GPUOptions.Experimental

パブリック静的最終クラスGPUOptions.Experimental

Protobuf 型tensorflow.GPUOptions.Experimental

ネストされたクラス

クラス	GPUOptions.Experimental.Builder		Protobuf 型tensorflow.GPUOptions.Experimental
クラス	GPUOptions.Experimental.VirtualDevices		Configuration for breaking down a visible GPU into multiple "virtual" devices.
インターフェース	GPUOptions.Experimental.VirtualDevicesOrBuilder

定数

整数	COLLECTIVE_RING_ORDER_FIELD_NUMBER
整数	KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER
整数	KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER
整数	KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER
整数	NUM_DEV_TO_DEV_COPY_STREAMS_FIELD_NUMBER
整数	TIMESTAMPED_ALLOCATOR_FIELD_NUMBER
整数	USE_UNIFIED_MEMORY_FIELD_NUMBER
整数	VIRTUAL_DEVICES_FIELD_NUMBER

パブリックメソッド

ブール値	等しい(オブジェクトオブジェクト)
弦	getCollectiveRingOrder () If non-empty, defines a good GPU ring order on a single worker based on device interconnect.
com.google.protobuf.ByteString	getCollectiveRingOrderBytes () If non-empty, defines a good GPU ring order on a single worker based on device interconnect.
静的GPUOptions.Experimental	getDefaultInstance ()
GPUOptions.Experimental	getDefaultInstanceForType ()
最終的な静的 com.google.protobuf.Descriptors.Descriptor	getDescriptor ()
整数	getKernelTrackerMaxBytes () If kernel_tracker_max_bytes = n > 0, then a tracking event is inserted after every series of kernels allocating a sum of memory >= n.
整数	getKernelTrackerMaxInterval () Parameters for GPUKernelTracker.
整数	getKernelTrackerMaxPending () If kernel_tracker_max_pending > 0 then no more than this many tracking events can be outstanding at a time.
整数	getNumDevToDevCopyStreams () If > 1, the number of device-to-device copy streams to create for each GPUDevice.
	getParserForType ()
整数	getSerializedSize ()
ブール値	getTimestampedAllocator () If true then extra work is done by GPUDevice and GPUBFCAllocator to keep track of when GPU memory is freed and when kernels actually complete so that we can know when a nominally free memory chunk is really not subject to pending use.
最終的な com.google.protobuf.UnknownFieldSet	getUnknownFields ()
ブール値	getUseUnifiedMemory () If true, uses CUDA unified memory for memory allocations.
GPUOptions.Experimental.VirtualDevices	getVirtualDevices (int インデックス) The multi virtual device settings.
整数	getVirtualDevicesCount () The multi virtual device settings.
リスト< GPUOptions.Experimental.VirtualDevices >	getVirtualDevicesList () The multi virtual device settings.
GPUOptions.Experimental.VirtualDevicesOrBuilder	getVirtualDevicesOrBuilder (int インデックス) The multi virtual device settings.
リスト<? GPUOptions.Experimental.VirtualDevicesOrBuilderを拡張 >	getVirtualDevicesOrBuilderList () The multi virtual device settings.
整数	ハッシュコード（）
最終ブール値	isInitialized ()
静的GPUOptions.Experimental.Builder	newBuilder ( GPUOptions.Experimentalプロトタイプ)
静的GPUOptions.Experimental.Builder	newBuilder ()
GPUOptions.Experimental.Builder	newBuilderForType ()
静的GPUOptions.Experimental	parseDelimitedFrom (InputStream 入力)
静的GPUOptions.Experimental	parseDelimitedFrom (InputStream 入力、com.google.protobuf.ExtensionRegistryLite extensionRegistry)
静的GPUOptions.Experimental	parseFrom (ByteBuffer データ)
静的GPUOptions.Experimental	parseFrom (com.google.protobuf.CodedInputStream 入力、com.google.protobuf.ExtensionRegistryLite extensionRegistry)
静的GPUOptions.Experimental	parseFrom (ByteBuffer データ、com.google.protobuf.ExtensionRegistryLite extensionRegistry)
静的GPUOptions.Experimental	parseFrom (com.google.protobuf.CodedInputStream 入力)
静的GPUOptions.Experimental	parseFrom (byte[] データ、com.google.protobuf.ExtensionRegistryLite extensionRegistry)
静的GPUOptions.Experimental	parseFrom (com.google.protobuf.ByteString データ)
静的GPUOptions.Experimental	parseFrom (InputStream 入力、com.google.protobuf.ExtensionRegistryLite extensionRegistry)
静的GPUOptions.Experimental	parseFrom (com.google.protobuf.ByteString データ、com.google.protobuf.ExtensionRegistryLite extensionRegistry)
静的	パーサー()
GPUOptions.Experimental.Builder	toビルダー()
空所	writeTo (com.google.protobuf.CodedOutputStream 出力)

