GPUOptions.Experimental

classe finale statica pubblica GPUOptions.Experimental

Tipo di protocollo tensorflow.GPUOptions.Experimental

Classi nidificate

classe	GPUOptions.Experimental.Builder		Tipo di protocollo tensorflow.GPUOptions.Experimental
classe	GPUOptions.Experimental.VirtualDevices		Configuration for breaking down a visible GPU into multiple "virtual" devices.
interfaccia	GPUOptions.Experimental.VirtualDevicesOrBuilder

Costanti

int	COLLECTIVE_RING_ORDER_FIELD_NUMBER
int	KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER
int	KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER
int	KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER
int	NUM_DEV_TO_DEV_COPY_STREAMS_FIELD_NUMBER
int	TIMESTAMPED_ALLOCATOR_FIELD_NUMBER
int	USE_UNIFIED_MEMORY_FIELD_NUMBER
int	VIRTUAL_DEVICES_FIELD_NUMBER

Metodi pubblici

booleano	è uguale a (Oggetto oggetto)
Corda	getCollectiveRingOrder () If non-empty, defines a good GPU ring order on a single worker based on device interconnect.
com.google.protobuf.ByteString	getCollectiveRingOrderBytes () If non-empty, defines a good GPU ring order on a single worker based on device interconnect.
GPUOptions.Experimental statico	getDefaultInstance ()
GPUOptions.Experimental	getDefaultInstanceForType ()
com.google.protobuf.Descriptors.Descriptor statico finale	getDescrittore ()
int	getKernelTrackerMaxBytes () If kernel_tracker_max_bytes = n > 0, then a tracking event is inserted after every series of kernels allocating a sum of memory >= n.
int	getKernelTrackerMaxInterval () Parameters for GPUKernelTracker.
int	getKernelTrackerMaxPending () If kernel_tracker_max_pending > 0 then no more than this many tracking events can be outstanding at a time.
int	getNumDevToDevCopyStreams () If > 1, the number of device-to-device copy streams to create for each GPUDevice.
	getParserForType ()
int	getSerializedSize ()
booleano	getTimestampedAllocator () If true then extra work is done by GPUDevice and GPUBFCAllocator to keep track of when GPU memory is freed and when kernels actually complete so that we can know when a nominally free memory chunk is really not subject to pending use.
finale com.google.protobuf.UnknownFieldSet	getUnknownFields ()
booleano	getUseUnifiedMemory () If true, uses CUDA unified memory for memory allocations.
GPUOptions.Experimental.VirtualDevices	getVirtualDevices (indice int) The multi virtual device settings.
int	getVirtualDevicesCount () The multi virtual device settings.
Elenco< GPUOptions.Experimental.VirtualDevices >	getVirtualDevicesList () The multi virtual device settings.
GPUOptions.Experimental.VirtualDevicesOrBuilder	getVirtualDevicesOrBuilder (indice int) The multi virtual device settings.
Elenco<? estende GPUOptions.Experimental.VirtualDevicesOrBuilder >	getVirtualDevicesOrBuilderList () The multi virtual device settings.
int	codicehash ()
booleano finale	èinizializzato ()
GPUOptions.Experimental.Builder statico	newBuilder ( GPUOptions.Prototipo sperimentale)
GPUOptions.Experimental.Builder statico	nuovocostruttore ()
GPUOptions.Experimental.Builder	newBuilderForType ()
GPUOptions.Experimental statico	parseDelimitedFrom (input InputStream)
GPUOptions.Experimental statico	parseDelimitedFrom (input InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
GPUOptions.Experimental statico	parseFrom (dati ByteBuffer)
GPUOptions.Experimental statico	parseFrom (input com.google.protobuf.CodedInputStream, estensione com.google.protobuf.ExtensionRegistryLiteRegistry)
GPUOptions.Experimental statico	parseFrom (dati ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
GPUOptions.Experimental statico	parseFrom (ingresso com.google.protobuf.CodedInputStream)
GPUOptions.Experimental statico	parseFrom (byte[] dati, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
GPUOptions.Experimental statico	parseFrom (dati com.google.protobuf.ByteString)
GPUOptions.Experimental statico	parseFrom (input InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
GPUOptions.Experimental statico	parseFrom (dati com.google.protobuf.ByteString, estensione Com.google.protobuf.ExtensionRegistryLiteRegistry)
statico	analizzatore ()
GPUOptions.Experimental.Builder	toBuilder ()
vuoto	writeTo (output com.google.protobuf.CodedOutputStream)

Metodi ereditati

Dalla classe java.lang.Object

booleano	è uguale a (Oggetto arg0)
Classe finale<?>	getClass ()
int	codicehash ()
vuoto finale	avvisare ()
vuoto finale	notificaTutti ()
Corda	aStringa ()
vuoto finale	attendere (lungo arg0, int arg1)
vuoto finale	aspetta (lungo arg0)
vuoto finale	Aspettare ()

