Class GPUOptions.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<GPUOptions.Builder>
com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Builder>
org.tensorflow.proto.GPUOptions.Builder
All Implemented Interfaces:
Message.Builder, MessageLite.Builder, MessageLiteOrBuilder, MessageOrBuilder, Cloneable, GPUOptionsOrBuilder
Enclosing class:
GPUOptions
public static final class GPUOptions.Builder extends GeneratedMessageV3.Builder<GPUOptions.Builder> implements GPUOptionsOrBuilder
Protobuf type tensorflow.GPUOptions

  • Method Details

    • getDescriptor

      public static final Descriptors.Descriptor getDescriptor()

    • internalGetFieldAccessorTable

      protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class GeneratedMessageV3.Builder<GPUOptions.Builder>

    • clear

      public GPUOptions.Builder clear()
      Specified by:
      clear in interface Message.Builder
      Specified by:
      clear in interface MessageLite.Builder
      Overrides:
      clear in class GeneratedMessageV3.Builder<GPUOptions.Builder>

    • getDescriptorForType

      public Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface Message.Builder
      Specified by:
      getDescriptorForType in interface MessageOrBuilder
      Overrides:
      getDescriptorForType in class GeneratedMessageV3.Builder<GPUOptions.Builder>

    • getDefaultInstanceForType

      public GPUOptions getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface MessageOrBuilder

    • build

      public GPUOptions build()
      Specified by:
      build in interface Message.Builder
      Specified by:
      build in interface MessageLite.Builder

    • buildPartial

      public GPUOptions buildPartial()
      Specified by:
      buildPartial in interface Message.Builder
      Specified by:
      buildPartial in interface MessageLite.Builder

    • clone

      public GPUOptions.Builder clone()
      Specified by:
      clone in interface Message.Builder
      Specified by:
      clone in interface MessageLite.Builder
      Overrides:
      clone in class GeneratedMessageV3.Builder<GPUOptions.Builder>

    • setField

      public GPUOptions.Builder setField(Descriptors.FieldDescriptor field, Object value)
      Specified by:
      setField in interface Message.Builder
      Overrides:
      setField in class GeneratedMessageV3.Builder<GPUOptions.Builder>

    • clearField

      public GPUOptions.Builder clearField(Descriptors.FieldDescriptor field)
      Specified by:
      clearField in interface Message.Builder
      Overrides:
      clearField in class GeneratedMessageV3.Builder<GPUOptions.Builder>

    • clearOneof

      public GPUOptions.Builder clearOneof(Descriptors.OneofDescriptor oneof)
      Specified by:
      clearOneof in interface Message.Builder
      Overrides:
      clearOneof in class GeneratedMessageV3.Builder<GPUOptions.Builder>

    • setRepeatedField

      public GPUOptions.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
      Specified by:
      setRepeatedField in interface Message.Builder
      Overrides:
      setRepeatedField in class GeneratedMessageV3.Builder<GPUOptions.Builder>

    • addRepeatedField

      public GPUOptions.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
      Specified by:
      addRepeatedField in interface Message.Builder
      Overrides:
      addRepeatedField in class GeneratedMessageV3.Builder<GPUOptions.Builder>

    • mergeFrom

      public GPUOptions.Builder mergeFrom(Message other)
      Specified by:
      mergeFrom in interface Message.Builder
      Overrides:
      mergeFrom in class AbstractMessage.Builder<GPUOptions.Builder>

    • mergeFrom

      public GPUOptions.Builder mergeFrom(GPUOptions other)

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface MessageLiteOrBuilder
      Overrides:
      isInitialized in class GeneratedMessageV3.Builder<GPUOptions.Builder>

    • mergeFrom

      public GPUOptions.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface Message.Builder
      Specified by:
      mergeFrom in interface MessageLite.Builder
      Overrides:
      mergeFrom in class AbstractMessage.Builder<GPUOptions.Builder>
      Throws:
      IOException

    • getPerProcessGpuMemoryFraction

      public double getPerProcessGpuMemoryFraction()
      Fraction of the total 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 total 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;
      Specified by:
      getPerProcessGpuMemoryFraction in interface GPUOptionsOrBuilder
      Returns:
      The perProcessGpuMemoryFraction.

    • setPerProcessGpuMemoryFraction

      public GPUOptions.Builder setPerProcessGpuMemoryFraction(double value)
      Fraction of the total 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 total 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;
      Parameters:
      value - The perProcessGpuMemoryFraction to set.
      Returns:
      This builder for chaining.

    • clearPerProcessGpuMemoryFraction

      public GPUOptions.Builder clearPerProcessGpuMemoryFraction()
      Fraction of the total 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 total 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;
      Returns:
      This builder for chaining.

    • getAllowGrowth

      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;
      Specified by:
      getAllowGrowth in interface GPUOptionsOrBuilder
      Returns:
      The allowGrowth.

    • setAllowGrowth

      public GPUOptions.Builder setAllowGrowth(boolean value)
      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;
      Parameters:
      value - The allowGrowth to set.
      Returns:
      This builder for chaining.

    • clearAllowGrowth

      public 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;
      Returns:
      This builder for chaining.

    • getAllocatorType

      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;
      Specified by:
      getAllocatorType in interface GPUOptionsOrBuilder
      Returns:
      The allocatorType.