継承されたメソッド

クラスjava.lang.Objectから

ブール値	等しい(オブジェクト arg0)
最終クラス<?>	getクラス()
整数	ハッシュコード（）
最後の空白	通知する()
最後の空白	すべて通知()
弦	toString ()
最後の空白	wait (long arg0, int arg1)
最後の空白	待機(長い引数0)
最後の空白	待って（）

インターフェースorg.tensorflow.proto.framework.GPUOptions.ExperimentalOrBuilderより

抽象文字列	getCollectiveRingOrder () If non-empty, defines a good GPU ring order on a single worker based on device interconnect.
抽象的な com.google.protobuf.ByteString	getCollectiveRingOrderBytes () If non-empty, defines a good GPU ring order on a single worker based on device interconnect.
抽象整数	getKernelTrackerMaxBytes () If kernel_tracker_max_bytes = n > 0, then a tracking event is inserted after every series of kernels allocating a sum of memory >= n.
抽象整数	getKernelTrackerMaxInterval () Parameters for GPUKernelTracker.
抽象整数	getKernelTrackerMaxPending () If kernel_tracker_max_pending > 0 then no more than this many tracking events can be outstanding at a time.
抽象整数	getNumDevToDevCopyStreams () If > 1, the number of device-to-device copy streams to create for each GPUDevice.
抽象ブール値	getTimestampedAllocator () If true then extra work is done by GPUDevice and GPUBFCAllocator to keep track of when GPU memory is freed and when kernels actually complete so that we can know when a nominally free memory chunk is really not subject to pending use.
抽象ブール値	getUseUnifiedMemory () If true, uses CUDA unified memory for memory allocations.
抽象GPUOptions.Experimental.VirtualDevices	getVirtualDevices (int インデックス) The multi virtual device settings.
抽象整数	getVirtualDevicesCount () The multi virtual device settings.
抽象リスト< GPUOptions.Experimental.VirtualDevices >	getVirtualDevicesList () The multi virtual device settings.
抽象GPUOptions.Experimental.VirtualDevicesOrBuilder	getVirtualDevicesOrBuilder (int インデックス) The multi virtual device settings.
抽象リスト<? GPUOptions.Experimental.VirtualDevicesOrBuilderを拡張 >	getVirtualDevicesOrBuilderList () The multi virtual device settings.

定数

public static Final int COLLECTIVE_RING_ORDER_FIELD_NUMBER

定数値: 4

パブリック静的最終整数KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER

定数値: 8

パブリック静的最終整数KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER

定数値: 7

パブリック静的最終整数KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER

定数値: 9

public static Final int NUM_DEV_TO_DEV_COPY_STREAMS_FIELD_NUMBER

定数値: 3

パブリック静的最終整数TIMESTAMPED_ALLOCATOR_FIELD_NUMBER

定数値: 5

パブリック静的最終整数USE_UNIFIED_MEMORY_FIELD_NUMBER

定数値: 2

パブリック静的最終整数VIRTUAL_DEVICES_FIELD_NUMBER

定数値: 1

パブリックメソッド

public booleanに等しい(オブジェクト obj)

