GPUOptions.Experimental

GPUOptions.Experimental الطبقة النهائية العامة الثابتة

نوع Protobuf tensorflow.GPUOptions.Experimental

فئات متداخلة

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

الثوابت

كثافة العمليات COLLECTIVE_RING_ORDER_FIELD_NUMBER
كثافة العمليات KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER
كثافة العمليات KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER
كثافة العمليات KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER
كثافة العمليات NUM_DEV_TO_DEV_COPY_STREAMS_FIELD_NUMBER
كثافة العمليات TIMESTAMPED_ALLOCATOR_FIELD_NUMBER
كثافة العمليات USE_UNIFIED_MEMORY_FIELD_NUMBER
كثافة العمليات VIRTUAL_DEVICES_FIELD_NUMBER

الأساليب العامة

منطقية
يساوي (كائن كائن)
خيط
الحصول علىCollectiveRingOrder () 
 If non-empty, defines a good GPU ring order on a single worker based on
 device interconnect.
com.google.protobuf.ByteString
الحصول علىCollectiveRingOrderBytes () 
 If non-empty, defines a good GPU ring order on a single worker based on
 device interconnect.
خيارات GPU ثابتة.تجريبية
الحصول على المثيل الافتراضي ()
GPUOptions.التجريبية
getDefaultInstanceForType ()
النهائي الثابت com.google.protobuf.Descriptors.Descriptor
الحصول على واصف ()
كثافة العمليات
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.
كثافة العمليات
getKernelTrackerMaxInterval () 
 Parameters for GPUKernelTracker.
كثافة العمليات
getKernelTrackerMaxPending () 
 If kernel_tracker_max_pending > 0 then no more than this many
 tracking events can be outstanding at a time.
كثافة العمليات
getNumDevToDevCopyStreams () 
 If > 1, the number of device-to-device copy streams to create
 for each GPUDevice.
الحصول على بارسيرفورتايب ()
كثافة العمليات
الحصول علىSerializedSize ()
منطقية
الحصول على TimestampedAllocator () 
 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.
النهائي com.google.protobuf.UnknownFieldSet
الحصول على الحقول غير المعروفة ()
منطقية
الحصول علىUseUnifiedMemory () 
 If true, uses CUDA unified memory for memory allocations.
GPUOptions.Experimental.VirtualDevices
getVirtualDevices (فهرس كثافة العمليات) 
 The multi virtual device settings.
كثافة العمليات
الحصول على VirtualDevicesCount () 
 The multi virtual device settings.
القائمة< GPUOptions.Experimental.VirtualDevices >
قائمة الأجهزة الافتراضية () 
 The multi virtual device settings.
GPUOptions.Experimental.VirtualDevicesOrBuilder
getVirtualDevicesOrBuilder (فهرس كثافة العمليات) 
 The multi virtual device settings.
القائمة<؟ يمتد GPUOptions.Experimental.VirtualDevicesOrBuilder >
getVirtualDevicesOrBuilderList () 
 The multi virtual device settings.
كثافة العمليات
رمز التجزئة ()
منطقية نهائية
تمت التهيئة ()
GPUOptions.Experimental.Builder
newBuilder (نموذج GPUOptions. التجريبي )
GPUOptions.Experimental.Builder
منشئ جديد ()
GPUOptions.Experimental.Builder
نيوبيلديرفورتايب ()
خيارات GPU ثابتة.تجريبية
parseDelimitedFrom (إدخال InputStream)
خيارات GPU ثابتة.تجريبية
parseDelimitedFrom (إدخال InputStream، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
خيارات GPU ثابتة.تجريبية
parseFrom (بيانات ByteBuffer)
خيارات GPU ثابتة.تجريبية
parseFrom (com.google.protobuf.CodedInputStream input، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
خيارات GPU ثابتة.تجريبية
parseFrom (بيانات ByteBuffer، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
خيارات GPU ثابتة.تجريبية
parseFrom (com.google.protobuf.CodedInputStream الإدخال)
خيارات GPU ثابتة.تجريبية
parseFrom (بيانات البايت[]، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
خيارات GPU ثابتة.تجريبية
parseFrom (بيانات com.google.protobuf.ByteString)
خيارات GPU ثابتة.تجريبية
parseFrom (إدخال InputStream، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
خيارات GPU ثابتة.تجريبية
parseFrom (com.google.protobuf.ByteString data، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
ثابت
محلل ()
GPUOptions.Experimental.Builder
إلى البناء ()
فارغ
writeTo (com.google.protobuf.CodedOutputStream الإخراج)