Dall'interfaccia org.tensorflow.proto.framework.GPUOptions.ExperimentalOrBuilder

stringa astratta	getCollectiveRingOrder () If non-empty, defines a good GPU ring order on a single worker based on device interconnect.
astratto com.google.protobuf.ByteString	getCollectiveRingOrderBytes () If non-empty, defines a good GPU ring order on a single worker based on device interconnect.
astratto int	getKernelTrackerMaxBytes () If kernel_tracker_max_bytes = n > 0, then a tracking event is inserted after every series of kernels allocating a sum of memory >= n.
astratto int	getKernelTrackerMaxInterval () Parameters for GPUKernelTracker.
astratto int	getKernelTrackerMaxPending () If kernel_tracker_max_pending > 0 then no more than this many tracking events can be outstanding at a time.
astratto int	getNumDevToDevCopyStreams () If > 1, the number of device-to-device copy streams to create for each GPUDevice.
booleano astratto	getTimestampedAllocator () If true then extra work is done by GPUDevice and GPUBFCAllocator to keep track of when GPU memory is freed and when kernels actually complete so that we can know when a nominally free memory chunk is really not subject to pending use.
booleano astratto	getUseUnifiedMemory () If true, uses CUDA unified memory for memory allocations.
astratto GPUOptions.Experimental.VirtualDevices	getVirtualDevices (indice int) The multi virtual device settings.
astratto int	getVirtualDevicesCount () The multi virtual device settings.
Elenco astratto< GPUOptions.Experimental.VirtualDevices >	getVirtualDevicesList () The multi virtual device settings.
astratto GPUOptions.Experimental.VirtualDevicesOrBuilder	getVirtualDevicesOrBuilder (indice int) The multi virtual device settings.
Elenco astratto<? estende GPUOptions.Experimental.VirtualDevicesOrBuilder >	getVirtualDevicesOrBuilderList () The multi virtual device settings.

Costanti

public static final int COLLECTIVE_RING_ORDER_FIELD_NUMBER

Valore costante: 4

pubblico statico finale int KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER

Valore costante: 8

pubblico statico finale int KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER

Valore costante: 7

pubblico statico finale int KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER

Valore costante: 9

public static final int NUM_DEV_TO_DEV_COPY_STREAMS_FIELD_NUMBER

Valore costante: 3

public static final int TIMESTAMPED_ALLOCATOR_FIELD_NUMBER

Valore costante: 5

public static final int USE_UNIFIED_MEMORY_FIELD_NUMBER

Valore costante: 2

public static final int VIRTUAL_DEVICES_FIELD_NUMBER

Valore costante: 1

Metodi pubblici

booleano pubblico è uguale a (Oggetto obj)

public String getCollectiveRingOrder ()

 If non-empty, defines a good GPU ring order on a single worker based on
 device interconnect.  This assumes that all workers have the same GPU
 topology.  Specify as a comma-separated string, e.g. "3,2,1,0,7,6,5,4".
 This ring order is used by the RingReducer implementation of
 CollectiveReduce, and serves as an override to automatic ring order
 generation in OrderTaskDeviceMap() during CollectiveParam resolution.
 

string collective_ring_order = 4;

pubblico com.google.protobuf.ByteString getCollectiveRingOrderBytes ()

 If non-empty, defines a good GPU ring order on a single worker based on
 device interconnect.  This assumes that all workers have the same GPU
 topology.  Specify as a comma-separated string, e.g. "3,2,1,0,7,6,5,4".
 This ring order is used by the RingReducer implementation of
 CollectiveReduce, and serves as an override to automatic ring order
 generation in OrderTaskDeviceMap() during CollectiveParam resolution.
 

string collective_ring_order = 4;

GPUOptions.Experimental statico pubblico getDefaultInstance ()

public GPUOptions.Experimental getDefaultInstanceForType ()

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

public int getKernelTrackerMaxBytes ()

 If kernel_tracker_max_bytes = n > 0, then a tracking event is
 inserted after every series of kernels allocating a sum of
 memory >= n.  If one kernel allocates b * n bytes, then one
 event will be inserted after it, but it will count as b against
 the pending limit.
 

int32 kernel_tracker_max_bytes = 8;

public int getKernelTrackerMaxInterval ()

 Parameters for GPUKernelTracker.  By default no kernel tracking is done.
 Note that timestamped_allocator is only effective if some tracking is
 specified.
 If kernel_tracker_max_interval = n > 0, then a tracking event
 is inserted after every n kernels without an event.
 

int32 kernel_tracker_max_interval = 7;

public int getKernelTrackerMaxPending ()