パブリック String getCollectiveRingOrder ()

 If non-empty, defines a good GPU ring order on a single worker based on
 device interconnect.  This assumes that all workers have the same GPU
 topology.  Specify as a comma-separated string, e.g. "3,2,1,0,7,6,5,4".
 This ring order is used by the RingReducer implementation of
 CollectiveReduce, and serves as an override to automatic ring order
 generation in OrderTaskDeviceMap() during CollectiveParam resolution.
 

string collective_ring_order = 4;

public com.google.protobuf.ByteString getCollectiveRingOrderBytes ()

 If non-empty, defines a good GPU ring order on a single worker based on
 device interconnect.  This assumes that all workers have the same GPU
 topology.  Specify as a comma-separated string, e.g. "3,2,1,0,7,6,5,4".
 This ring order is used by the RingReducer implementation of
 CollectiveReduce, and serves as an override to automatic ring order
 generation in OrderTaskDeviceMap() during CollectiveParam resolution.
 

string collective_ring_order = 4;

public static GPUOptions.Experimental getDefaultInstance ()

public GPUOptions.Experimental getDefaultInstanceForType ()

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

public int getKernelTrackerMaxBytes ()

 If kernel_tracker_max_bytes = n > 0, then a tracking event is
 inserted after every series of kernels allocating a sum of
 memory >= n.  If one kernel allocates b * n bytes, then one
 event will be inserted after it, but it will count as b against
 the pending limit.
 

int32 kernel_tracker_max_bytes = 8;

public int getKernelTrackerMaxInterval ()

 Parameters for GPUKernelTracker.  By default no kernel tracking is done.
 Note that timestamped_allocator is only effective if some tracking is
 specified.
 If kernel_tracker_max_interval = n > 0, then a tracking event
 is inserted after every n kernels without an event.
 

int32 kernel_tracker_max_interval = 7;

public int getKernelTrackerMaxPending ()

 If kernel_tracker_max_pending > 0 then no more than this many
 tracking events can be outstanding at a time.  An attempt to
 launch an additional kernel will stall until an event
 completes.
 

int32 kernel_tracker_max_pending = 9;

public int getNumDevToDevCopyStreams ()

 If > 1, the number of device-to-device copy streams to create
 for each GPUDevice.  Default value is 0, which is automatically
 converted to 1.
 

int32 num_dev_to_dev_copy_streams = 3;

公共getParserForType ()

public int getSerializedSize ()

public boolean getTimestampedAllocator ()

 If true then extra work is done by GPUDevice and GPUBFCAllocator to
 keep track of when GPU memory is freed and when kernels actually
 complete so that we can know when a nominally free memory chunk
 is really not subject to pending use.
 

bool timestamped_allocator = 5;

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

public boolean getUseUnifiedMemory ()

 If true, uses CUDA unified memory for memory allocations. If
 per_process_gpu_memory_fraction option is greater than 1.0, then unified
 memory is used regardless of the value for this field. See comments for
 per_process_gpu_memory_fraction field for more details and requirements
 of the unified memory. This option is useful to oversubscribe memory if
 multiple processes are sharing a single GPU while individually using less
 than 1.0 per process memory fraction.
 

bool use_unified_memory = 2;

public GPUOptions.Experimental.VirtualDevices getVirtualDevices (int インデックス)

