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GPUOptions

Opsi GPU kelas akhir publik

Tipe protobuf tensorflow.GPUOptions

Kelas Bersarang

kelas	Opsi GPU.Pembangun	Tipe protobuf `tensorflow.GPUOptions`
kelas	Opsi GPU.Eksperimental	Tipe protobuf `tensorflow.GPUOptions.Experimental`
antarmuka	GPUOptions.ExperimentalOrBuilder

Konstanta

ke dalam	ALLOCATOR_TYPE_FIELD_NUMBER
ke dalam	ALLOW_GROWTH_FIELD_NUMBER
ke dalam	DEFERRED_DELETION_BYTES_FIELD_NUMBER
ke dalam	EXPERIMENTAL_FIELD_NUMBER
ke dalam	FORCE_GPU_COMPATIBLE_FIELD_NUMBER
ke dalam	PER_PROCESS_GPU_MEMORY_FRACTION_FIELD_NUMBER
ke dalam	POLLING_ACTIVE_DELAY_USECS_FIELD_NUMBER
ke dalam	POLLING_INACTIVE_DELAY_MSECS_FIELD_NUMBER
ke dalam	VISIBLE_DEVICE_LIST_FIELD_NUMBER

Metode Publik

boolean	sama dengan (Objek objek)
Rangkaian	dapatkanAllocatorType () The type of GPU allocation strategy to use.
com.google.protobuf.ByteString	dapatkanAllocatorTypeBytes () The type of GPU allocation strategy to use.
boolean	dapatkan Izinkan Pertumbuhan () If true, the allocator does not pre-allocate the entire specified GPU memory region, instead starting small and growing as needed.
Opsi GPU statis	dapatkanDefaultInstance ()
Opsi GPU	dapatkanDefaultInstanceForType ()
panjang	dapatkanDeferredDeletionBytes () Delay deletion of up to this many bytes to reduce the number of interactions with gpu driver code.
com.google.protobuf.Descriptors.Descriptor statis terakhir	dapatkanDescriptor ()
Opsi GPU.Eksperimental	dapatkan Eksperimental () Everything inside experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat.
GPUOptions.ExperimentalOrBuilder	dapatkanExperimentalOrBuilder () Everything inside experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat.
boolean	getForceGpuKompatibel () Force all tensors to be gpu_compatible.
	dapatkanParserForType ()
dobel	getPerProcessGpuMemoryFraction () Fraction of the available GPU memory to allocate for each process.
ke dalam	dapatkanPollingActiveDelayUsecs () In the event polling loop sleep this many microseconds between PollEvents calls, when the queue is not empty.
ke dalam	getPollingInactiveDelayMsecs () This field is deprecated and ignored.
ke dalam	dapatkanUkuranSerial ()
final com.google.protobuf.UnknownFieldSet	dapatkan Bidang Tidak Dikenal ()
Rangkaian	dapatkanDaftarPerangkatVisible () A comma-separated list of GPU ids that determines the 'visible' to 'virtual' mapping of GPU devices.
com.google.protobuf.ByteString	dapatkanVisibleDeviceListBytes () A comma-separated list of GPU ids that determines the 'visible' to 'virtual' mapping of GPU devices.
boolean	memiliki Eksperimental () Everything inside experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat.
ke dalam	Kode hash ()
boolean terakhir	diinisialisasi ()
GPUOptions.Builder statis	newBuilder (prototipe GPUOptions )
GPUOptions.Builder statis	Pembangun baru ()
Opsi GPU.Pembangun	newBuilderForType ()
Opsi GPU statis	parseDelimitedFrom (masukan Aliran Masukan)
Opsi GPU statis	parseDelimitedFrom (masukan InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Opsi GPU statis	parseFrom (data ByteBuffer)
Opsi GPU statis	parseFrom (com.google.protobuf.CodedInputStream masukan, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Opsi GPU statis	parseFrom (data ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Opsi GPU statis	parseFrom (com.google.protobuf.CodedInputStream masukan)
Opsi GPU statis	parseFrom (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Opsi GPU statis	parseFrom (com.google.protobuf.ByteString data)
Opsi GPU statis	parseFrom (masukan InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
Opsi GPU statis	parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
statis	pengurai ()
Opsi GPU.Pembangun	untukPembangun ()
ruang kosong	writeTo (com.google.protobuf.CodedOutputStream keluaran)

Metode Warisan

Dari kelas java.lang.Object

boolean	sama dengan (Objek arg0)
Kelas terakhir<?>	dapatkan Kelas ()
ke dalam	Kode hash ()
kekosongan terakhir	memberitahu ()
kekosongan terakhir	beri tahuSemua ()
Rangkaian	keString ()
kekosongan terakhir	tunggu (arg0 panjang, int arg1)
kekosongan terakhir	tunggu (argumen panjang0)
kekosongan terakhir	Tunggu ()