 If kernel_tracker_max_pending > 0 then no more than this many
 tracking events can be outstanding at a time.  An attempt to
 launch an additional kernel will stall until an event
 completes.
 

int32 kernel_tracker_max_pending = 9;

public int getNumDevToDevCopyStreams ()

 If > 1, the number of device-to-device copy streams to create
 for each GPUDevice.  Default value is 0, which is automatically
 converted to 1.
 

int32 num_dev_to_dev_copy_streams = 3;

pubblico getParserForType ()

public int getSerializedSize ()

pubblico booleano getTimestampedAllocator ()

 If true then extra work is done by GPUDevice and GPUBFCAllocator to
 keep track of when GPU memory is freed and when kernels actually
 complete so that we can know when a nominally free memory chunk
 is really not subject to pending use.
 

bool timestamped_allocator = 5;

pubblico finale com.google.protobuf.UnknownFieldSet getUnknownFields ()

pubblico booleano getUseUnifiedMemory ()

 If true, uses CUDA unified memory for memory allocations. If
 per_process_gpu_memory_fraction option is greater than 1.0, then unified
 memory is used regardless of the value for this field. See comments for
 per_process_gpu_memory_fraction field for more details and requirements
 of the unified memory. This option is useful to oversubscribe memory if
 multiple processes are sharing a single GPU while individually using less
 than 1.0 per process memory fraction.
 

bool use_unified_memory = 2;

public GPUOptions.Experimental.VirtualDevices getVirtualDevices (indice int)

 The multi virtual device settings. If empty (not set), it will create
 single virtual device on each visible GPU, according to the settings
 in "visible_device_list" above. Otherwise, the number of elements in the
 list must be the same as the number of visible GPUs (after
 "visible_device_list" filtering if it is set), and the string represented
 device names (e.g. /device:GPU:<id>) will refer to the virtual
 devices and have the <id> field assigned sequentially starting from 0,
 according to the order they appear in this list and the "memory_limit"
 list inside each element. For example,
   visible_device_list = "1,0"
   virtual_devices { memory_limit: 1GB memory_limit: 2GB }
   virtual_devices {}
 will create three virtual devices as:
   /device:GPU:0 -> visible GPU 1 with 1GB memory
   /device:GPU:1 -> visible GPU 1 with 2GB memory
   /device:GPU:2 -> visible GPU 0 with all available memory
 NOTE:
 1. It's invalid to set both this and "per_process_gpu_memory_fraction"
    at the same time.
 2. Currently this setting is per-process, not per-session. Using
    different settings in different sessions within same process will
    result in undefined behavior.
 

repeated .tensorflow.GPUOptions.Experimental.VirtualDevices virtual_devices = 1;

public int getVirtualDevicesCount ()

 The multi virtual device settings. If empty (not set), it will create
 single virtual device on each visible GPU, according to the settings
 in "visible_device_list" above. Otherwise, the number of elements in the
 list must be the same as the number of visible GPUs (after
 "visible_device_list" filtering if it is set), and the string represented
 device names (e.g. /device:GPU:<id>) will refer to the virtual
 devices and have the <id> field assigned sequentially starting from 0,
 according to the order they appear in this list and the "memory_limit"
 list inside each element. For example,
   visible_device_list = "1,0"
   virtual_devices { memory_limit: 1GB memory_limit: 2GB }
   virtual_devices {}
 will create three virtual devices as:
   /device:GPU:0 -> visible GPU 1 with 1GB memory
   /device:GPU:1 -> visible GPU 1 with 2GB memory
   /device:GPU:2 -> visible GPU 0 with all available memory
 NOTE:
 1. It's invalid to set both this and "per_process_gpu_memory_fraction"
    at the same time.
 2. Currently this setting is per-process, not per-session. Using
    different settings in different sessions within same process will
    result in undefined behavior.
 

repeated .tensorflow.GPUOptions.Experimental.VirtualDevices virtual_devices = 1;

Elenco pubblico< GPUOptions.Experimental.VirtualDevices > getVirtualDevicesList ()

 The multi virtual device settings. If empty (not set), it will create
 single virtual device on each visible GPU, according to the settings
 in "visible_device_list" above. Otherwise, the number of elements in the
 list must be the same as the number of visible GPUs (after
 "visible_device_list" filtering if it is set), and the string represented
 device names (e.g. /device:GPU:<id>) will refer to the virtual
 devices and have the <id> field assigned sequentially starting from 0,
 according to the order they appear in this list and the "memory_limit"
 list inside each element. For example,
   visible_device_list = "1,0"
   virtual_devices { memory_limit: 1GB memory_limit: 2GB }
   virtual_devices {}
 will create three virtual devices as:
   /device:GPU:0 -> visible GPU 1 with 1GB memory
   /device:GPU:1 -> visible GPU 1 with 2GB memory
   /device:GPU:2 -> visible GPU 0 with all available memory
 NOTE:
 1. It's invalid to set both this and "per_process_gpu_memory_fraction"
    at the same time.
 2. Currently this setting is per-process, not per-session. Using
    different settings in different sessions within same process will
    result in undefined behavior.
 

