GPUOptions.Experimental

عمومی استاتیک کلاس نهایی GPUOptions.Experimental

نوع Protobuf tensorflow.GPUOptions.Experimental

کلاس های تو در تو

کلاس	GPUOptions.Experimental.Builder		نوع Protobuf tensorflow.GPUOptions.Experimental
کلاس	GPUOptions.Experimental.VirtualDevices		Configuration for breaking down a visible GPU into multiple "virtual" devices.
رابط	GPUOptions.Experimental.VirtualDevicesOrBuilder

ثابت ها

بین المللی	COLLECTIVE_RING_ORDER_FIELD_NUMBER
بین المللی	KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER
بین المللی	KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER
بین المللی	KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER
بین المللی	NUM_DEV_TO_DEV_COPY_STREAMS_FIELD_NUMBER
بین المللی	TIMESTAMPED_ALLOCATOR_FIELD_NUMBER
بین المللی	USE_UNIFIED_MEMORY_FIELD_NUMBER
بین المللی	VIRTUAL_DEVICES_FIELD_NUMBER

روش های عمومی

بولی	برابر است (object obj)
رشته	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.
استاتیک GPUOptions.Experimental	getDefaultInstance ()
GPUOptions.Experimental	getDefaultInstanceForType ()
نهایی static com.google.protobuf.Descriptors.Descriptor	getDescriptor ()
بین المللی	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.
بین المللی	getKernelTrackerMaxInterval () Parameters for GPUKernelTracker.
بین المللی	getKernelTrackerMaxPending () If kernel_tracker_max_pending > 0 then no more than this many tracking events can be outstanding at a time.
بین المللی	getNumDevToDevCopyStreams () If > 1, the number of device-to-device copy streams to create for each GPUDevice.
	getParserForType ()
بین المللی	getSerializedSize ()
بولی	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.
com.google.protobuf.UnknownFieldSet نهایی	getUnknownFields ()
بولی	getUseUnifiedMemory () If true, uses CUDA unified memory for memory allocations.
GPUOptions.Experimental.VirtualDevices	getVirtualDevices (Int index) The multi virtual device settings.
بین المللی	getVirtualDevicesCount () The multi virtual device settings.
فهرست < GPUOptions.Experimental.VirtualDevices >	getVirtualDevicesList () The multi virtual device settings.
GPUOptions.Experimental.VirtualDevicesOrBuilder	getVirtualDevicesOrBuilder (int index) The multi virtual device settings.
لیست<? GPUOptions.Experimental.VirtualDevicesOrBuilder > را گسترش می دهد	getVirtualDevicesOrBuilderList () The multi virtual device settings.
بین المللی	هش کد ()
بولی نهایی	اولیه شده است ()
استاتیک GPUOptions.Experimental.Builder	newBuilder (نمونه اولیه GPUOptions.Experimental )
استاتیک GPUOptions.Experimental.Builder	newBuilder ()
GPUOptions.Experimental.Builder	newBuilderForType ()
استاتیک GPUOptions.Experimental	parseDelimitedFrom (ورودی جریان ورودی)
استاتیک GPUOptions.Experimental	parseDelimitedFrom (ورودی InputStream، com.google.protobuf.ExtensionRegistryLite extensionRegistry)
استاتیک GPUOptions.Experimental	parseFrom (داده های ByteBuffer)
استاتیک GPUOptions.Experimental	parseFrom (ورودی com.google.protobuf.CodedInputStream، com.google.protobuf.ExtensionRegistryLite extensionRegistry)
استاتیک GPUOptions.Experimental	parseFrom (داده‌های ByteBuffer، com.google.protobuf.ExtensionRegistryLite extensionRegistry)
استاتیک GPUOptions.Experimental	parseFrom (ورودی com.google.protobuf.CodedInputStream)
استاتیک GPUOptions.Experimental	parseFrom (بایت[] داده، com.google.protobuf.ExtensionRegistryLite extensionRegistry)
استاتیک GPUOptions.Experimental	parseFrom (داده های com.google.protobuf.ByteString)
استاتیک GPUOptions.Experimental	parseFrom (ورودی InputStream، com.google.protobuf.ExtensionRegistryLite extensionRegistry)
استاتیک GPUOptions.Experimental	parseFrom (داده‌های com.google.protobuf.ByteString، com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ایستا	تجزیه کننده ()
GPUOptions.Experimental.Builder	toBuilder ()
خالی	writeTo (خروجی com.google.protobuf.CodedOutputStream)

روش های ارثی

از کلاس java.lang.Object

بولی	برابر است (شیء arg0)
کلاس نهایی<?>	getClass ()
بین المللی	هش کد ()
باطل نهایی	اعلام کردن ()
باطل نهایی	اطلاع رسانی به همه ()
رشته	toString ()
باطل نهایی	صبر کنید (long arg0، int arg1)
باطل نهایی	صبر کنید (طولانی arg0)
باطل نهایی	صبر کن ()