Dari antarmuka org.tensorflow.proto.framework.GPUOptionsOrBuilder

Tali abstrak	dapatkanAllocatorType () The type of GPU allocation strategy to use.
abstrak com.google.protobuf.ByteString	dapatkanAllocatorTypeBytes () The type of GPU allocation strategy to use.
boolean abstrak	dapatkan Izinkan Pertumbuhan () If true, the allocator does not pre-allocate the entire specified GPU memory region, instead starting small and growing as needed.
abstrak panjang	dapatkanDeferredDeletionBytes () Delay deletion of up to this many bytes to reduce the number of interactions with gpu driver code.
GPUOptions abstrak.Eksperimental	dapatkan Eksperimental () Everything inside experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat.
abstrak GPUOptions.ExperimentalOrBuilder	dapatkanExperimentalOrBuilder () Everything inside experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat.
boolean abstrak	getForceGpuKompatibel () Force all tensors to be gpu_compatible.
abstrak ganda	getPerProcessGpuMemoryFraction () Fraction of the available GPU memory to allocate for each process.
abstrak ke dalam	dapatkanPollingActiveDelayUsecs () In the event polling loop sleep this many microseconds between PollEvents calls, when the queue is not empty.
abstrak ke dalam	getPollingInactiveDelayMsecs () This field is deprecated and ignored.
Tali abstrak	dapatkanDaftarPerangkatVisible () A comma-separated list of GPU ids that determines the 'visible' to 'virtual' mapping of GPU devices.
abstrak com.google.protobuf.ByteString	dapatkanVisibleDeviceListBytes () A comma-separated list of GPU ids that determines the 'visible' to 'virtual' mapping of GPU devices.
boolean abstrak	memiliki Eksperimental () Everything inside experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat.

Konstanta

int final statis publik ALLOCATOR_TYPE_FIELD_NUMBER

Nilai Konstan: 2

int final statis publik ALLOW_GROWTH_FIELD_NUMBER

Nilai Konstan: 4

int akhir statis publik DEFERRED_DELETION_BYTES_FIELD_NUMBER

Nilai Konstan: 3

int akhir statis publik EXPERIMENTAL_FIELD_NUMBER

Nilai Konstan: 9

int final statis publik FORCE_GPU_COMPATIBLE_FIELD_NUMBER

Nilai Konstan: 8

int akhir statis publik PER_PROCESS_GPU_MEMORY_FRACTION_FIELD_NUMBER

Nilai Konstan: 1

int akhir statis publik POLLING_ACTIVE_DELAY_USECS_FIELD_NUMBER

Nilai Konstan: 6

int akhir statis publik POLLING_INACTIVE_DELAY_MSECS_FIELD_NUMBER

Nilai Konstan: 7

int final statis publik VISIBLE_DEVICE_LIST_FIELD_NUMBER

Nilai Konstan: 5

Metode Publik

boolean publik sama (Obj objek)

String publik getAllocatorType ()

 The type of GPU allocation strategy to use.
 Allowed values:
 "": The empty string (default) uses a system-chosen default
     which may change over time.
 "BFC": A "Best-fit with coalescing" algorithm, simplified from a
        version of dlmalloc.

string allocator_type = 2;

publik com.google.protobuf.ByteString getAllocatorTypeBytes ()

 The type of GPU allocation strategy to use.
 Allowed values:
 "": The empty string (default) uses a system-chosen default
     which may change over time.
 "BFC": A "Best-fit with coalescing" algorithm, simplified from a
        version of dlmalloc.

string allocator_type = 2;

boolean publik getAllowGrowth ()

 If true, the allocator does not pre-allocate the entire specified
 GPU memory region, instead starting small and growing as needed.

bool allow_growth = 4;

GPUOptions statis publik getDefaultInstance ()

GPUOptions publik getDefaultInstanceForType ()

get panjang publikDeferredDeletionBytes ()

 Delay deletion of up to this many bytes to reduce the number of
 interactions with gpu driver code.  If 0, the system chooses
 a reasonable default (several MBs).

int64 deferred_deletion_bytes = 3;

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

Opsi GPU publik. GetEksperimental eksperimental ()

 Everything inside experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.

.tensorflow.GPUOptions.Experimental experimental = 9;

GPUOptions.ExperimentalOrBuilder publik getExperimentalOrBuilder ()

 Everything inside experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.

.tensorflow.GPUOptions.Experimental experimental = 9;

boolean publik getForceGpuCompatible ()

 Force all tensors to be gpu_compatible. On a GPU-enabled TensorFlow,
 enabling this option forces all CPU tensors to be allocated with Cuda
 pinned memory. Normally, TensorFlow will infer which tensors should be
 allocated as the pinned memory. But in case where the inference is
 incomplete, this option can significantly speed up the cross-device memory
 copy performance as long as it fits the memory.
 Note that this option is not something that should be
 enabled by default for unknown or very large models, since all Cuda pinned
 memory is unpageable, having too much pinned memory might negatively impact
 the overall host system performance.

bool force_gpu_compatible = 8;

publik dapatkanParserForType ()

getPerProcessGpuMemoryFraction ganda publik ()

