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ConfigProto.Builder

publiczna statyczna klasa końcowa ConfigProto.Builder

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

Protobuf typu tensorflow.ConfigProto

Metody publiczne

ConfigProto.Builder	addAllDeviceFilters (wartości Iterable<String>) When any filters are present sessions will ignore all devices which do not match the filters.
ConfigProto.Builder	addAllSessionInterOpThreadPool (Iterable<? rozszerza wartości ThreadPoolOptionProto >) This option is experimental - it may be replaced with a different mechanism in the future.
ConfigProto.Builder	addDeviceFilters (wartość ciągu) When any filters are present sessions will ignore all devices which do not match the filters.
ConfigProto.Builder	addDeviceFiltersBytes (wartość com.google.protobuf.ByteString) When any filters are present sessions will ignore all devices which do not match the filters.
ConfigProto.Builder	addRepeatedField (pole com.google.protobuf.Descriptors.FieldDescriptor, wartość obiektu)
ConfigProto.Builder	addSessionInterOpThreadPool (wartość ThreadPoolOptionProto ) This option is experimental - it may be replaced with a different mechanism in the future.
ConfigProto.Builder	addSessionInterOpThreadPool (indeks int, wartość 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 (indeks int, ThreadPoolOptionProto.Builder builderForValue) This option is experimental - it may be replaced with a different mechanism in the future.
ThreadPoolOptionProto.Builder	addSessionInterOpThreadPoolBuilder (indeks int) 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.
KonfiguracjaProto	zbudować ()
KonfiguracjaProto	kompilacjaCzęściowa ()
ConfigProto.Builder	jasne ()
ConfigProto.Builder	clearAllowSoftPlacement () Whether soft placement is allowed.
ConfigProto.Builder	wyczyśćClusterDef () Optional list of all workers to use in this session.
ConfigProto.Builder	wyczyść liczbę urządzeń ()
ConfigProto.Builder	wyczyść filtry urządzeń () When any filters are present sessions will ignore all devices which do not match the filters.
ConfigProto.Builder	jasneEksperymentalne () `.tensorflow.ConfigProto.Experimental experimental = 16;`
ConfigProto.Builder	clearField (pole com.google.protobuf.Descriptors.FieldDescriptor)
ConfigProto.Builder	wyczyśćGpuOpcje () Options that apply to all GPUs.
ConfigProto.Builder	clearGraphOptions () 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	wyczyśćIsolateSessionState () 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	wyczyśćPlacementPeriod () 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	wyczyśćRpcOpcje () 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	klon ()
wartość logiczna	zawieraDeviceCount (klucz ciąg) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
wartość logiczna	getAllowSoftPlacement () Whether soft placement is allowed.
KlasterDef	pobierzClusterDef () Optional list of all workers to use in this session.
Konstruktor defibrylacji klastrów	getClusterDefBuilder () Optional list of all workers to use in this session.
ClusterDefOrBuilder	getClusterDefOrBuilder () Optional list of all workers to use in this session.
KonfiguracjaProto	getDefaultInstanceForType ()
końcowy statyczny com.google.protobuf.Descriptors.Descriptor	pobierzDescriptor ()
com.google.protobuf.Descriptors.Descriptor	getDescriptorForType ()
Mapa<String, Integer>	pobierz liczbę urządzeń () Zamiast tego użyj funkcji `getDeviceCountMap()` .
wew	getDeviceCountCount () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
Mapa<String, Integer>	getDeviceCountMap () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
wew	getDeviceCountOrDefault (klucz ciągu, int wartość domyślna) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
wew	getDeviceCountOrThrow (klucz ciąg) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
Smyczkowy	getDeviceFilters (indeks int) When any filters are present sessions will ignore all devices which do not match the filters.
com.google.protobuf.ByteString	getDeviceFiltersBytes (indeks int) When any filters are present sessions will ignore all devices which do not match the filters.