از رابط org.tensorflow.proto.framework.GPUOptions.ExperimentalOrBuilder

رشته انتزاعی	getCollectiveRingOrder () If non-empty, defines a good GPU ring order on a single worker based on device interconnect.
چکیده com.google.protobuf.ByteString	getCollectiveRingOrderBytes () If non-empty, defines a good GPU ring order on a single worker based on device interconnect.
انتزاعی	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.
انتزاعی	getKernelTrackerMaxInterval () Parameters for GPUKernelTracker.
انتزاعی	getKernelTrackerMaxPending () If kernel_tracker_max_pending > 0 then no more than this many tracking events can be outstanding at a time.
انتزاعی	getNumDevToDevCopyStreams () If > 1, the number of device-to-device copy streams to create for each GPUDevice.
بولی انتزاعی	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.
بولی انتزاعی	getUseUnifiedMemory () If true, uses CUDA unified memory for memory allocations.
انتزاعی GPUOptions.Experimental.VirtualDevices	getVirtualDevices (Int index) The multi virtual device settings.
انتزاعی	getVirtualDevicesCount () The multi virtual device settings.
فهرست انتزاعی< GPUOptions.Experimental.VirtualDevices >	getVirtualDevicesList () The multi virtual device settings.
انتزاعی GPUOptions.Experimental.VirtualDevicesOrBuilder	getVirtualDevicesOrBuilder (int index) The multi virtual device settings.
فهرست چکیده <? GPUOptions.Experimental.VirtualDevicesOrBuilder > را گسترش می دهد	getVirtualDevicesOrBuilderList () The multi virtual device settings.

ثابت ها

نهایی استاتیک عمومی COLLECTIVE_RING_ORDER_FIELD_NUMBER

ارزش ثابت: 4

نهایی استاتیک عمومی KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER

مقدار ثابت: 8

نهایی استاتیک عمومی KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER

ارزش ثابت: 7

نهایی استاتیک عمومی KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER

مقدار ثابت: 9

نهایی استاتیک عمومی NUM_DEV_TO_DEV_COPY_STREAMS_FIELD_NUMBER

مقدار ثابت: 3

نهایی استاتیک عمومی TIMESTAMPED_ALLOCATOR_FIELD_NUMBER

ارزش ثابت: 5

ورودی نهایی ثابت عمومی USE_UNIFIED_MEMORY_FIELD_NUMBER

مقدار ثابت: 2

VIRTUAL_DEVICES_FIELD_NUMBER نهایی استاتیک عمومی

ارزش ثابت: 1

روش های عمومی

بولین عمومی برابر است (Object Obj)

رشته عمومی 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;

عمومی com.google.protobuf.ByteString getCollectiveRingOrderBytes ()

رشته

 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;

عمومی استاتیک GPUOptions.Experimental getDefaultInstance ()

عمومی GPUOptions.Experimental getDefaultInstanceForType ()

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

عمومی 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;

عمومی 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;

عمومی 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;

عمومی 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;

عمومی getParserForType ()

عمومی int getSerializedSize ()

بولی عمومی 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;

عمومی نهایی com.google.protobuf.UnknownFieldSet getUnknownFields ()

بولی عمومی 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;

عمومی GPUOptions.Experimental.VirtualDevices getVirtualDevices (int index)

 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;

عمومی 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;

فهرست عمومی < 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;

عمومی GPUOptions.Experimental.VirtualDevicesOrBuilder getVirtualDevicesOrBuilder (int index)

 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;

لیست عمومی<? گسترش 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;

هش کد عمومی ()

بولین نهایی عمومی isInitialized ()

عمومی استاتیک GPUOptions.Experimental.Builder newBuilder ( GPUOptions.Experimental prototype)

عمومی استاتیک GPUOptions.Experimental.Builder newBuilder ()

عمومی GPUOptions.Experimental.Builder newBuilderForType ()

عمومی استاتیک GPUOptions.Experimental parseDelimitedFrom (ورودی InputStream)

پرتاب می کند

IOException

عمومی استاتیک GPUOptions.Experimental parseDelimitedFrom (ورودی InputStream، com.google.protobuf.ExtensionRegistryLite extensionRegistry)

پرتاب می کند

IOException

عمومی استاتیک GPUOptions.Experimental parseFrom (داده ByteBuffer)

پرتاب می کند

InvalidProtocolBufferException

عمومی استاتیک GPUOptions.Experimental parseFrom (ورودی com.google.protobuf.CodedInputStream، com.google.protobuf.ExtensionRegistryLite extensionRegistry)

پرتاب می کند

IOException

عمومی استاتیک GPUOptions.Experimental parseFrom (داده های ByteBuffer، com.google.protobuf.ExtensionRegistryLite extensionRegistry)

پرتاب می کند

InvalidProtocolBufferException

عمومی استاتیک GPUOptions.Experimental parseFrom (ورودی com.google.protobuf.CodedInputStream)

پرتاب می کند

IOException

عمومی استاتیک GPUOptions.Experimental parseFrom (بایت[] داده، com.google.protobuf.ExtensionRegistryLite extensionRegistry)

پرتاب می کند

InvalidProtocolBufferException

عمومی استاتیک GPUOptions.Experimental parseFrom (داده های com.google.protobuf.ByteString)

پرتاب می کند

InvalidProtocolBufferException

عمومی استاتیک GPUOptions.Experimental parseFrom (ورودی InputStream، com.google.protobuf.ExtensionRegistryLite extensionRegistry)

پرتاب می کند

IOException

عمومی استاتیک GPUOptions.Experimental parseFrom (داده های com.google.protobuf.ByteString، com.google.protobuf.ExtensionRegistryLite extensionRegistry)

پرتاب می کند

InvalidProtocolBufferException

استاتیک عمومی تجزیه کننده ()

عمومی GPUOptions.Experimental.Builder toBuilder ()

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

پرتاب می کند

IOException