 Fraction of the available GPU memory to allocate for each process.
 1 means to allocate all of the GPU memory, 0.5 means the process
 allocates up to ~50% of the available GPU memory.
 GPU memory is pre-allocated unless the allow_growth option is enabled.
 If greater than 1.0, uses CUDA unified memory to potentially oversubscribe
 the amount of memory available on the GPU device by using host memory as a
 swap space. Accessing memory not available on the device will be
 significantly slower as that would require memory transfer between the host
 and the device. Options to reduce the memory requirement should be
 considered before enabling this option as this may come with a negative
 performance impact. Oversubscription using the unified memory requires
 Pascal class or newer GPUs and it is currently only supported on the Linux
 operating system. See
 https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#um-requirements
 for the detailed requirements.

double per_process_gpu_memory_fraction = 1;

int publik getPollingActiveDelayUsecs ()

 In the event polling loop sleep this many microseconds between
 PollEvents calls, when the queue is not empty.  If value is not
 set or set to 0, gets set to a non-zero default.

int32 polling_active_delay_usecs = 6;

publik int getPollingInactiveDelayMsecs ()

 This field is deprecated and ignored.

int32 polling_inactive_delay_msecs = 7;

publik int getSerializedSize ()

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

String publik getVisibleDeviceList ()

 A comma-separated list of GPU ids that determines the 'visible'
 to 'virtual' mapping of GPU devices.  For example, if TensorFlow
 can see 8 GPU devices in the process, and one wanted to map
 visible GPU devices 5 and 3 as "/device:GPU:0", and "/device:GPU:1",
 then one would specify this field as "5,3".  This field is similar in
 spirit to the CUDA_VISIBLE_DEVICES environment variable, except
 it applies to the visible GPU devices in the process.
 NOTE:
 1. The GPU driver provides the process with the visible GPUs
    in an order which is not guaranteed to have any correlation to
    the *physical* GPU id in the machine.  This field is used for
    remapping "visible" to "virtual", which means this operates only
    after the process starts.  Users are required to use vendor
    specific mechanisms (e.g., CUDA_VISIBLE_DEVICES) to control the
    physical to visible device mapping prior to invoking TensorFlow.
 2. In the code, the ids in this list are also called "platform GPU id"s,
    and the 'virtual' ids of GPU devices (i.e. the ids in the device
    name "/device:GPU:<id>") are also called "TF GPU id"s. Please
    refer to third_party/tensorflow/core/common_runtime/gpu/gpu_id.h
    for more information.

string visible_device_list = 5;

publik com.google.protobuf.ByteString getVisibleDeviceListBytes ()

 A comma-separated list of GPU ids that determines the 'visible'
 to 'virtual' mapping of GPU devices.  For example, if TensorFlow
 can see 8 GPU devices in the process, and one wanted to map
 visible GPU devices 5 and 3 as "/device:GPU:0", and "/device:GPU:1",
 then one would specify this field as "5,3".  This field is similar in
 spirit to the CUDA_VISIBLE_DEVICES environment variable, except
 it applies to the visible GPU devices in the process.
 NOTE:
 1. The GPU driver provides the process with the visible GPUs
    in an order which is not guaranteed to have any correlation to
    the *physical* GPU id in the machine.  This field is used for
    remapping "visible" to "virtual", which means this operates only
    after the process starts.  Users are required to use vendor
    specific mechanisms (e.g., CUDA_VISIBLE_DEVICES) to control the
    physical to visible device mapping prior to invoking TensorFlow.
 2. In the code, the ids in this list are also called "platform GPU id"s,
    and the 'virtual' ids of GPU devices (i.e. the ids in the device
    name "/device:GPU:<id>") are also called "TF GPU id"s. Please
    refer to third_party/tensorflow/core/common_runtime/gpu/gpu_id.h
    for more information.

string visible_device_list = 5;

boolean publik hasEksperimental ()

 Everything inside experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.

.tensorflow.GPUOptions.Experimental experimental = 9;

kode hash int publik ()

boolean akhir publik diinisialisasi ()

GPUOptions statis publik.Builder newBuilder (prototipe GPUOptions )

GPUOptions statis publik.Builder newBuilder ()

GPUOptions publik.Builder newBuilderForType ()

GPUOptions statis publik parseDelimitedFrom (input InputStream)

Melempar

Pengecualian IO

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

Melempar

Pengecualian IO

parseFrom GPUOptions statis publik (data ByteBuffer)

Melempar

InvalidProtocolBufferException

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

Melempar

Pengecualian IO

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

Melempar

InvalidProtocolBufferException

parseFrom GPUOptions statis publik (com.google.protobuf.CodedInputStream input)

Melempar

Pengecualian IO

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

Melempar

InvalidProtocolBufferException

parseFrom GPUOptions statis publik (com.google.protobuf.ByteString data)

Melempar

InvalidProtocolBufferException

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

Melempar

Pengecualian IO

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

Melempar

InvalidProtocolBufferException

statis publik pengurai ()

GPUOptions.Builder toBuilder publik ()

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

Melempar

Pengecualian IO