GPUOptions de clase final estática pública .
Protobuf tipo tensorflow.GPUOptions.Experimental
Clases anidadas
clase | GPUOptions.Experimental.Builder | Protobuf tipo tensorflow.GPUOptions.Experimental | |
clase | GPUOptions.Experimental.VirtualDevices | Configuration for breaking down a visible GPU into multiple "virtual" devices. | |
interfaz | GPUOptions.Experimental.VirtualDevicesOrBuilder |
Constantes
Métodos públicos
booleano | es igual a (Objeto obj) |
Cuerda | 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 estáticas.Experimental | |
GPUOptions.Experimental | |
com.google.protobuf.Descriptors.Descriptor estático final | |
En t | 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. |
En t | getKernelTrackerMaxInterval () Parameters for GPUKernelTracker. |
En t | getKernelTrackerMaxPending () If kernel_tracker_max_pending > 0 then no more than this many tracking events can be outstanding at a time. |
En t | getNumDevToDevCopyStreams () If > 1, the number of device-to-device copy streams to create for each GPUDevice. |
En t | |
booleano | 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. |
final com.google.protobuf.UnknownFieldSet | |
booleano | getUseUnifiedMemory () If true, uses CUDA unified memory for memory allocations. |
GPUOptions.Experimental.VirtualDevices | getVirtualDevices (índice int) The multi virtual device settings. |
En t | getVirtualDevicesCount () The multi virtual device settings. |
Lista < GPUOptions.Experimental.VirtualDevices > | getVirtualDevicesList () The multi virtual device settings. |
GPUOptions.Experimental.VirtualDevicesOrBuilder | getVirtualDevicesOrBuilder (índice int) The multi virtual device settings. |
Lista <? extiende GPUOptions.Experimental.VirtualDevicesOrBuilder > | getVirtualDevicesOrBuilderList () The multi virtual device settings. |
En t | hashCode () |
booleano final | |
static GPUOptions.Experimental.Builder | newBuilder ( GPUOptions.Experimental prototype) |
static GPUOptions.Experimental.Builder | newBuilder () |
GPUOptions.Experimental.Builder | |
GPUOptions estáticas.Experimental | parseDelimitedFrom (entrada InputStream) |
GPUOptions estáticas.Experimental | parseDelimitedFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
GPUOptions estáticas.Experimental | parseFrom (datos ByteBuffer) |
GPUOptions estáticas.Experimental | parseFrom (entrada com.google.protobuf.CodedInputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
GPUOptions estáticas.Experimental | parseFrom (datos ByteBuffer, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
GPUOptions estáticas.Experimental | parseFrom (entrada com.google.protobuf.CodedInputStream) |
GPUOptions estáticas.Experimental | parseFrom (byte [] datos, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
GPUOptions estáticas.Experimental | parseFrom (datos com.google.protobuf.ByteString) |
GPUOptions estáticas.Experimental | parseFrom (entrada InputStream, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
GPUOptions estáticas.Experimental | parseFrom (datos com.google.protobuf.ByteString, com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
estático | analizador () |
GPUOptions.Experimental.Builder | toBuilder () |
vacío | writeTo (salida de com.google.protobuf.CodedOutputStream) |
Métodos heredados
Constantes
public static final int COLLECTIVE_RING_ORDER_FIELD_NUMBER
Valor constante: 4
público estático final int KERNEL_TRACKER_MAX_BYTES_FIELD_NUMBER
Valor constante: 8
público estático final int KERNEL_TRACKER_MAX_INTERVAL_FIELD_NUMBER
Valor constante: 7
público estático final int KERNEL_TRACKER_MAX_PENDING_FIELD_NUMBER
Valor constante: 9
public static final int NUM_DEV_TO_DEV_COPY_STREAMS_FIELD_NUMBER
Valor constante: 3
public static final int TIMESTAMPED_ALLOCATOR_FIELD_NUMBER
Valor constante: 5
público estático final int USE_UNIFIED_MEMORY_FIELD_NUMBER
Valor constante: 2
public static final int VIRTUAL_DEVICES_FIELD_NUMBER
Valor constante: 1
Métodos públicos
public boolean es igual a (Object obj)
public 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;
Collective_ring_order 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;
Collective_ring_order string collective_ring_order = 4;
público estático 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;
público 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 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;
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;
Lista pública < 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 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;
Lista pública <? extiende 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 ()
public final boolean isInitialized ()
public static GPUOptions.Experimental parseDelimitedFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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GPUOptions.Experimental estática pública GPUOptions.Experimental parseFrom (ByteBuffer datos)
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public static GPUOptions.Experimental parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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public static GPUOptions.Experimental parseFrom (ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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public static GPUOptions.Experimental parseFrom (entrada com.google.protobuf.CodedInputStream)
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public static GPUOptions.Experimental parseFrom (byte [] datos, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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public static GPUOptions.Experimental parseFrom (com.google.protobuf.ByteString data)
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public static GPUOptions.Experimental parseFrom (InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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public static GPUOptions.Experimental parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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público estático analizador ()
public void writeTo (salida de com.google.protobuf.CodedOutputStream)
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