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
Opsi GPU
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
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.
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
final com.google.protobuf.UnknownFieldSet
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
boolean terakhir
GPUOptions.Builder statis
newBuilder (prototipe GPUOptions )
GPUOptions.Builder statis
Opsi GPU.Pembangun
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
Opsi GPU.Pembangun
ruang kosong
writeTo (com.google.protobuf.CodedOutputStream keluaran)

Metode Warisan

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 final statis publik EXPERIMENTAL_FIELD_NUMBER

Nilai Konstan: 9

int final statis publik FORCE_GPU_COMPATIBLE_FIELD_NUMBER

Nilai Konstan: 8

int final 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
ProtokolBufferException Tidak Valid

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
ProtokolBufferException Tidak Valid

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

Melempar
Pengecualian IO

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

Melempar
ProtokolBufferException Tidak Valid

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

Melempar
ProtokolBufferException Tidak Valid

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
ProtokolBufferException Tidak Valid

statis publik pengurai ()

GPUOptions.Builder toBuilder publik ()

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

Melempar
Pengecualian IO