    • getAllocatorTypeBytes

      public 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;
      Specified by:
      getAllocatorTypeBytes in interface GPUOptionsOrBuilder
      Returns:
      The bytes for allocatorType.

    • setAllocatorType

      public GPUOptions.Builder setAllocatorType(String value)
      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;
      Parameters:
      value - The allocatorType to set.
      Returns:
      This builder for chaining.

    • clearAllocatorType

      public 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;
      Returns:
      This builder for chaining.

    • setAllocatorTypeBytes

      public GPUOptions.Builder setAllocatorTypeBytes(ByteString value)
      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;
      Parameters:
      value - The bytes for allocatorType to set.
      Returns:
      This builder for chaining.

    • getDeferredDeletionBytes

      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;
      Specified by:
      getDeferredDeletionBytes in interface GPUOptionsOrBuilder
      Returns:
      The deferredDeletionBytes.

    • setDeferredDeletionBytes

      public GPUOptions.Builder setDeferredDeletionBytes(long value)
      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;
      Parameters:
      value - The deferredDeletionBytes to set.
      Returns:
      This builder for chaining.

    • clearDeferredDeletionBytes

      public 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;
      Returns:
      This builder for chaining.

    • getVisibleDeviceList

      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;
      Specified by:
      getVisibleDeviceList in interface GPUOptionsOrBuilder
      Returns:
      The visibleDeviceList.

    • getVisibleDeviceListBytes

      public 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;
      Specified by:
      getVisibleDeviceListBytes in interface GPUOptionsOrBuilder
      Returns:
      The bytes for visibleDeviceList.

    • setVisibleDeviceList

      public GPUOptions.Builder setVisibleDeviceList(String value)
      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;
      Parameters:
      value - The visibleDeviceList to set.
      Returns:
      This builder for chaining.

    • clearVisibleDeviceList

      public 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;
      Returns:
      This builder for chaining.

    • setVisibleDeviceListBytes

      public GPUOptions.Builder setVisibleDeviceListBytes(ByteString value)
      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;
      Parameters:
      value - The bytes for visibleDeviceList to set.
      Returns:
      This builder for chaining.

    • getPollingActiveDelayUsecs

      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;
      Specified by:
      getPollingActiveDelayUsecs in interface GPUOptionsOrBuilder
      Returns:
      The pollingActiveDelayUsecs.

    • setPollingActiveDelayUsecs

      public GPUOptions.Builder setPollingActiveDelayUsecs(int value)
      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;
      Parameters:
      value - The pollingActiveDelayUsecs to set.
      Returns:
      This builder for chaining.

    • clearPollingActiveDelayUsecs

      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;
      Returns:
      This builder for chaining.

    • getPollingInactiveDelayMsecs

      public int getPollingInactiveDelayMsecs()
      This field is deprecated and ignored.
      int32 polling_inactive_delay_msecs = 7;
      Specified by:
      getPollingInactiveDelayMsecs in interface GPUOptionsOrBuilder
      Returns:
      The pollingInactiveDelayMsecs.

    • setPollingInactiveDelayMsecs

      public GPUOptions.Builder setPollingInactiveDelayMsecs(int value)
      This field is deprecated and ignored.
      int32 polling_inactive_delay_msecs = 7;
      Parameters:
      value - The pollingInactiveDelayMsecs to set.
      Returns:
      This builder for chaining.

    • clearPollingInactiveDelayMsecs

      public GPUOptions.Builder clearPollingInactiveDelayMsecs()
      This field is deprecated and ignored.
      int32 polling_inactive_delay_msecs = 7;
      Returns:
      This builder for chaining.

    • getForceGpuCompatible

      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;
      Specified by:
      getForceGpuCompatible in interface GPUOptionsOrBuilder
      Returns:
      The forceGpuCompatible.

    • setForceGpuCompatible

      public GPUOptions.Builder setForceGpuCompatible(boolean value)
      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;
      Parameters:
      value - The forceGpuCompatible to set.
      Returns:
      This builder for chaining.

    • clearForceGpuCompatible

      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;
      Returns:
      This builder for chaining.

    • hasExperimental

      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;
      Specified by:
      hasExperimental in interface GPUOptionsOrBuilder
      Returns:
      Whether the experimental field is set.

    • getExperimental

      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;
      Specified by:
      getExperimental in interface GPUOptionsOrBuilder
      Returns:
      The experimental.

    • setExperimental

      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;

    • setExperimental

      public 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.
      .tensorflow.GPUOptions.Experimental experimental = 9;

    • mergeExperimental

      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;

    • clearExperimental

      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;

    • getExperimentalBuilder

      public 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;

    • getExperimentalOrBuilder

      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;
      Specified by:
      getExperimentalOrBuilder in interface GPUOptionsOrBuilder

    • setUnknownFields

      public final GPUOptions.Builder setUnknownFields(UnknownFieldSet unknownFields)
      Specified by:
      setUnknownFields in interface Message.Builder
      Overrides:
      setUnknownFields in class GeneratedMessageV3.Builder<GPUOptions.Builder>

    • mergeUnknownFields

      public final GPUOptions.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
      Specified by:
      mergeUnknownFields in interface Message.Builder
      Overrides:
      mergeUnknownFields in class GeneratedMessageV3.Builder<GPUOptions.Builder>