 Whether soft placement is allowed.
ConfigProto.Builder
setClusterDef ( ClusterDef.Builder builderForValue)
 Optional list of all workers to use in this session.
ConfigProto.Builder
setClusterDef (قيمة ClusterDef )
 Optional list of all workers to use in this session.
ConfigProto.Builder
setDeviceFilters (مؤشر int، قيمة السلسلة)
 When any filters are present sessions will ignore all devices which do not
 match the filters.
ConfigProto.Builder
setExperimental (قيمة ConfigProto.Experimental )
.tensorflow.ConfigProto.Experimental experimental = 16;
ConfigProto.Builder
setExperimental ( ConfigProto.Experimental.Builder builderForValue)
.tensorflow.ConfigProto.Experimental experimental = 16;
ConfigProto.Builder
setField (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن)
ConfigProto.Builder
setGpuOptions ( GPUOptions.Builder builderForValue)
 Options that apply to all GPUs.
ConfigProto.Builder
setGpuOptions (قيمة GPUOptions )
 Options that apply to all GPUs.
ConfigProto.Builder
setGraphOptions ( GraphOptions.Builder builderForValue)
 Options that apply to all graphs.
ConfigProto.Builder
setGraphOptions (قيمة GraphOptions )
 Options that apply to all graphs.
ConfigProto.Builder
setInterOpParallelismThreads (قيمة int)
 Nodes that perform blocking operations are enqueued on a pool of
 inter_op_parallelism_threads available in each process.
ConfigProto.Builder
setIntraOpParallelismThreads (قيمة int)
 The execution of an individual op (for some op types) can be
 parallelized on a pool of intra_op_parallelism_threads.
ConfigProto.Builder
setIsolateSessionState (قيمة منطقية)
 If true, any resources such as Variables used in the session will not be
 shared with other sessions.
ConfigProto.Builder
setLogDevicePlacement (قيمة منطقية)
 Whether device placements should be logged.
ConfigProto.Builder
setOperationTimeoutInMs (قيمة طويلة)
 Global timeout for all blocking operations in this session.
ConfigProto.Builder
setPlacementPeriod (قيمة int)
 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).
ConfigProto.Builder
setRepeatedField (حقل com.google.protobuf.Descriptors.FieldDescriptor، فهرس int، قيمة الكائن)
ConfigProto.Builder
setRpcOptions (قيمة RPCOptions )
 Options that apply when this session uses the distributed runtime.
ConfigProto.Builder
setRpcOptions ( RPCOptions.Builder builderForValue)
 Options that apply when this session uses the distributed runtime.
ConfigProto.Builder
setSessionInterOpThreadPool (مؤشر int، قيمة ThreadPoolOptionProto )
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ConfigProto.Builder
setSessionInterOpThreadPool (فهرس كثافة العمليات، ThreadPoolOptionProto.Builder builderForValue)
 This option is experimental - it may be replaced with a different mechanism
 in the future.
ConfigProto.Builder
setShareClusterDevicesInSession (قيمة منطقية)
 When true, WorkerSessions are created with device attributes from the
 full cluster.
النهائي ConfigProto.Builder
setUnknownFields (com.google.protobuf.UnknownFieldSet UnknownFields)
ConfigProto.Builder
setUsePerSessionThreads (قيمة منطقية)
 If true, use a new set of threads for this session rather than the global
 pool of threads.

الطرق الموروثة

الأساليب العامة

public ConfigProto.Builder addAllDeviceFilters (قيم Iterable<String>)

 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.Builder addAllSessionInterOpThreadPool (Iterable<؟ يمتد ThreadPoolOptionProto > القيم)

 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 ConfigProto.Builder addDeviceFilters (قيمة السلسلة)

 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.Builder addDeviceFiltersBytes (قيمة com.google.protobuf.ByteString)

 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.Builder addRepeatedField (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن)

public ConfigProto.Builder addSessionInterOpThreadPool (قيمة ThreadPoolOptionProto )

 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 ConfigProto.Builder addSessionInterOpThreadPool (مؤشر int، قيمة ThreadPoolOptionProto )

 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 ConfigProto.Builder addSessionInterOpThreadPool ( ThreadPoolOptionProto.Builder builderForValue)

 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 ConfigProto.Builder addSessionInterOpThreadPool (مؤشر int، ThreadPoolOptionProto.Builder builderForValue)

 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;

ThreadPoolOptionProto.Builder العام addSessionInterOpThreadPoolBuilder (فهرس كثافة العمليات)

 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;

ThreadPoolOptionProto.Builder العام addSessionInterOpThreadPoolBuilder ()

 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;

بناء ConfigProto العام ()

بناء ConfigProto العام جزئيًا ()

مسح ConfigProto.Builder العام ()

ConfigProto.Builder العام ClearAllowSoftPlacement ()

 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;

ConfigProto.Builder العام ClearClusterDef ()

 Optional list of all workers to use in this session.
 
