GPUOptions.Experimental

lớp cuối cùng tĩnh công khai GPUOptions.Experimental

Protobuf loại tensorflow.GPUOptions.Experimental

Các lớp lồng nhau

lớp học GPUOptions.Experimental.Builder Protobuf loại tensorflow.GPUOptions.Experimental
lớp học GPUOptions.Experimental.VirtualDevices
 Configuration for breaking down a visible GPU into multiple "virtual"
 devices. 
giao diện GPUOptions.Experimental.VirtualDevicesOrBuilder

Hằng số

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

Phương pháp công cộng

boolean
bằng (Đối tượng obj)
Sợi dây
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.
GPUOptions.Experimental tĩnh
GPUOptions.Experimental
com.google.protobuf.Descriptors.Descriptor tĩnh cuối cùng
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.
int
getKernelTrackerMaxInterval ()
 Parameters for GPUKernelTracker.
int
getKernelTrackerMaxPending ()
 If kernel_tracker_max_pending > 0 then no more than this many
 tracking events can be outstanding at a time.
int
getNumDevToDevCopyStreams ()
 If > 1, the number of device-to-device copy streams to create
 for each GPUDevice.
int
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.
com.google.protobuf.UnknownFieldSet cuối cùng
boolean
getUseUnifiedMemory ()
 If true, uses CUDA unified memory for memory allocations.
GPUOptions.Experimental.VirtualDevices
getVirtualDevices (chỉ mục int)
 The multi virtual device settings.
int
getVirtualDevicesCount ()
 The multi virtual device settings.
Danh sách< GPUOptions.Experimental.VirtualDevices >
getVirtualDevicesList ()
 The multi virtual device settings.
GPUOptions.Experimental.VirtualDevicesOrBuilder
getVirtualDevicesOrBuilder (chỉ mục int)
 The multi virtual device settings.
Danh sách<? mở rộng GPUOptions.Experimental.VirtualDevicesOrBuilder >
getVirtualDevicesOrBuilderList ()
 The multi virtual device settings.
int
boolean cuối cùng
GPUOptions.Experimental.Builder tĩnh
GPUOptions.Experimental.Builder tĩnh
GPUOptions.Experimental.Builder
GPUOptions.Experimental tĩnh
phân tích cú phápDelimitedFrom (Đầu vào luồng đầu vào)
GPUOptions.Experimental tĩnh
phân tích cú phápDelimitedFrom (Đầu vào luồng đầu vào, com.google.protobuf.ExtensionRegistryLite tiện ích mở rộngRegistry)
GPUOptions.Experimental tĩnh
ParseFrom (dữ liệu ByteBuffer)
GPUOptions.Experimental tĩnh
ParseFrom (đầu vào com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
GPUOptions.Experimental tĩnh
ParseFrom (Dữ liệu ByteBuffer, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
GPUOptions.Experimental tĩnh
ParseFrom (đầu vào com.google.protobuf.CodedInputStream)
GPUOptions.Experimental tĩnh
ParseFrom (dữ liệu byte[], com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
GPUOptions.Experimental tĩnh
ParseFrom (dữ liệu com.google.protobuf.ByteString)
GPUOptions.Experimental tĩnh
ParseFrom (Đầu vào inputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
GPUOptions.Experimental tĩnh
ParseFrom (dữ liệu com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)
tĩnh
GPUOptions.Experimental.Builder
trống rỗng
writeTo (đầu ra com.google.protobuf.CodedOutputStream)

Phương pháp kế thừa

Hằng số

int tĩnh cuối cùng COLLECTIVE_RING_ORDER_FIELD_NUMBER

Giá trị không đổi: 4

int tĩnh công khai KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER

Giá trị không đổi: 8

int tĩnh công khai KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER

Giá trị không đổi: 7

int cuối cùng tĩnh công khai KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER

Giá trị không đổi: 9

int cuối cùng tĩnh công khai NUM_DEV_TO_DEV_COPY_STREAMS_FIELD_NUMBER

Giá trị không đổi: 3

int cuối cùng tĩnh công khai TIMESTAMPED_ALLOCATOR_FIELD_NUMBER

Giá trị không đổi: 5

int tĩnh cuối cùng USE_UNIFIED_MEMORY_FIELD_NUMBER

Giá trị không đổi: 2

int tĩnh cuối cùng VIRTUAL_DEVICES_FIELD_NUMBER

Giá trị không đổi: 1

Phương pháp công cộng

boolean công khai bằng (Object obj)

Chuỗi công khai 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 công khai 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 tĩnh công khai.Experimental getDefaultInstance ()

GPUOptions công khai.Experimental getDefaultInstanceForType ()

công khai tĩnh cuối cùng com.google.protobuf.Descriptors.Descriptor getDescriptor ()

int công khai 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 công khai 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 công khai 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 công khai 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;

công cộng getParserForType ()

int công khai getSerializedSize ()

boolean công khai 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;

trận chung kết công khai com.google.protobuf.UnknownFieldSet getUnknownFields ()

boolean công khai 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;

công khai GPUOptions.Experimental.VirtualDevices getVirtualDevices (chỉ mục 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 công khai 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;

Danh sách công khai< 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;

công khai GPUOptions.Experimental.VirtualDevicesOrBuilder getVirtualDevicesOrBuilder (chỉ mục 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;

Danh sách công khai<? mở rộng 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;

mã băm int công khai ()

boolean cuối cùng công khai được khởi tạo ()

GPUOptions.Experimental.Builder newBuilder tĩnh công khai ( nguyên mẫu GPUOptions.Experimental )

GPUOptions.Experimental.Builder tĩnh công khai newBuilder ()

công khai GPUOptions.Experimental.Builder newBuilderForType ()

GPUOptions tĩnh công khai.Experimental parsingDelimitedFrom (Đầu vào luồng đầu vào)

Ném
IOException

GPUOptions tĩnh công khai.Experimental parsingDelimitedFrom (Đầu vào InputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Ném
IOException

GPUOptions tĩnh công khai.Experimental parsFrom (dữ liệu ByteBuffer)

Ném
Giao thức đệm ngoại lệ không hợp lệ

GPUOptions tĩnh công khai.Experimental parsFrom (đầu vào com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Ném
IOException

GPUOptions tĩnh công khai.Experimental parsFrom (Dữ liệu ByteBuffer, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Ném
Giao thức đệm ngoại lệ không hợp lệ

GPUOptions tĩnh công khai.Experimental parsFrom (đầu vào com.google.protobuf.CodedInputStream)

Ném
IOException

GPUOptions tĩnh công khai.Experimental parsFrom (dữ liệu byte[], com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Ném
Giao thức đệm ngoại lệ không hợp lệ

GPUOptions tĩnh công khai.Experimental parsFrom (dữ liệu com.google.protobuf.ByteString)

Ném
Giao thức đệm ngoại lệ không hợp lệ

GPUOptions tĩnh công khai.Experimental parsFrom (Đầu vào inputStream, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Ném
IOException

GPUOptions tĩnh công khai.Experimental parsFrom (dữ liệu com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite ExtensionRegistry)

Ném
Giao thức đệm ngoại lệ không hợp lệ

công cộng tĩnh trình phân tích cú pháp ()

GPUOptions.Experimental.Builder toBuilder công khai ()

public void writeTo (đầu ra com.google.protobuf.CodedOutputStream)

Ném
IOException