repeated .tensorflow.GPUOptions.Experimental.VirtualDevices virtual_devices = 1;

public GPUOptions.Experimental.VirtualDevicesOrBuilder getVirtualDevicesOrBuilder (indice int)

 The multi virtual device settings. If empty (not set), it will create
 single virtual device on each visible GPU, according to the settings
 in "visible_device_list" above. Otherwise, the number of elements in the
 list must be the same as the number of visible GPUs (after
 "visible_device_list" filtering if it is set), and the string represented
 device names (e.g. /device:GPU:<id>) will refer to the virtual
 devices and have the <id> field assigned sequentially starting from 0,
 according to the order they appear in this list and the "memory_limit"
 list inside each element. For example,
   visible_device_list = "1,0"
   virtual_devices { memory_limit: 1GB memory_limit: 2GB }
   virtual_devices {}
 will create three virtual devices as:
   /device:GPU:0 -> visible GPU 1 with 1GB memory
   /device:GPU:1 -> visible GPU 1 with 2GB memory
   /device:GPU:2 -> visible GPU 0 with all available memory
 NOTE:
 1. It's invalid to set both this and "per_process_gpu_memory_fraction"
    at the same time.
 2. Currently this setting is per-process, not per-session. Using
    different settings in different sessions within same process will
    result in undefined behavior.
 

repeated .tensorflow.GPUOptions.Experimental.VirtualDevices virtual_devices = 1;

Elenco pubblico<? estende GPUOptions.Experimental.VirtualDevicesOrBuilder > getVirtualDevicesOrBuilderList ()

 The multi virtual device settings. If empty (not set), it will create
 single virtual device on each visible GPU, according to the settings
 in "visible_device_list" above. Otherwise, the number of elements in the
 list must be the same as the number of visible GPUs (after
 "visible_device_list" filtering if it is set), and the string represented
 device names (e.g. /device:GPU:<id>) will refer to the virtual
 devices and have the <id> field assigned sequentially starting from 0,
 according to the order they appear in this list and the "memory_limit"
 list inside each element. For example,
   visible_device_list = "1,0"
   virtual_devices { memory_limit: 1GB memory_limit: 2GB }
   virtual_devices {}
 will create three virtual devices as:
   /device:GPU:0 -> visible GPU 1 with 1GB memory
   /device:GPU:1 -> visible GPU 1 with 2GB memory
   /device:GPU:2 -> visible GPU 0 with all available memory
 NOTE:
 1. It's invalid to set both this and "per_process_gpu_memory_fraction"
    at the same time.
 2. Currently this setting is per-process, not per-session. Using
    different settings in different sessions within same process will
    result in undefined behavior.
 

repeated .tensorflow.GPUOptions.Experimental.VirtualDevices virtual_devices = 1;

public int hashCode ()

public final booleano isInitialized ()

pubblico statico GPUOptions.Experimental.Builder newBuilder (prototipo GPUOptions.Experimental )

pubblico statico GPUOptions.Experimental.Builder newBuilder ()

pubblico GPUOptions.Experimental.Builder newBuilderForType ()

GPUOptions statico pubblico.Experimental parseDelimitedFrom (input InputStream)

Lancia

IOException

GPUOptions.Experimental statico pubblico parseDelimitedFrom (input InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lancia

IOException

GPUOptions statiche pubbliche. ParseFrom sperimentale (dati ByteBuffer)

Lancia

InvalidProtocolBufferException

GPUOptions statico pubblico. ParseFrom sperimentale (input com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lancia

IOException

GPUOptions statiche pubbliche. ParseFrom sperimentale (dati ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lancia

InvalidProtocolBufferException

GPUOptions.Experimental statico pubblico parseFrom (input com.google.protobuf.CodedInputStream)

Lancia

IOException

GPUOptions statico pubblico. ParseFrom sperimentale (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lancia

InvalidProtocolBufferException

GPUOptions statico pubblico. ParseFrom sperimentale (dati com.google.protobuf.ByteString)

Lancia

InvalidProtocolBufferException

GPUOptions statico pubblico. ParseFrom sperimentale (input InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lancia

IOException

GPUOptions statiche pubbliche. ParseFrom sperimentale (dati com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lancia

InvalidProtocolBufferException

pubblico statico analizzatore ()

pubblico GPUOptions.Experimental.Builder toBuilder ()

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

Lancia

IOException