 The multi virtual device settings. If empty (not set), it will create
 single virtual device on each visible GPU, according to the settings
 in "visible_device_list" above. Otherwise, the number of elements in the
 list must be the same as the number of visible GPUs (after
 "visible_device_list" filtering if it is set), and the string represented
 device names (e.g. /device:GPU:<id>) will refer to the virtual
 devices and have the <id> field assigned sequentially starting from 0,
 according to the order they appear in this list and the "memory_limit"
 list inside each element. For example,
   visible_device_list = "1,0"
   virtual_devices { memory_limit: 1GB memory_limit: 2GB }
   virtual_devices {}
 will create three virtual devices as:
   /device:GPU:0 -> visible GPU 1 with 1GB memory
   /device:GPU:1 -> visible GPU 1 with 2GB memory
   /device:GPU:2 -> visible GPU 0 with all available memory
 NOTE:
 1. It's invalid to set both this and "per_process_gpu_memory_fraction"
    at the same time.
 2. Currently this setting is per-process, not per-session. Using
    different settings in different sessions within same process will
    result in undefined behavior.
 

repeated .tensorflow.GPUOptions.Experimental.VirtualDevices virtual_devices = 1;

public int getVirtualDevicesCount ()

 The multi virtual device settings. If empty (not set), it will create
 single virtual device on each visible GPU, according to the settings
 in "visible_device_list" above. Otherwise, the number of elements in the
 list must be the same as the number of visible GPUs (after
 "visible_device_list" filtering if it is set), and the string represented
 device names (e.g. /device:GPU:<id>) will refer to the virtual
 devices and have the <id> field assigned sequentially starting from 0,
 according to the order they appear in this list and the "memory_limit"
 list inside each element. For example,
   visible_device_list = "1,0"
   virtual_devices { memory_limit: 1GB memory_limit: 2GB }
   virtual_devices {}
 will create three virtual devices as:
   /device:GPU:0 -> visible GPU 1 with 1GB memory
   /device:GPU:1 -> visible GPU 1 with 2GB memory
   /device:GPU:2 -> visible GPU 0 with all available memory
 NOTE:
 1. It's invalid to set both this and "per_process_gpu_memory_fraction"
    at the same time.
 2. Currently this setting is per-process, not per-session. Using
    different settings in different sessions within same process will
    result in undefined behavior.
 

repeated .tensorflow.GPUOptions.Experimental.VirtualDevices virtual_devices = 1;

public List< GPUOptions.Experimental.VirtualDevices > getVirtualDevicesList ()

 The multi virtual device settings. If empty (not set), it will create
 single virtual device on each visible GPU, according to the settings
 in "visible_device_list" above. Otherwise, the number of elements in the
 list must be the same as the number of visible GPUs (after
 "visible_device_list" filtering if it is set), and the string represented
 device names (e.g. /device:GPU:<id>) will refer to the virtual
 devices and have the <id> field assigned sequentially starting from 0,
 according to the order they appear in this list and the "memory_limit"
 list inside each element. For example,
   visible_device_list = "1,0"
   virtual_devices { memory_limit: 1GB memory_limit: 2GB }
   virtual_devices {}
 will create three virtual devices as:
   /device:GPU:0 -> visible GPU 1 with 1GB memory
   /device:GPU:1 -> visible GPU 1 with 2GB memory
   /device:GPU:2 -> visible GPU 0 with all available memory
 NOTE:
 1. It's invalid to set both this and "per_process_gpu_memory_fraction"
    at the same time.
 2. Currently this setting is per-process, not per-session. Using
    different settings in different sessions within same process will
    result in undefined behavior.
 

repeated .tensorflow.GPUOptions.Experimental.VirtualDevices virtual_devices = 1;

public GPUOptions.Experimental.VirtualDevicesOrBuilder getVirtualDevicesOrBuilder (int インデックス)

 The multi virtual device settings. If empty (not set), it will create
 single virtual device on each visible GPU, according to the settings
 in "visible_device_list" above. Otherwise, the number of elements in the
 list must be the same as the number of visible GPUs (after
 "visible_device_list" filtering if it is set), and the string represented
 device names (e.g. /device:GPU:<id>) will refer to the virtual
 devices and have the <id> field assigned sequentially starting from 0,
 according to the order they appear in this list and the "memory_limit"
 list inside each element. For example,
   visible_device_list = "1,0"
   virtual_devices { memory_limit: 1GB memory_limit: 2GB }
   virtual_devices {}
 will create three virtual devices as:
   /device:GPU:0 -> visible GPU 1 with 1GB memory
   /device:GPU:1 -> visible GPU 1 with 2GB memory
   /device:GPU:2 -> visible GPU 0 with all available memory
 NOTE:
 1. It's invalid to set both this and "per_process_gpu_memory_fraction"
    at the same time.
 2. Currently this setting is per-process, not per-session. Using
    different settings in different sessions within same process will
    result in undefined behavior.
 