الطرق الموروثة

الثوابت

العدد النهائي الثابت العام COLLECTIVE_RING_ORDER_FIELD_NUMBER

القيمة الثابتة: 4

العدد النهائي الثابت العام KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER

القيمة الثابتة: 8

العدد النهائي الثابت العام KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER

القيمة الثابتة: 7

العدد النهائي الثابت العام KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER

القيمة الثابتة: 9

العدد النهائي الثابت العام NUM_DEV_TO_DEV_COPY_STREAMS_FIELD_NUMBER

القيمة الثابتة: 3

العدد النهائي الثابت العام TIMESTAMPED_ALLOCATOR_FIELD_NUMBER

القيمة الثابتة: 5

العدد النهائي الثابت العام USE_UNIFIED_MEMORY_FIELD_NUMBER

القيمة الثابتة: 2

العدد النهائي الثابت العام VIRTUAL_DEVICES_FIELD_NUMBER

القيمة الثابتة: 1

الأساليب العامة

القيمة المنطقية العامة تساوي (Object obj)

سلسلة عامة 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;

com.google.protobuf.ByteString العامة 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;

GPUOptions العامة الثابتة. getDefaultInstance التجريبية ()

GPUOptions العامة. getDefaultInstanceForType () التجريبية

النهائي العام الثابت com.google.protobuf.Descriptors.Descriptor getDescriptor ()

int العام 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;

int public 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;

int العام 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;

int العام 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;

عام الحصول على بارسيرفورتايب ()

int public getSerializedSize ()

getTimestampedAllocator () المنطقي العام 

 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;

النهائي العام com.google.protobuf.UnknownFieldSet getUnknownFields ()

getUseUnifiedMemory () المنطقية العامة 

 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;

GPUOptions.Experimental.VirtualDevices العامة getVirtualDevices (مؤشر int) 

 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;

int public 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;

القائمة العامة< 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;

GPUOptions.Experimental.VirtualDevicesOrBuilder العام getVirtualDevicesOrBuilder (فهرس كثافة العمليات) 

 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;

القائمة العامة <؟ يمتد 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;

كود التجزئة الدولي العام ()

تمت تهيئة القيمة المنطقية النهائية العامة ()

GPUOptions.Experimental.Builder newBuilder العام الثابت ( GPUOptions. النموذج التجريبي)

GPUOptions العامة الثابتة.Experimental.Builder newBuilder ()

GPUOptions.Experimental.Builder newBuilderForType () العامة

GPUOptions العامة الثابتة. التحليل التجريبيDelimitedFrom (إدخال InputStream)

رميات
IOEException

GPUOptions العامة الثابتة. التحليل التجريبي DelimitedFrom (إدخال InputStream، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

رميات
IOEException

GPUOptions العامة الثابتة. التحليل التجريبي من (بيانات ByteBuffer)

رميات
InvalidProtocolBufferException

GPUOptions العامة الثابتة. التحليل التجريبي من (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

رميات
IOEException

GPUOptions العامة الثابتة. التحليل التجريبي من (بيانات ByteBuffer، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

رميات
InvalidProtocolBufferException

GPUOptions العامة الثابتة. التحليل التجريبي من (com.google.protobuf.CodedInputStream input)

رميات
IOEException

GPUOptions العامة الثابتة. التحليل التجريبي من (بيانات البايت []، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

رميات
InvalidProtocolBufferException

GPUOptions العامة الثابتة. التحليل التجريبي من (بيانات com.google.protobuf.ByteString)

رميات
InvalidProtocolBufferException

GPUOptions العامة الثابتة. التحليل التجريبي من (InputStream input، com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

رميات
IOEException

GPUOptions العامة الثابتة. التحليل التجريبي من (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

رميات
InvalidProtocolBufferException

ساكنة عامة محلل ()

GPUOptions.Experimental.Builder toBuilder () العامة

الكتابة إلى الفراغ العام (إخراج com.google.protobuf.CodedOutputStream)

رميات
IOEException