wew	pobierz liczbę filtrów urządzeń () When any filters are present sessions will ignore all devices which do not match the filters.
com.google.protobuf.ProtocolStringList	pobierz listę filtrów urządzeń () When any filters are present sessions will ignore all devices which do not match the filters.
ConfigProto.Eksperymentalny	uzyskaj eksperymentalny () `.tensorflow.ConfigProto.Experimental experimental = 16;`
ConfigProto.Experimental.Builder	getExperimentalBuilder () `.tensorflow.ConfigProto.Experimental experimental = 16;`
ConfigProto.ExperimentalOrBuilder	getExperimentalOrBuilder () `.tensorflow.ConfigProto.Experimental experimental = 16;`
Opcje GPU	getGpuOptions () Options that apply to all GPUs.
Opcje GPU. Konstruktor	getGpuOptionsBuilder () Options that apply to all GPUs.
Opcje GPULubBuilder	getGpuOptionsOrBuilder () Options that apply to all GPUs.
Opcje wykresu	getGraphOptions () Options that apply to all graphs.
GraphOptions.Builder	getGraphOptionsBuilder () Options that apply to all graphs.
GraphOptionsOrBuilder	getGraphOptionsOrBuilder () Options that apply to all graphs.
wew	getInterOpParallelismThreads () Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process.
wew	getIntraOpParallelismThreads () The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads.
wartość logiczna	getIsolateSessionState () If true, any resources such as Variables used in the session will not be shared with other sessions.
wartość logiczna	getLogDevicePlacement () Whether device placements should be logged.
Mapa<String, Integer>	getMutableDeviceCount () Zamiast tego użyj alternatywnych akcesorów mutacji.
długi	getOperationTimeoutInMs () Global timeout for all blocking operations in this session.
wew	pobierzPlacementPeriod () 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).
Opcje RPC	getRpcOptions () Options that apply when this session uses the distributed runtime.
Konstruktor RPCOptions.Builder	getRpcOptionsBuilder () Options that apply when this session uses the distributed runtime.
RPCOptionsOrBuilder	getRpcOptionsOrBuilder () Options that apply when this session uses the distributed runtime.
ThreadPoolOpcjaProto	getSessionInterOpThreadPool (indeks int) This option is experimental - it may be replaced with a different mechanism in the future.
ThreadPoolOptionProto.Builder	getSessionInterOpThreadPoolBuilder (indeks int) This option is experimental - it may be replaced with a different mechanism in the future.
Lista< ThreadPoolOptionProto.Builder >	getSessionInterOpThreadPoolBuilderList () This option is experimental - it may be replaced with a different mechanism in the future.
wew	getSessionInterOpThreadPoolCount () This option is experimental - it may be replaced with a different mechanism in the future.
Lista< ThreadPoolOptionProto >	getSessionInterOpThreadPoolList () This option is experimental - it may be replaced with a different mechanism in the future.
ThreadPoolOptionProtoOrBuilder	getSessionInterOpThreadPoolOrBuilder (indeks int) This option is experimental - it may be replaced with a different mechanism in the future.
Lista<? rozszerza ThreadPoolOptionProtoOrBuilder >	getSessionInterOpThreadPoolOrBuilderList () This option is experimental - it may be replaced with a different mechanism in the future.
wartość logiczna	getShareClusterDevicesInSession () When true, WorkerSessions are created with device attributes from the full cluster.
wartość logiczna	getUsePerSessionThreads () If true, use a new set of threads for this session rather than the global pool of threads.
wartość logiczna	maClusterDef () Optional list of all workers to use in this session.
wartość logiczna	maEksperymentalny () `.tensorflow.ConfigProto.Experimental experimental = 16;`
wartość logiczna	maGpuOpcje () Options that apply to all GPUs.
wartość logiczna	maGraphOptions () Options that apply to all graphs.
wartość logiczna	maRpcOptions () Options that apply when this session uses the distributed runtime.
końcowa wartość logiczna	jest zainicjowany ()
