GPUOptions.Builder

публичный статический конечный класс GPUOptions.Builder

Тип protobuf tensorflow.GPUOptions

Публичные методы

GPUOptions.Builder
addRepeatedField (поле com.google.protobuf.Descriptors.FieldDescriptor, значение объекта)
Параметры графического процессора
Параметры графического процессора
GPUOptions.Builder
GPUOptions.Builder
ОчиститьАллокаторТип ()
 The type of GPU allocation strategy to use.
GPUOptions.Builder
ОчиститьАлловГровс ()
 If true, the allocator does not pre-allocate the entire specified
 GPU memory region, instead starting small and growing as needed.
GPUOptions.Builder
ClearDeferredDeletionBytes ()
 Delay deletion of up to this many bytes to reduce the number of
 interactions with gpu driver code.
GPUOptions.Builder
очиститьЭкспериментальный ()
 Everything inside experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.
GPUOptions.Builder
ClearField (поле com.google.protobuf.Descriptors.FieldDescriptor)
GPUOptions.Builder
ClearForceGpuCompatible ()
 Force all tensors to be gpu_compatible.
GPUOptions.Builder
ClearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)
GPUOptions.Builder
ClearPerProcessGpuMemoryFraction ()
 Fraction of the available GPU memory to allocate for each process.
GPUOptions.Builder
ClearPollingActiveDelayUsecs ()
 In the event polling loop sleep this many microseconds between
 PollEvents calls, when the queue is not empty.
GPUOptions.Builder
ClearPollingInactiveDelayMsecs ()
 This field is deprecated and ignored.
GPUOptions.Builder
ClearVisibleDeviceList ()
 A comma-separated list of GPU ids that determines the 'visible'
 to 'virtual' mapping of GPU devices.
GPUOptions.Builder
Нить
ПолучитьАллокаторТип ()
 The type of GPU allocation strategy to use.
com.google.protobuf.ByteString
getAllocatorTypeBytes ()
 The type of GPU allocation strategy to use.
логическое значение
getAllowGrowth ()
 If true, the allocator does not pre-allocate the entire specified
 GPU memory region, instead starting small and growing as needed.
Параметры графического процессора
длинный
getDeferredDeletionBytes ()
 Delay deletion of up to this many bytes to reduce the number of
 interactions with gpu driver code.
окончательный статический com.google.protobuf.Descriptors.Descriptor
com.google.protobuf.Descriptors.Descriptor
GPUOptions.Экспериментальный
получитьЭкспериментальный ()
 Everything inside experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.
GPUOptions.Experimental.Builder
getExperimentalBuilder ()
 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.
логическое значение
getForceGpuCompatible ()
 Force all tensors to be gpu_compatible.
двойной
getPerProcessGpuMemoryFraction ()
 Fraction of the available GPU memory to allocate for each process.
интервал
getPollingActiveDelayUsecs ()
 In the event polling loop sleep this many microseconds between
 PollEvents calls, when the queue is not empty.
интервал
getPollingInactiveDelayMsecs ()
 This field is deprecated and ignored.
Нить
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.
логическое значение
имеетЭкспериментальный ()
 Everything inside experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.
последнее логическое значение
GPUOptions.Builder
mergeExperimental ( GPUOptions.Экспериментальное значение)
 Everything inside experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.
GPUOptions.Builder
mergeFrom (com.google.protobuf.Message другое)
GPUOptions.Builder
mergeFrom (ввод com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
окончательный вариант GPUOptions.Builder
mergeUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)
GPUOptions.Builder
setAllocatorType (строковое значение)
 The type of GPU allocation strategy to use.
GPUOptions.Builder
setAllocatorTypeBytes (значение com.google.protobuf.ByteString)
 The type of GPU allocation strategy to use.
GPUOptions.Builder
setAllowGrowth (логическое значение)
 If true, the allocator does not pre-allocate the entire specified
 GPU memory region, instead starting small and growing as needed.
GPUOptions.Builder
setDeferredDeletionBytes (длинное значение)
 Delay deletion of up to this many bytes to reduce the number of
 interactions with gpu driver code.
GPUOptions.Builder
setExperimental ( GPUOptions.Experimental.Builder builderForValue)
 Everything inside experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.
GPUOptions.Builder
setExperimental ( GPUOptions.Экспериментальное значение)
 Everything inside experimental is subject to change and is not subject
 to API stability guarantees in
 https://www.tensorflow.org/guide/version_compat.
GPUOptions.Builder
setField (поле com.google.protobuf.Descriptors.FieldDescriptor, значение объекта)
GPUOptions.Builder
setForceGpuCompatible (логическое значение)
 Force all tensors to be gpu_compatible.
GPUOptions.Builder
setPerProcessGpuMemoryFraction (двойное значение)
 Fraction of the available GPU memory to allocate for each process.
GPUOptions.Builder
setPollingActiveDelayUsecs (целое значение)
 In the event polling loop sleep this many microseconds between
 PollEvents calls, when the queue is not empty.
GPUOptions.Builder
setPollingInactiveDelayMsecs (целое значение)
 This field is deprecated and ignored.
GPUOptions.Builder
setRepeatedField (поле com.google.protobuf.Descriptors.FieldDescriptor, индекс int, значение объекта)
окончательный вариант GPUOptions.Builder
setUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)
GPUOptions.Builder
setVisibleDeviceList (строковое значение)
 A comma-separated list of GPU ids that determines the 'visible'
 to 'virtual' mapping of GPU devices.
GPUOptions.Builder
setVisibleDeviceListBytes (значение com.google.protobuf.ByteString)
 A comma-separated list of GPU ids that determines the 'visible'
 to 'virtual' mapping of GPU devices.

