GPUOptions.Experimental

GPUOptions kelas akhir statis publik.Eksperimental

Tipe protobuf tensorflow.GPUOptions.Experimental

Kelas Bersarang

kelas GPUOptions.Eksperimental.Builder Tipe protobuf tensorflow.GPUOptions.Experimental
kelas Opsi GPU.Eksperimental.Perangkat Virtual
 Configuration for breaking down a visible GPU into multiple "virtual"
 devices. 
antarmuka GPUOptions.Experimental.VirtualDevicesOrBuilder

Konstanta

ke dalam COLLECTIVE_RING_ORDER_FIELD_NUMBER
ke dalam KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER
ke dalam KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER
ke dalam KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER
ke dalam NUM_DEV_TO_DEV_COPY_STRREAMS_FIELD_NUMBER
ke dalam TIMESTAMPED_ALLOCATOR_FIELD_NUMBER
ke dalam USE_UNIFIED_MEMORY_FIELD_NUMBER
ke dalam VIRTUAL_DEVICES_FIELD_NUMBER

Metode Publik

boolean
sama dengan (Objek objek)
Rangkaian
dapatkanCollectiveRingOrder ()
 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.
Opsi GPU statis. Eksperimental
dapatkanDefaultInstance ()
Opsi GPU.Eksperimental
dapatkanDefaultInstanceForType ()
com.google.protobuf.Descriptors.Descriptor statis terakhir
dapatkanDescriptor ()
ke dalam
dapatkanKernelTrackerMaxBytes ()
 If kernel_tracker_max_bytes = n > 0, then a tracking event is
 inserted after every series of kernels allocating a sum of
 memory >= n.
ke dalam
dapatkanKernelTrackerMaxInterval ()
 Parameters for GPUKernelTracker.
ke dalam
getKernelTrackerMaxPending ()
 If kernel_tracker_max_pending > 0 then no more than this many
 tracking events can be outstanding at a time.
ke dalam
getNumDevToDevCopyStream ()
 If > 1, the number of device-to-device copy streams to create
 for each GPUDevice.
dapatkanParserForType ()
ke dalam
dapatkanUkuranSerial ()
boolean
dapatkan Pengalokasi Waktu ()
 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.
final com.google.protobuf.UnknownFieldSet
dapatkan Bidang Tidak Dikenal ()
boolean
dapatkanUseUnifiedMemory ()
 If true, uses CUDA unified memory for memory allocations.
Opsi GPU.Eksperimental.Perangkat Virtual
getVirtualDevices (indeks int)
 The multi virtual device settings.
ke dalam
dapatkanVirtualDevicesCount ()
 The multi virtual device settings.
Daftar< GPUOptions.Experimental.VirtualDevices >
dapatkanDaftar PerangkatVirtual ()
 The multi virtual device settings.
GPUOptions.Experimental.VirtualDevicesOrBuilder
getVirtualDevicesOrBuilder (indeks int)
 The multi virtual device settings.
Daftar<? memperluas GPUOptions.Experimental.VirtualDevicesOrBuilder >
dapatkanVirtualDevicesOrBuilderList ()
 The multi virtual device settings.
ke dalam
Kode hash ()
boolean terakhir
diinisialisasi ()
GPUOptions.Eksperimental.Builder statis
newBuilder ( GPUOptions.Prototipe eksperimental )
GPUOptions.Eksperimental.Builder statis
Pembangun baru ()
GPUOptions.Eksperimental.Builder
newBuilderForType ()
Opsi GPU statis. Eksperimental
parseDelimitedFrom (masukan Aliran Masukan)
Opsi GPU statis. Eksperimental
parseDelimitedFrom (masukan InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Opsi GPU statis. Eksperimental
parseFrom (data ByteBuffer)
Opsi GPU statis. Eksperimental
parseFrom (com.google.protobuf.CodedInputStream masukan, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Opsi GPU statis. Eksperimental
parseFrom (data ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Opsi GPU statis. Eksperimental
parseFrom (com.google.protobuf.CodedInputStream masukan)
Opsi GPU statis. Eksperimental
parseFrom (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Opsi GPU statis. Eksperimental
parseFrom (com.google.protobuf.ByteString data)
Opsi GPU statis. Eksperimental
parseFrom (masukan InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Opsi GPU statis. Eksperimental
parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
statis
pengurai ()
GPUOptions.Eksperimental.Builder
untukPembangun ()
ruang kosong
writeTo (com.google.protobuf.CodedOutputStream keluaran)

Metode Warisan

Konstanta

int final statis publik COLLECTIVE_RING_ORDER_FIELD_NUMBER

Nilai Konstan: 4

int final statis publik KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER

Nilai Konstan: 8

int final statis publik KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER

Nilai Konstan: 7

int final statis publik KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER

Nilai Konstan: 9

int final statis publik NUM_DEV_TO_DEV_COPY_STRREAMS_FIELD_NUMBER

Nilai Konstan: 3

int final statis publik TIMESTAMPED_ALLOCATOR_FIELD_NUMBER

Nilai Konstan: 5

int akhir statis publik USE_UNIFIED_MEMORY_FIELD_NUMBER

Nilai Konstan: 2

int final statis publik VIRTUAL_DEVICES_FIELD_NUMBER

Nilai Konstan: 1

Metode Publik

boolean publik sama (Obj objek)

String publik 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;

com.google.protobuf.ByteString publik 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 statis publik. GetDefaultInstance eksperimental ()

GPUOptions publik. GetDefaultInstanceForType eksperimental ()

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

int publik 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;

int publik 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;

int publik 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;

int publik 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;

publik dapatkanParserForType ()

publik int getSerializedSize ()

boolean publik 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;

public final com.google.protobuf.UnknownFieldSet getUnknownFields ()

boolean publik 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;

GPUOptions.Experimental.VirtualDevices publik getVirtualDevices (int indeks) 

 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;

publik 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;

Daftar publik< 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;

GPUOptions.Experimental.VirtualDevicesOrBuilder publik getVirtualDevicesOrBuilder (int indeks) 

 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;

Daftar Publik<? memperluas 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;

kode hash int publik ()

boolean akhir publik diinisialisasi ()

GPUOptions.Experimental.Builder newBuilder statis publik ( GPUOptions.Prototipe eksperimental)

GPUOptions.Experimental.Builder statis publik newBuilder ()

GPUOptions.Experimental.Builder publik newBuilderForType ()

GPUOptions statis publik. ParseDelimitedFrom eksperimental (input InputStream)

Melempar
Pengecualian IO

GPUOptions statis publik. ParseDelimitedFrom eksperimental (input InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
Pengecualian IO

GPUOptions statis publik. ParseFrom eksperimental (data ByteBuffer)

Melempar
InvalidProtocolBufferException

GPUOptions statis publik. ParseFrom eksperimental (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
Pengecualian IO

GPUOptions statis publik. ParseFrom eksperimental (data ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
InvalidProtocolBufferException

GPUOptions statis publik. ParseFrom eksperimental (com.google.protobuf.CodedInputStream input)

Melempar
Pengecualian IO

GPUOptions statis publik. ParseFrom eksperimental (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
InvalidProtocolBufferException

GPUOptions statis publik. ParseFrom eksperimental (com.google.protobuf.ByteString data)

Melempar
InvalidProtocolBufferException

GPUOptions statis publik. ParseFrom eksperimental (input InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
Pengecualian IO

GPUOptions statis publik. ParseFrom eksperimental (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Melempar
InvalidProtocolBufferException

statis publik pengurai ()

GPUOptions.Experimental.Builder toBuilder () publik

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

Melempar
Pengecualian IO