ConfigProto.Builder	mergeClusterDef (wartość ClusterDef ) Optional list of all workers to use in this session.
ConfigProto.Builder	mergeExperimental (wartość ConfigProto.Experimental ) `.tensorflow.ConfigProto.Experimental experimental = 16;`
ConfigProto.Builder	mergeFrom (com.google.protobuf.Wiadomość inna)
ConfigProto.Builder	mergeFrom (wejście com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
ConfigProto.Builder	mergeGpuOptions (wartość GPUOptions ) Options that apply to all GPUs.
ConfigProto.Builder	mergeGraphOptions (wartość GraphOptions ) Options that apply to all graphs.
ConfigProto.Builder	mergeRpcOptions (wartość RPCOptions ) Options that apply when this session uses the distributed runtime.
końcowy ConfigProto.Builder	mergeUnknownFields (com.google.protobuf.UnknownFieldUstaw nieznane pola)
ConfigProto.Builder	putAllDeviceCount (wartości 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 (klucz ciągu, wartość int) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
ConfigProto.Builder	usuńDeviceCount (klucz ciąg) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
ConfigProto.Builder	usuńSessionInterOpThreadPool (indeks int) This option is experimental - it may be replaced with a different mechanism in the future.
ConfigProto.Builder	setAllowSoftPlacement (wartość logiczna) Whether soft placement is allowed.
ConfigProto.Builder	setClusterDef ( ClusterDef.Builder builderForValue) Optional list of all workers to use in this session.
ConfigProto.Builder	setClusterDef (wartość ClusterDef ) Optional list of all workers to use in this session.
ConfigProto.Builder	setDeviceFilters (indeks int, wartość ciągu) When any filters are present sessions will ignore all devices which do not match the filters.
ConfigProto.Builder	setExperimental (wartość ConfigProto.Experimental ) `.tensorflow.ConfigProto.Experimental experimental = 16;`
ConfigProto.Builder	setExperimental ( ConfigProto.Experimental.Builder builderForValue) `.tensorflow.ConfigProto.Experimental experimental = 16;`
ConfigProto.Builder	setField (pole com.google.protobuf.Descriptors.FieldDescriptor, wartość obiektu)
ConfigProto.Builder	setGpuOptions ( GPUOptions.Builder builderForValue) Options that apply to all GPUs.
ConfigProto.Builder	setGpuOptions (wartość GPUOptions ) Options that apply to all GPUs.
ConfigProto.Builder	setGraphOptions ( GraphOptions.Builder builderForValue) Options that apply to all graphs.
ConfigProto.Builder	setGraphOptions (wartość GraphOptions ) Options that apply to all graphs.
ConfigProto.Builder	setInterOpParallelismThreads (wartość int) Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process.
ConfigProto.Builder	setIntraOpParallelismThreads (wartość 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 (wartość logiczna) If true, any resources such as Variables used in the session will not be shared with other sessions.
ConfigProto.Builder	setLogDevicePlacement (wartość logiczna) Whether device placements should be logged.
ConfigProto.Builder	setOperationTimeoutInMs (długa wartość) Global timeout for all blocking operations in this session.
ConfigProto.Builder	setPlacementPeriod (wartość 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 (pole com.google.protobuf.Descriptors.FieldDescriptor, indeks int, wartość obiektu)
ConfigProto.Builder	setRpcOptions (wartość 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 (indeks int, wartość ThreadPoolOptionProto ) This option is experimental - it may be replaced with a different mechanism in the future.
ConfigProto.Builder	setSessionInterOpThreadPool (indeks int, ThreadPoolOptionProto.Builder builderForValue) This option is experimental - it may be replaced with a different mechanism in the future.
ConfigProto.Builder	setShareClusterDevicesInSession (wartość logiczna) When true, WorkerSessions are created with device attributes from the full cluster.
końcowy ConfigProto.Builder	setUnknownFields (com.google.protobuf.UnknownFieldUstaw nieznane pola)
ConfigProto.Builder	setUsePerSessionThreads (wartość logiczna) If true, use a new set of threads for this session rather than the global pool of threads.

