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
GPUOptions.Experimental
com.google.protobuf.Descriptors.Descriptor statico finale
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.
int
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
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
booleano finale
GPUOptions.Experimental.Builder statico
GPUOptions.Experimental.Builder statico
GPUOptions.Experimental.Builder
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
GPUOptions.Experimental.Builder
vuoto
writeTo (output com.google.protobuf.CodedOutputStream)

Metodi ereditati

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