GPUOptions.Experimental

publiczna statyczna klasa końcowa GPUOptions.Experimental

Protobuf typu tensorflow.GPUOptions.Experimental

Klasy zagnieżdżone

klasa Opcje GPU. Eksperymentalne. Konstruktor Protobuf typu tensorflow.GPUOptions.Experimental
klasa Opcje GPU. Eksperymentalne. Urządzenia wirtualne 
 Configuration for breaking down a visible GPU into multiple "virtual"
 devices. 
interfejs GPUOptions.Experimental.VirtualDevicesOrBuilder

Stałe

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

Metody publiczne

wartość logiczna
równa się (obiekt obiektu)
Smyczkowy
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.
statyczne opcje GPU. Eksperymentalne
pobierz instancję domyślną ()
Opcje GPU. Eksperymentalne
getDefaultInstanceForType ()
końcowy statyczny com.google.protobuf.Descriptors.Descriptor
pobierzDescriptor ()
wew
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.
wew
getKernelTrackerMaxInterval () 
 Parameters for GPUKernelTracker.
wew
getKernelTrackerMaxPending () 
 If kernel_tracker_max_pending > 0 then no more than this many
 tracking events can be outstanding at a time.
wew
getNumDevToDevCopyStreams () 
 If > 1, the number of device-to-device copy streams to create
 for each GPUDevice.
getParserForType ()
wew
getSerializedSize ()
wartość logiczna
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.
końcowy com.google.protobuf.UnknownFieldSet
getUnknownFields ()
wartość logiczna
getUseUnifiedMemory () 
 If true, uses CUDA unified memory for memory allocations.
Opcje GPU. Eksperymentalne. Urządzenia wirtualne
getVirtualDevices (indeks int) 
 The multi virtual device settings.
wew
getVirtualDevicesCount () 
 The multi virtual device settings.
Lista< Opcje GPU.Eksperymentalne.Urządzenia wirtualne >
pobierz listę urządzeń wirtualnych () 
 The multi virtual device settings.
GPUOptions.Experimental.VirtualDevicesOrBuilder
getVirtualDevicesOrBuilder (indeks int) 
 The multi virtual device settings.
Lista<? rozszerza GPUOptions.Experimental.VirtualDevicesOrBuilder >
getVirtualDevicesOrBuilderList () 
 The multi virtual device settings.
wew
hashCode ()
końcowa wartość logiczna
jest zainicjowany ()
statyczne opcje GPU.Experimental.Builder
newBuilder ( GPUOptions.Prototyp eksperymentalny)
statyczne opcje GPU.Experimental.Builder
nowyBuilder ()
Opcje GPU. Eksperymentalne. Konstruktor
nowyBuilderForType ()
statyczne opcje GPU. Eksperymentalne
parseDelimitedFrom (wejście strumienia wejściowego)
statyczne opcje GPU. Eksperymentalne
parseDelimitedFrom (dane wejścioweInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
statyczne opcje GPU. Eksperymentalne
parseFrom (dane ByteBuffer)
statyczne opcje GPU. Eksperymentalne
parseFrom (wejście com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
statyczne opcje GPU. Eksperymentalne
parseFrom (dane ByteBuffer, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
statyczne opcje GPU. Eksperymentalne
parseFrom (wejście com.google.protobuf.CodedInputStream)
statyczne opcje GPU. Eksperymentalne
parseFrom (bajt [] dane, com.google.protobuf.ExtensionRegistryLite rozszerzenieRegistry)
statyczne opcje GPU. Eksperymentalne
parseFrom (dane com.google.protobuf.ByteString)
statyczne opcje GPU. Eksperymentalne
parseFrom (dane wejścioweInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
statyczne opcje GPU. Eksperymentalne
parseFrom (dane com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
statyczny
parser ()
Opcje GPU. Eksperymentalne. Konstruktor
do konstruktora ()
próżnia
writeTo (wyjście com.google.protobuf.CodedOutputStream)

Metody dziedziczone

Stałe

publiczny statyczny końcowy int COLLECTIVE_RING_ORDER_FIELD_NUMBER

Wartość stała: 4

publiczny statyczny końcowy int KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER

Wartość stała: 8

publiczny statyczny końcowy int KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER

Wartość stała: 7

publiczny statyczny końcowy w KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER

Wartość stała: 9

publiczny statyczny końcowy int NUM_DEV_TO_DEV_COPY_STREAMS_FIELD_NUMBER

Wartość stała: 3

publiczny statyczny końcowy int TIMESTAMPED_ALLOCATOR_FIELD_NUMBER

Wartość stała: 5

publiczny statyczny końcowy int USE_UNIFIED_MEMORY_FIELD_NUMBER

Wartość stała: 2

publiczny statyczny końcowy int VIRTUAL_DEVICES_FIELD_NUMBER

Wartość stała: 1

Metody publiczne

publiczna wartość logiczna równa się (obiekt obiektu)

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;

public 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;

publiczne statyczne GPUOptions.Experimental getDefaultInstance ()

publiczne GPUOptions.Eksperymentalne 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;

publiczny getParserForType ()

publiczny int getSerializedSize ()

publiczna wartość logiczna 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;

publiczny finał com.google.protobuf.UnknownFieldSet getUnknownFields ()

publiczna wartość logiczna 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 (indeks 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;

public List< 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 (indeks 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;

lista publiczna<? rozszerza 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;

publiczny int hashCode ()

publiczna końcowa wartość logiczna isInitialized ()

public static GPUOptions.Experimental.Builder newBuilder ( GPUOptions.Experimental prototyp)

public static GPUOptions.Experimental.Builder newBuilder ()

public GPUOptions.Experimental.Builder newBuilderForType ()

public static GPUOptions.Experimental parseDelimitedFrom (wejście wejściowe strumienia wejściowego)

Rzuca
Wyjątek IO

public static GPUOptions.Experimental parseDelimitedFrom (dane wejściowe wejściowe strumienia wejściowego, com.google.protobuf.ExtensionRegistryLite rozszerzenieRegistry)

Rzuca
Wyjątek IO

public static GPUOptions.Experimental parseFrom (dane ByteBuffer)

Rzuca
Nieprawidłowy wyjątekProtocolBufferException

publiczne statyczne GPUOptions.Experimental parseFrom (wejście com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Rzuca
Wyjątek IO

public static GPUOptions.Experimental parseFrom (dane ByteBuffer, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Rzuca
Nieprawidłowy wyjątekProtocolBufferException

public static GPUOptions.Experimental parseFrom (wejście com.google.protobuf.CodedInputStream)

Rzuca
Wyjątek IO

public static GPUOptions.Experimental parseFrom (bajt[] dane, com.google.protobuf.ExtensionRegistryLite rozszerzenieRegistry)

Rzuca
Nieprawidłowy wyjątekProtocolBufferException

public static GPUOptions.Experimental parseFrom (dane com.google.protobuf.ByteString)

Rzuca
Nieprawidłowy wyjątekProtocolBufferException

public static GPUOptions.Experimental parseFrom (dane wejścioweInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Rzuca
Wyjątek IO

public static GPUOptions.Experimental parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Rzuca
Nieprawidłowy wyjątekProtocolBufferException

publiczna statyka parser ()

public GPUOptions.Experimental.Builder toBuilder ()

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

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Wyjątek IO