Metody dziedziczone

Z klasy java.lang.Object

wartość logiczna	równa się (Obiekt arg0)
ostatnia klasa<?>	pobierzKlasę ()
wew	hashCode ()
ostateczna pustka	powiadomić ()
ostateczna pustka	powiadom wszystkich ()
Smyczkowy	doString ()
ostateczna pustka	czekaj (długi arg0, int arg1)
ostateczna pustka	czekaj (długi arg0)
ostateczna pustka	Czekać ()

Z interfejsu org.tensorflow.proto.framework.ConfigProtoOrBuilder

abstrakcyjna wartość logiczna	zawieraDeviceCount (klucz ciąg) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
abstrakcyjna wartość logiczna	getAllowSoftPlacement () Whether soft placement is allowed.
abstrakcyjny ClusterDef	pobierzClusterDef () Optional list of all workers to use in this session.
abstrakcyjny ClusterDefOrBuilder	getClusterDefOrBuilder () Optional list of all workers to use in this session.
abstrakcyjna Mapa<String, Integer>	pobierz liczbę urządzeń () Zamiast tego użyj funkcji `getDeviceCountMap()` .
streszczenie wew	getDeviceCountCount () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
abstrakcyjna Mapa<String, Integer>	getDeviceCountMap () Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
streszczenie wew	getDeviceCountOrDefault (klucz ciągu, int wartość domyślna) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
streszczenie wew	getDeviceCountOrThrow (klucz ciąg) Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use.
abstrakcyjny ciąg	getDeviceFilters (indeks int) When any filters are present sessions will ignore all devices which do not match the filters.
streszczenie com.google.protobuf.ByteString	getDeviceFiltersBytes (indeks int) When any filters are present sessions will ignore all devices which do not match the filters.
streszczenie wew	pobierz liczbę filtrów urządzeń () When any filters are present sessions will ignore all devices which do not match the filters.
lista abstrakcyjna<String>	pobierz listę filtrów urządzeń () When any filters are present sessions will ignore all devices which do not match the filters.
streszczenie ConfigProto.Experimental	uzyskaj eksperymentalny () `.tensorflow.ConfigProto.Experimental experimental = 16;`
streszczenie ConfigProto.ExperimentalOrBuilder	getExperimentalOrBuilder () `.tensorflow.ConfigProto.Experimental experimental = 16;`
abstrakcyjne opcje GPU	getGpuOptions () Options that apply to all GPUs.
abstrakcyjne opcje GPUOrBuilder	getGpuOptionsOrBuilder () Options that apply to all GPUs.
abstrakcyjne opcje wykresu	getGraphOptions () Options that apply to all graphs.
streszczenie GraphOptionsOrBuilder	getGraphOptionsOrBuilder () Options that apply to all graphs.
streszczenie wew	getInterOpParallelismThreads () Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process.
streszczenie wew	getIntraOpParallelismThreads () The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads.
abstrakcyjna wartość logiczna	getIsolateSessionState () If true, any resources such as Variables used in the session will not be shared with other sessions.
abstrakcyjna wartość logiczna	getLogDevicePlacement () Whether device placements should be logged.
streszczenie długie	getOperationTimeoutInMs () Global timeout for all blocking operations in this session.
streszczenie wew	pobierzPlacementPeriod () 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).
abstrakcyjne opcje RPCOptions	getRpcOptions () Options that apply when this session uses the distributed runtime.
streszczenie RPCOptionsOrBuilder	getRpcOptionsOrBuilder () Options that apply when this session uses the distributed runtime.
streszczenie ThreadPoolOptionProto	getSessionInterOpThreadPool (indeks int) This option is experimental - it may be replaced with a different mechanism in the future.
streszczenie wew	getSessionInterOpThreadPoolCount () This option is experimental - it may be replaced with a different mechanism in the future.
lista abstrakcyjna< ThreadPoolOptionProto >	getSessionInterOpThreadPoolList () This option is experimental - it may be replaced with a different mechanism in the future.
streszczenie ThreadPoolOptionProtoOrBuilder	getSessionInterOpThreadPoolOrBuilder (indeks int) This option is experimental - it may be replaced with a different mechanism in the future.
lista abstrakcyjna<? rozszerza ThreadPoolOptionProtoOrBuilder >	getSessionInterOpThreadPoolOrBuilderList () This option is experimental - it may be replaced with a different mechanism in the future.
abstrakcyjna wartość logiczna	getShareClusterDevicesInSession () When true, WorkerSessions are created with device attributes from the full cluster.
abstrakcyjna wartość logiczna	getUsePerSessionThreads () If true, use a new set of threads for this session rather than the global pool of threads.
abstrakcyjna wartość logiczna	maClusterDef () Optional list of all workers to use in this session.
abstrakcyjna wartość logiczna	maEksperymentalny () `.tensorflow.ConfigProto.Experimental experimental = 16;`
abstrakcyjna wartość logiczna	maGpuOpcje () Options that apply to all GPUs.
abstrakcyjna wartość logiczna	maGraphOptions () Options that apply to all graphs.
abstrakcyjna wartość logiczna	maRpcOptions () Options that apply when this session uses the distributed runtime.