repeated .tensorflow.GPUOptions.Experimental.VirtualDevices virtual_devices = 1;

公開リスト<? extends GPUOptions.Experimental.VirtualDevicesOrBuilder > getVirtualDevicesOrBuilderList ()

 The multi virtual device settings. If empty (not set), it will create
 single virtual device on each visible GPU, according to the settings
 in "visible_device_list" above. Otherwise, the number of elements in the
 list must be the same as the number of visible GPUs (after
 "visible_device_list" filtering if it is set), and the string represented
 device names (e.g. /device:GPU:<id>) will refer to the virtual
 devices and have the <id> field assigned sequentially starting from 0,
 according to the order they appear in this list and the "memory_limit"
 list inside each element. For example,
   visible_device_list = "1,0"
   virtual_devices { memory_limit: 1GB memory_limit: 2GB }
   virtual_devices {}
 will create three virtual devices as:
   /device:GPU:0 -> visible GPU 1 with 1GB memory
   /device:GPU:1 -> visible GPU 1 with 2GB memory
   /device:GPU:2 -> visible GPU 0 with all available memory
 NOTE:
 1. It's invalid to set both this and "per_process_gpu_memory_fraction"
    at the same time.
 2. Currently this setting is per-process, not per-session. Using
    different settings in different sessions within same process will
    result in undefined behavior.
 

repeated .tensorflow.GPUOptions.Experimental.VirtualDevices virtual_devices = 1;

public int hashCode ()

パブリック最終ブール値isInitialized ()

public static GPUOptions.Experimental.Builder newBuilder ( GPUOptions.Experimentalプロトタイプ)

public static GPUOptions.Experimental.Builder newBuilder ()

public GPUOptions.Experimental.Builder newBuilderForType ()

public static GPUOptions.Experimental parseDelimitedFrom (InputStream 入力)

投げる

IO例外

public static GPUOptions.Experimental parseDelimitedFrom (InputStream 入力、com.google.protobuf.ExtensionRegistryLite extensionRegistry)

投げる

IO例外

public static GPUOptions.Experimental parseFrom (ByteBuffer データ)

投げる

無効なプロトコルバッファ例外

public static GPUOptions.Experimental parseFrom (com.google.protobuf.CodedInputStream 入力、com.google.protobuf.ExtensionRegistryLite extensionRegistry)

投げる

IO例外

public static GPUOptions.Experimental parseFrom (ByteBuffer データ、com.google.protobuf.ExtensionRegistryLite extensionRegistry)

投げる

無効なプロトコルバッファ例外

public static GPUOptions.Experimental parseFrom (com.google.protobuf.CodedInputStream 入力)

投げる

IO例外

public static GPUOptions.Experimental parseFrom (byte[] データ、com.google.protobuf.ExtensionRegistryLite extensionRegistry)

投げる

無効なプロトコルバッファ例外

public static GPUOptions.Experimental parseFrom (com.google.protobuf.ByteString データ)

投げる

無効なプロトコルバッファ例外

public static GPUOptions.Experimental parseFrom (InputStream 入力、com.google.protobuf.ExtensionRegistryLite extensionRegistry)

投げる

IO例外

public static GPUOptions.Experimental parseFrom (com.google.protobuf.ByteString データ、com.google.protobuf.ExtensionRegistryLite extensionRegistry)

投げる

無効なプロトコルバッファ例外

パブリック静的パーサー()

public GPUOptions.Experimental.Builder toBuilder ()

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

投げる

IO例外