Унаследованные методы

Публичные методы

public GPUOptions.Builder addRepeatedField (поле com.google.protobuf.Descriptors.FieldDescriptor, значение объекта)

общедоступная сборка GPUOptions ()

общедоступные GPUOptions buildPartial ()

общедоступный GPUOptions.Builder очистить ()

общедоступный GPUOptions.Builder ClearAllocatorType ()

 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;

общедоступный GPUOptions.Builder ClearAllowGrowth ()

 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;

общедоступный GPUOptions.Builder ClearDeferredDeletionBytes ()

 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 GPUOptions.Builder ClearExperimental ()

 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.Builder ClearField (поле com.google.protobuf.Descriptors.FieldDescriptor)

public GPUOptions.Builder ClearForceGpuCompatible ()

 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;

общедоступный GPUOptions.Builder ClearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)

public GPUOptions.Builder ClearPerProcessGpuMemoryFraction ()

 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 GPUOptions.Builder ClearPollingActiveDelayUsecs ()

 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 GPUOptions.Builder ClearPollingInactiveDelayMsecs ()

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

общедоступный GPUOptions.Builder ClearVisibleDeviceList ()

 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;

общедоступный клон GPUOptions.Builder ()

общедоступная строка 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;

общедоступное логическое значение 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;

общедоступные GPUOptions getDefaultInstanceForType ()

общедоступный длинный 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;

общедоступный статический окончательный com.google.protobuf.Descriptors.Descriptor getDescriptor ()

общедоступный com.google.protobuf.Descriptors.Descriptor getDescriptorForType ()

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;

общедоступный GPUOptions.Experimental.Builder getExperimentalBuilder ()

 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;

общедоступное логическое значение 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;

публичный двойной 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;

публичная строка 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;

общедоступное логическое значение 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;

публичное финальное логическое значение isInitialized ()

public GPUOptions.Builder mergeExperimental ( GPUOptions.Experimental value)

 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.Builder mergeFrom (com.google.protobuf.Message другое)

public GPUOptions.Builder mergeFrom (вход com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Броски
Исключение IO

общедоступный окончательный вариант GPUOptions.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)

public GPUOptions.Builder setAllocatorType (строковое значение)

 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 GPUOptions.Builder setAllocatorTypeBytes (значение com.google.protobuf.ByteString)

 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 GPUOptions.Builder setAllowGrowth (логическое значение)

 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 GPUOptions.Builder setDeferredDeletionBytes (длинное значение)

 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;

общедоступный набор GPUOptions.BuilderExperimental ( GPUOptions.Experimental.Builder builderForValue)

 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.Builder setExperimental ( GPUOptions.Experimental value)

 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.Builder setField (поле com.google.protobuf.Descriptors.FieldDescriptor, значение объекта)

public GPUOptions.Builder setForceGpuCompatible (логическое значение)

 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;

public GPUOptions.Builder setPerProcessGpuMemoryFraction (двойное значение)

 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 GPUOptions.Builder setPollingActiveDelayUsecs (целое значение)

 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 GPUOptions.Builder setPollingInactiveDelayMsecs (целое значение)

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

public GPUOptions.Builder setRepeatedField (поле com.google.protobuf.Descriptors.FieldDescriptor, индекс int, значение объекта)

общедоступный окончательный вариант GPUOptions.Builder setUnknownFields (com.google.protobuf.UnknownFieldSetknownFields)

public GPUOptions.Builder setVisibleDeviceList (строковое значение)

 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 GPUOptions.Builder setVisibleDeviceListBytes (значение com.google.protobuf.ByteString)

 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;