Metody publiczne

public ConfigProto.Builder addAllDeviceFilters (wartości 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<? rozszerza wartości 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 addDeviceFilters (wartość ciągu)

 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 (wartość 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 (pole com.google.protobuf.Descriptors.FieldDescriptor, wartość obiektu)

public ConfigProto.Builder addSessionInterOpThreadPool (wartość 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 (indeks int, wartość 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 (indeks 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;

public ThreadPoolOptionProto.Builder addSessionInterOpThreadPoolBuilder (indeks 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;

publiczny ThreadPoolOptionProto.Builder 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;

publiczna kompilacja ConfigProto ()

public ConfigProto buildPartial ()

publiczny ConfigProto.Builder wyczyść ()

public ConfigProto.Builder 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;

public ConfigProto.Builder clearClusterDef ()

 Optional list of all workers to use in this session.

.tensorflow.ClusterDef cluster_def = 14;

public ConfigProto.Builder clearDeviceCount ()

public ConfigProto.Builder 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;

public ConfigProto.Builder clearExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

public ConfigProto.Builder clearField (pole com.google.protobuf.Descriptors.FieldDescriptor)

public ConfigProto.Builder clearGpuOptions ()

 Options that apply to all GPUs.

.tensorflow.GPUOptions gpu_options = 6;

public ConfigProto.Builder clearGraphOptions ()

 Options that apply to all graphs.

.tensorflow.GraphOptions graph_options = 10;

public ConfigProto.Builder 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;

public ConfigProto.Builder 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;

public ConfigProto.Builder 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;

public ConfigProto.Builder clearLogDevicePlacement ()

 Whether device placements should be logged.

bool log_device_placement = 8;

public ConfigProto.Builder clearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)

public ConfigProto.Builder 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;

public ConfigProto.Builder 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;

public ConfigProto.Builder clearRpcOptions ()

 Options that apply when this session uses the distributed runtime.

.tensorflow.RPCOptions rpc_options = 13;

public ConfigProto.Builder 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;

public ConfigProto.Builder 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;

public ConfigProto.Builder 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;

publiczny klon ConfigProto.Builder ()

publiczna wartość logiczna zawieraDeviceCount (klucz ciąg)

 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;

publiczna wartość logiczna 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;

publiczny ClusterDef getClusterDef ()

 Optional list of all workers to use in this session.

.tensorflow.ClusterDef cluster_def = 14;

publiczny ClusterDef.Builder getClusterDefBuilder ()

 Optional list of all workers to use in this session.

.tensorflow.ClusterDef cluster_def = 14;

public ClusterDefOrBuilder getClusterDefOrBuilder ()

 Optional list of all workers to use in this session.

.tensorflow.ClusterDef cluster_def = 14;

public ConfigProto getDefaultInstanceForType ()

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

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

public Map<String, Integer> getDeviceCount ()

Zamiast tego użyj funkcji getDeviceCountMap() .

publiczny int getDeviceCountCount ()

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

map<string, int32> device_count = 1;

public Map<String, Integer> getDeviceCountMap ()

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

map<string, int32> device_count = 1;

public int getDeviceCountOrDefault (klucz ciągu, int wartość domyślna)

 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 (klucz ciąg)

 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 (indeks 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 (indeks int)

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

repeated string device_filters = 4;

public int getDeviceFiltersCount ()

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

repeated string device_filters = 4;

public com.google.protobuf.ProtocolStringList getDeviceFiltersList ()

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

repeated string device_filters = 4;

public ConfigProto.Experimental getExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

public ConfigProto.Experimental.Builder getExperimentalBuilder ()

.tensorflow.ConfigProto.Experimental experimental = 16;

public ConfigProto.ExperimentalOrBuilder getExperimentalOrBuilder ()

.tensorflow.ConfigProto.Experimental experimental = 16;

publiczne GPUOptions getGpuOptions ()

 Options that apply to all GPUs.

