GPUOptions

public final class GPUOptions

tensorflow.GPUOptions type tensorflow.GPUOptions

Classes aninhadas

aula GPUOptions.Builder tensorflow.GPUOptions type tensorflow.GPUOptions
aula GPUOptions.Experimental tensorflow.GPUOptions.Experimental type tensorflow.GPUOptions.Experimental
interface GPUOptions.ExperimentalOrBuilder

Constantes

int ALLOCATOR_TYPE_FIELD_NUMBER
int ALLOW_GROWTH_FIELD_NUMBER
int DEFERRED_DELETION_BYTES_FIELD_NUMBER
int EXPERIMENTAL_FIELD_NUMBER
int FORCE_GPU_COMPATIBLE_FIELD_NUMBER
int PER_PROCESS_GPU_MEMORY_FRACTION_FIELD_NUMBER
int POLLING_ACTIVE_DELAY_USECS_FIELD_NUMBER
int POLLING_INACTIVE_DELAY_MSECS_FIELD_NUMBER
int VISIBLE_DEVICE_LIST_FIELD_NUMBER

Métodos Públicos

boleano
igual a (objeto obj)
Fragmento
getAllocatorType ()
 The type of GPU allocation strategy to use.
com.google.protobuf.ByteString
getAllocatorTypeBytes ()
 The type of GPU allocation strategy to use.
boleano
getAllowGrowth ()
 If true, the allocator does not pre-allocate the entire specified
 GPU memory region, instead starting small and growing as needed.
GPUOptions estáticos
getDefaultInstance ()
Opções GPU
getDefaultInstanceForType ()
longo
getDeferredDeletionBytes ()
 Delay deletion of up to this many bytes to reduce the number of
 interactions with gpu driver code.
final static com.google.protobuf.Descriptors.Descriptor
getDescriptor ()
GPUOptions.Experimental
getExperimental ()
 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
getExperimentalOrBuilder ()
 Everything inside experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.
boleano
getForceGpuCompatible ()
 Force all tensors to be gpu_compatible.
getParserForType ()
Duplo
getPerProcessGpuMemoryFraction ()
 Fraction of the available GPU memory to allocate for each process.
int
getPollingActiveDelayUsecs ()
 In the event polling loop sleep this many microseconds between
 PollEvents calls, when the queue is not empty.
int
getPollingInactiveDelayMsecs ()
 This field is deprecated and ignored.
int
getSerializedSize ()
final com.google.protobuf.UnknownFieldSet
getUnknownFields ()
Fragmento
getVisibleDeviceList ()
 A comma-separated list of GPU ids that determines the 'visible'
 to 'virtual' mapping of GPU devices.
com.google.protobuf.ByteString
getVisibleDeviceListBytes ()
 A comma-separated list of GPU ids that determines the 'visible'
 to 'virtual' mapping of GPU devices.
boleano
hasExperimental ()
 Everything inside experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.
int
hashCode ()
final booleano
isInitialized ()
GPUOptions.Builder estático
newBuilder (protótipo GPUOptions )
GPUOptions.Builder estático
newBuilder ()
GPUOptions.Builder
newBuilderForType ()
GPUOptions estáticos
parseDelimitedFrom (input InputStream)
GPUOptions estáticos
parseDelimitedFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
GPUOptions estáticos
parseFrom (dados ByteBuffer)
GPUOptions estáticos
parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
GPUOptions estáticos
parseFrom (ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
GPUOptions estáticos
parseFrom (com.google.protobuf.CodedInputStream input)
GPUOptions estáticos
parseFrom (byte [] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
GPUOptions estáticos
parseFrom (com.google.protobuf.ByteString data)
GPUOptions estáticos
parseFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
GPUOptions estáticos
parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
estático
analisador ()
GPUOptions.Builder
toBuilder ()
vazio
writeTo (saída com.google.protobuf.CodedOutputStream)

Métodos herdados

Constantes

public static final int ALLOCATOR_TYPE_FIELD_NUMBER

Valor constante: 2

public static final int ALLOW_GROWTH_FIELD_NUMBER

Valor constante: 4

público estático final int DEFERRED_DELETION_BYTES_FIELD_NUMBER

Valor Constante: 3

public static final int EXPERIMENTAL_FIELD_NUMBER

Valor constante: 9

public static final int FORCE_GPU_COMPATIBLE_FIELD_NUMBER

Valor constante: 8

public static final int PER_PROCESS_GPU_MEMORY_FRACTION_FIELD_NUMBER

Valor Constante: 1

public static final int POLLING_ACTIVE_DELAY_USECS_FIELD_NUMBER

Valor constante: 6

public static final int POLLING_INACTIVE_DELAY_MSECS_FIELD_NUMBER

Valor constante: 7

public static final int VISIBLE_DEVICE_LIST_FIELD_NUMBER

Valor constante: 5

Métodos Públicos

public boolean equals (Object obj)

public String 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;

public 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;

public boolean 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;

public static GPUOptions getDefaultInstance ()

public GPUOptions getDefaultInstanceForType ()

public long getDeferredDeletionBytes () 

 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 ()

public GPUOptions.Experimental getExperimental () 

 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;

public GPUOptions.ExperimentalOrBuilder 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;

public boolean 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;

público getParserForType ()

public double getPerProcessGpuMemoryFraction () 

 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;

public int 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;

public int getPollingInactiveDelayMsecs () 

 This field is deprecated and ignored.
int32 polling_inactive_delay_msecs = 7;

public int getSerializedSize ()

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

public String 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;

public 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;

public boolean hasExperimental () 

 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;

public int hashCode ()

public final boolean isInitialized ()

public static GPUOptions.Builder newBuilder (protótipo GPUOptions )

public static GPUOptions.Builder newBuilder ()

public GPUOptions.Builder newBuilderForType ()

public static GPUOptions parseDelimitedFrom (InputStream input)

Lança
IOException

public static GPUOptions parseDelimitedFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lança
IOException

public static GPUOptions parseFrom (dados ByteBuffer)

Lança
InvalidProtocolBufferException

public static GPUOptions parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lança
IOException

public static GPUOptions parseFrom (ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lança
InvalidProtocolBufferException

public static GPUOptions parseFrom (com.google.protobuf.CodedInputStream input)

Lança
IOException

public static GPUOptions parseFrom (byte [] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lança
InvalidProtocolBufferException

public static GPUOptions parseFrom (com.google.protobuf.ByteString data)

Lança
InvalidProtocolBufferException

public static GPUOptions parseFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)

Lança
IOException

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

Lança
InvalidProtocolBufferException

estática pública analisador ()

public GPUOptions.Builder toBuilder ()

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

Lança
IOException