.tensorflow.ClusterDef cluster_def = 14;

ConfigProto.Builder العام ClearDeviceCount ()

ConfigProto.Builder العامة ClearDeviceFilters ()

 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;

ConfigProto.Builder العام ClearExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

ConfigProto.Builder ClearField العام (حقل com.google.protobuf.Descriptors.FieldDescriptor)

ConfigProto.Builder العام ClearGpuOptions ()

 Options that apply to all GPUs.
 
.tensorflow.GPUOptions gpu_options = 6;

ConfigProto.Builder العامة ClearGraphOptions ()

 Options that apply to all graphs.
 
.tensorflow.GraphOptions graph_options = 10;

ConfigProto.Builder العام ClearInterOpParallelismThreads ()

 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;

ConfigProto.Builder العام ClearIntraOpParallelismThreads ()

 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;

ConfigProto.Builder العام ClearIsolateSessionState ()

 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;

ConfigProto.Builder العام ClearLogDevicePlacement ()

 Whether device placements should be logged.
 
bool log_device_placement = 8;

العام ConfigProto.Builder ClearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)

ConfigProto.Builder العام ClearOperationTimeoutInMs ()

 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;

ConfigProto.Builder العام ClearPlacementPeriod ()

 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;

ConfigProto.Builder العام ClearRpcOptions ()

 Options that apply when this session uses the distributed runtime.
 
.tensorflow.RPCOptions rpc_options = 13;

ConfigProto.Builder العام ClearSessionInterOpThreadPool ()

 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;

ConfigProto.Builder العام ClearShareClusterDevicesInSession ()

 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;

ConfigProto.Builder العام ClearUsePerSessionThreads ()

 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;

استنساخ ConfigProto.Builder العام ()

المنطقية العامة تحتوي علىDeviceCount (مفتاح السلسلة)

 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;

getAllowSoftPlacement () المنطقية العامة

 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;

ClusterDef العامة getClusterDef ()

 Optional list of all workers to use in this session.
 
.tensorflow.ClusterDef cluster_def = 14;

ClusterDef.Builder العامة getClusterDefBuilder ()

 Optional list of all workers to use in this session.
 
.tensorflow.ClusterDef cluster_def = 14;

getClusterDefOrBuilder العامة getClusterDefOrBuilder ()

 Optional list of all workers to use in this session.
 
.tensorflow.ClusterDef cluster_def = 14;

ConfigProto العامة getDefaultInstanceForType ()

النهائي العام الثابت com.google.protobuf.Descriptors.Descriptor getDescriptor ()

com.google.protobuf.Descriptors.Descriptor getDescriptorForType () العام

الخريطة العامة<String, Integer> getDeviceCount ()

استخدم getDeviceCountMap() بدلاً من ذلك.

int public 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;

الخريطة العامة<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;

int public getDeviceCountOrDefault (مفتاح السلسلة، 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;

int public getDeviceCountOrThrow (مفتاح السلسلة)

 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;

سلسلة getDeviceFilters العامة (مؤشر 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;

com.google.protobuf.ByteString getDeviceFiltersBytes العام (مؤشر 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;

int public 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;

com.google.protobuf.ProtocolStringList العامة 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;

ConfigProto.Experimental getExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

ConfigProto.Experimental.Builder العامة getExperimentalBuilder ()

.tensorflow.ConfigProto.Experimental experimental = 16;

ConfigProto.ExperimentalOrBuilder العامة getExperimentalOrBuilder ()

.tensorflow.ConfigProto.Experimental experimental = 16;

خيارات GPU العامة getGpuOptions ()

 Options that apply to all GPUs.
 