.tensorflow.GPUOptions gpu_options = 6;

public GPUOptions.Builder getGpuOptionsBuilder ()

 Options that apply to all GPUs.

.tensorflow.GPUOptions gpu_options = 6;

publiczne GPUOptionsOrBuilder getGpuOptionsOrBuilder ()

 Options that apply to all GPUs.

.tensorflow.GPUOptions gpu_options = 6;

public GraphOptions getGraphOptions ()

 Options that apply to all graphs.

.tensorflow.GraphOptions graph_options = 10;

public GraphOptions.Builder getGraphOptionsBuilder ()

 Options that apply to all graphs.

.tensorflow.GraphOptions graph_options = 10;

public GraphOptionsOrBuilder getGraphOptionsOrBuilder ()

 Options that apply to all graphs.

.tensorflow.GraphOptions graph_options = 10;

public int getInterOpParallelismThreads ()

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

int32 inter_op_parallelism_threads = 5;

public int getIntraOpParallelismThreads ()

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

int32 intra_op_parallelism_threads = 2;

publiczna wartość logiczna 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;

publiczna wartość logiczna getLogDevicePlacement ()

 Whether device placements should be logged.

bool log_device_placement = 8;

public Map<String, Integer> getMutableDeviceCount ()

Zamiast tego użyj alternatywnych akcesorów mutacji.

publiczny długi 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;

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;

publiczne RPCOptions getRpcOptions ()

 Options that apply when this session uses the distributed runtime.

.tensorflow.RPCOptions rpc_options = 13;

publiczny RPCOptions.Builder getRpcOptionsBuilder ()

 Options that apply when this session uses the distributed runtime.

.tensorflow.RPCOptions rpc_options = 13;

publiczne RPCOptionsOrBuilder getRpcOptionsOrBuilder ()

 Options that apply when this session uses the distributed runtime.

.tensorflow.RPCOptions rpc_options = 13;

public ThreadPoolOptionProto getSessionInterOpThreadPool (indeks 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;

publiczny ThreadPoolOptionProto.Builder getSessionInterOpThreadPoolBuilder (indeks 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 List< 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;

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;

lista publiczna< 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;

publiczny ThreadPoolOptionProtoOrBuilder getSessionInterOpThreadPoolOrBuilder (indeks 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;

lista publiczna<? rozszerza 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;

publiczna wartość logiczna 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;

publiczna wartość logiczna 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;

publiczna wartość logiczna hasClusterDef ()

 Optional list of all workers to use in this session.

.tensorflow.ClusterDef cluster_def = 14;

publiczna wartość logiczna maExperimental ()

.tensorflow.ConfigProto.Experimental experimental = 16;

publiczna wartość logiczna hasGpuOptions ()

 Options that apply to all GPUs.

.tensorflow.GPUOptions gpu_options = 6;

publiczna wartość logiczna hasGraphOptions ()

 Options that apply to all graphs.

.tensorflow.GraphOptions graph_options = 10;

publiczna wartość logiczna hasRpcOptions ()

 Options that apply when this session uses the distributed runtime.

.tensorflow.RPCOptions rpc_options = 13;

publiczna końcowa wartość logiczna isInitialized ()

public ConfigProto.Builder mergeClusterDef (wartość ClusterDef )

 Optional list of all workers to use in this session.

.tensorflow.ClusterDef cluster_def = 14;

public ConfigProto.Builder mergeExperimental (wartość ConfigProto.Experimental )

.tensorflow.ConfigProto.Experimental experimental = 16;

public ConfigProto.Builder mergeFrom (com.google.protobuf.Message other)

public ConfigProto.Builder mergeFrom (wejście com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Rzuca

Wyjątek IO

public ConfigProto.Builder mergeGpuOptions (wartość GPUOptions )

 Options that apply to all GPUs.

