Package org.tensorflow.framework

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.framework.GPUOptions.Builder
All Implemented Interfaces:
com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable, GPUOptionsOrBuilder
Enclosing class:
GPUOptions
public static final class GPUOptions.Builder extends com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Builder> implements GPUOptionsOrBuilder
Protobuf type tensorflow.GPUOptions

  • Method Details

    • getDescriptor

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

    • internalGetFieldAccessorTable

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

    • clear

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

    • getDescriptorForType

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

    • getDefaultInstanceForType

      public GPUOptions getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

    • build

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

    • buildPartial

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

    • clone

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

    • setField

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

    • clearField

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

    • clearOneof

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

    • setRepeatedField

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

    • addRepeatedField

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

    • mergeFrom

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

    • mergeFrom

      public GPUOptions.Builder mergeFrom(GPUOptions other)

    • isInitialized

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

    • mergeFrom

      public GPUOptions.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.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 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;
      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(com.google.protobuf.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.
 3. The visible_device_list is also used for PluggableDevice. And
    different types of PluggableDevices share this field. In that case,
    the pluggable_device_type is used to distinguish them, making the
    visible_device_list a list of <pluggable_device_type>:<device_index>,
    e.g. "PluggableDeviceA:0,PluggableDeviceA:1,PluggableDeviceB:0".
      string visible_device_list = 5;
      Specified by:
      getVisibleDeviceList in interface GPUOptionsOrBuilder
      Returns:
      The visibleDeviceList.

    • getVisibleDeviceListBytes

      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.
 3. The visible_device_list is also used for PluggableDevice. And
    different types of PluggableDevices share this field. In that case,
    the pluggable_device_type is used to distinguish them, making the
    visible_device_list a list of <pluggable_device_type>:<device_index>,
    e.g. "PluggableDeviceA:0,PluggableDeviceA:1,PluggableDeviceB:0".
      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.
 3. The visible_device_list is also used for PluggableDevice. And
    different types of PluggableDevices share this field. In that case,
    the pluggable_device_type is used to distinguish them, making the
    visible_device_list a list of <pluggable_device_type>:<device_index>,
    e.g. "PluggableDeviceA:0,PluggableDeviceA:1,PluggableDeviceB:0".
      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.
 3. The visible_device_list is also used for PluggableDevice. And
    different types of PluggableDevices share this field. In that case,
    the pluggable_device_type is used to distinguish them, making the
    visible_device_list a list of <pluggable_device_type>:<device_index>,
    e.g. "PluggableDeviceA:0,PluggableDeviceA:1,PluggableDeviceB:0".
      string visible_device_list = 5;
      Returns:
      This builder for chaining.

    • setVisibleDeviceListBytes

      public GPUOptions.Builder setVisibleDeviceListBytes(com.google.protobuf.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.
 3. The visible_device_list is also used for PluggableDevice. And
    different types of PluggableDevices share this field. In that case,
    the pluggable_device_type is used to distinguish them, making the
    visible_device_list a list of <pluggable_device_type>:<device_index>,
    e.g. "PluggableDeviceA:0,PluggableDeviceA:1,PluggableDeviceB:0".
      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(com.google.protobuf.UnknownFieldSet unknownFields)
      Specified by:
      setUnknownFields in interface com.google.protobuf.Message.Builder
      Overrides:
      setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Builder>

    • mergeUnknownFields

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