.tensorflow.GPUOptions gpu_options = 6;

GPUOptions.Builder العام getGpuOptionsBuilder ()

 Options that apply to all GPUs.
 
.tensorflow.GPUOptions gpu_options = 6;

GPUOptionsOrBuilder العام getGpuOptionsOrBuilder ()

 Options that apply to all GPUs.
 
.tensorflow.GPUOptions gpu_options = 6;

خيارات GraphOptions العامة getGraphOptions ()

 Options that apply to all graphs.
 
.tensorflow.GraphOptions graph_options = 10;

GraphOptions.Builder العامة getGraphOptionsBuilder ()

 Options that apply to all graphs.
 
.tensorflow.GraphOptions graph_options = 10;

GraphOptionsOrBuilder العام getGraphOptionsOrBuilder ()

 Options that apply to all graphs.
 
.tensorflow.GraphOptions graph_options = 10;

int public 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;

int العام 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;

getIsolateSessionState () المنطقية العامة

 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;

getLogDevicePlacement () المنطقية العامة

 Whether device placements should be logged.
 
bool log_device_placement = 8;

الخريطة العامة<String, Integer> getMutableDeviceCount ()

استخدم أدوات الوصول البديلة للطفرات بدلاً من ذلك.

getOperationTimeoutInMs العامة الطويلة ()

 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;

int public 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 العامة getRpcOptions ()

 Options that apply when this session uses the distributed runtime.
 
.tensorflow.RPCOptions rpc_options = 13;

RPCOptions.Builder العامة getRpcOptionsBuilder ()

 Options that apply when this session uses the distributed runtime.
 
.tensorflow.RPCOptions rpc_options = 13;

RPCOptionsOrBuilder العام getRpcOptionsOrBuilder ()

 Options that apply when this session uses the distributed runtime.
 
.tensorflow.RPCOptions rpc_options = 13;

ThreadPoolOptionProto public getSessionInterOpThreadPool (مؤشر 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;

ThreadPoolOptionProto.Builder العام getSessionInterOpThreadPoolBuilder (فهرس كثافة العمليات)

 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;

القائمة العامة< ThreadPoolOptionProto.Builder > getSessionInterOpThreadPoolBuilderList ()

 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;

int public 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;

القائمة العامة< 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;

ThreadPoolOptionProtoOrBuilder العام getSessionInterOpThreadPoolOrBuilder (فهرس كثافة العمليات)

 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;

القائمة العامة <؟ يمتد 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;

getShareClusterDevicesInSession () المنطقية العامة

 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;

getUsePerSessionThreads المنطقية العامة ()

 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;

المنطق المنطقي العام hasClusterDef ()

 Optional list of all workers to use in this session.
 
.tensorflow.ClusterDef cluster_def = 14;

القيمة المنطقية العامة تجريبية ()

.tensorflow.ConfigProto.Experimental experimental = 16;

المنطق المنطقي العام hasGpuOptions ()

 Options that apply to all GPUs.
 
.tensorflow.GPUOptions gpu_options = 6;

المنطق المنطقي العام hasGraphOptions ()

 Options that apply to all graphs.
 
.tensorflow.GraphOptions graph_options = 10;

hasRpcOptions () المنطقية العامة

 Options that apply when this session uses the distributed runtime.
 
.tensorflow.RPCOptions rpc_options = 13;

تمت تهيئة القيمة المنطقية النهائية العامة ()

ConfigProto.Builder العام mergeClusterDef (قيمة ClusterDef )

 Optional list of all workers to use in this session.
 
.tensorflow.ClusterDef cluster_def = 14;

دمج ConfigProto.Builder العام (قيمة ConfigProto.Experimental )

.tensorflow.ConfigProto.Experimental experimental = 16;

العام ConfigProto.Builder mergeFrom (com.google.protobuf.Message أخرى)

عام ConfigProto.Builder mergeFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

رميات
IOEException

عام ConfigProto.Builder mergeGpuOptions (قيمة GPUOptions )

 Options that apply to all GPUs.
 
.tensorflow.GPUOptions gpu_options = 6;

عام ConfigProto.Builder mergeGraphOptions (قيمة GraphOptions )

 Options that apply to all graphs.
 
.tensorflow.GraphOptions graph_options = 10;

عام ConfigProto.Builder mergeRpcOptions (قيمة RPCOptions )

 Options that apply when this session uses the distributed runtime.
 