.tensorflow.GPUOptions gpu_options = 6;

public ConfigProto.Builder mergeGraphOptions (wartość GraphOptions )

 Options that apply to all graphs.

.tensorflow.GraphOptions graph_options = 10;

public ConfigProto.Builder mergeRpcOptions (wartość RPCOptions )

 Options that apply when this session uses the distributed runtime.

.tensorflow.RPCOptions rpc_options = 13;

publiczna wersja końcowa ConfigProto.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)

public ConfigProto.Builder putAllDeviceCount (wartości 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;

public ConfigProto.Builder putDeviceCount (klucz ciągu, wartość 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;

public ConfigProto.Builder usuńDeviceCount (klucz ciąg)

 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 ConfigProto.Builder usuńSessionInterOpThreadPool (indeks 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 ConfigProto.Builder setAllowSoftPlacement (wartość logiczna)

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

bool allow_soft_placement = 7;

public ConfigProto.Builder setClusterDef ( ClusterDef.Builder builderForValue)

 Optional list of all workers to use in this session.

.tensorflow.ClusterDef cluster_def = 14;

public ConfigProto.Builder setClusterDef (wartość ClusterDef )

 Optional list of all workers to use in this session.

.tensorflow.ClusterDef cluster_def = 14;

public ConfigProto.Builder setDeviceFilters (indeks int, wartość ciągu)

 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 setExperimental (wartość ConfigProto.Experimental )

.tensorflow.ConfigProto.Experimental experimental = 16;

public ConfigProto.Builder setExperimental ( ConfigProto.Experimental.Builder builderForValue)

.tensorflow.ConfigProto.Experimental experimental = 16;

public ConfigProto.Builder setField (pole com.google.protobuf.Descriptors.FieldDescriptor, wartość obiektu)

public ConfigProto.Builder setGpuOptions ( GPUOptions.Builder builderForValue)

 Options that apply to all GPUs.

.tensorflow.GPUOptions gpu_options = 6;

public ConfigProto.Builder setGpuOptions (wartość GPUOptions )

 Options that apply to all GPUs.

.tensorflow.GPUOptions gpu_options = 6;

public ConfigProto.Builder setGraphOptions ( GraphOptions.Builder builderForValue)

 Options that apply to all graphs.

.tensorflow.GraphOptions graph_options = 10;

public ConfigProto.Builder setGraphOptions (wartość GraphOptions )

 Options that apply to all graphs.

.tensorflow.GraphOptions graph_options = 10;

public ConfigProto.Builder setInterOpParallelismThreads (wartość 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;

public ConfigProto.Builder setIntraOpParallelismThreads (wartość 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;

public ConfigProto.Builder setIsolateSessionState (wartość logiczna)

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

bool isolate_session_state = 15;

public ConfigProto.Builder setLogDevicePlacement (wartość logiczna)

 Whether device placements should be logged.

bool log_device_placement = 8;

public ConfigProto.Builder setOperationTimeoutInMs (długa wartość)

 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;

public ConfigProto.Builder setPlacementPeriod (wartość 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;

public ConfigProto.Builder setRepeatedField (pole com.google.protobuf.Descriptors.FieldDescriptor, indeks int, wartość obiektu)

public ConfigProto.Builder setRpcOptions (wartość RPCOptions )

 Options that apply when this session uses the distributed runtime.

.tensorflow.RPCOptions rpc_options = 13;

public ConfigProto.Builder setRpcOptions ( RPCOptions.Builder builderForValue)

 Options that apply when this session uses the distributed runtime.

.tensorflow.RPCOptions rpc_options = 13;

public ConfigProto.Builder setSessionInterOpThreadPool (indeks int, wartość 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 setSessionInterOpThreadPool (indeks 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;

public ConfigProto.Builder setShareClusterDevicesInSession (wartość logiczna)

 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;

publiczny końcowy ConfigProto.Builder setUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)

public ConfigProto.Builder setUsePerSessionThreads (wartość logiczna)

 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;