.tensorflow.RPCOptions rpc_options = 13;

النهائي العام ConfigProto.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSetUnknownFields)

public ConfigProto.Builder putAllDeviceCount (قيم Map<String, Integer>)

 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;

ConfigProto.Builder العام putDeviceCount (مفتاح السلسلة، قيمة int)

 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;

إزالة ConfigProto.Builder العامة (مفتاح السلسلة)

 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;

ConfigProto.Builder العام RemoveSessionInterOpThreadPool (فهرس كثافة العمليات)

 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;

مجموعة ConfigProto.Builder العامة AllowSoftPlacement (قيمة منطقية)

 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;

مجموعة ConfigProto.Builder العامة ClusterDef ( ClusterDef.Builder builderForValue)

 Optional list of all workers to use in this session.
 
.tensorflow.ClusterDef cluster_def = 14;

مجموعة ConfigProto.Builder العامة ClusterDef (قيمة ClusterDef )

 Optional list of all workers to use in this session.
 
.tensorflow.ClusterDef cluster_def = 14;

مجموعة ConfigProto.Builder العامة (مؤشر int، قيمة السلسلة)

 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;

مجموعة ConfigProto.Builder العامة التجريبية (قيمة ConfigProto.Experimental )

.tensorflow.ConfigProto.Experimental experimental = 16;

مجموعة ConfigProto.Builder العامة التجريبية ( ConfigProto.Experimental.Builder builderForValue)

.tensorflow.ConfigProto.Experimental experimental = 16;

public ConfigProto.Builder setField (حقل com.google.protobuf.Descriptors.FieldDescriptor، قيمة الكائن)

مجموعة ConfigProto.Builder العامة GpuOptions ( GPUOptions.Builder builderForValue)

 Options that apply to all GPUs.
 
.tensorflow.GPUOptions gpu_options = 6;

مجموعة ConfigProto.Builder العامة GpuOptions (قيمة GPUOptions )

 Options that apply to all GPUs.
 
.tensorflow.GPUOptions gpu_options = 6;

مجموعة ConfigProto.Builder العامة GraphOptions ( GraphOptions.Builder builderForValue)

 Options that apply to all graphs.
 
.tensorflow.GraphOptions graph_options = 10;

مجموعة ConfigProto.Builder العامة GraphOptions (قيمة GraphOptions )

 Options that apply to all graphs.
 
.tensorflow.GraphOptions graph_options = 10;

مجموعة ConfigProto.Builder العامة InterOpParallelismThreads (قيمة int)

 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;

مجموعة ConfigProto.Builder العامة IntraOpParallelismThreads (قيمة int)

 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;

مجموعة ConfigProto.Builder العامة IsolateSessionState (قيمة منطقية)

 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;

مجموعة ConfigProto.Builder العامة ، LogDevicePlacement (قيمة منطقية)

 Whether device placements should be logged.
 
bool log_device_placement = 8;

ConfigProto.Builder العام setOperationTimeoutInMs (قيمة طويلة)

 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;

مجموعة ConfigProto.Builder العامة PlacementPeriod (قيمة int)

 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;

ConfigProto.Builder العام setRepeatedField (حقل com.google.protobuf.Descriptors.FieldDescriptor، مؤشر int، قيمة الكائن)

مجموعة ConfigProto.Builder العامة (قيمة RPCOptions )

 Options that apply when this session uses the distributed runtime.
 
.tensorflow.RPCOptions rpc_options = 13;

مجموعة ConfigProto.Builder العامة ( RPCOptions.Builder builderForValue)

 Options that apply when this session uses the distributed runtime.
 
.tensorflow.RPCOptions rpc_options = 13;

مجموعة ConfigProto.Builder العامة SessionInterOpThreadPool (مؤشر int، قيمة ThreadPoolOptionProto )

 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;

مجموعة ConfigProto.Builder العامة SessionInterOpThreadPool (مؤشر int، ThreadPoolOptionProto.Builder builderForValue)

 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;

مجموعة ConfigProto.Builder العامة ShareClusterDevicesInSession (قيمة منطقية)

 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;

النهائي العام ConfigProto.Builder setUnknownFields (com.google.protobuf.UnknownFieldSetUnknownFields)

مجموعة ConfigProto.Builder العامة UsePerSessionThreads (قيمة منطقية)

 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;