Package org.tensorflow.framework
Class GPUOptions.Experimental.Builder
- java.lang.Object
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- org.nd4j.shade.protobuf.AbstractMessageLite.Builder
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- org.nd4j.shade.protobuf.AbstractMessage.Builder<BuilderType>
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- org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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- org.tensorflow.framework.GPUOptions.Experimental.Builder
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- All Implemented Interfaces:
Cloneable,org.nd4j.shade.protobuf.Message.Builder,org.nd4j.shade.protobuf.MessageLite.Builder,org.nd4j.shade.protobuf.MessageLiteOrBuilder,org.nd4j.shade.protobuf.MessageOrBuilder,GPUOptions.ExperimentalOrBuilder
- Enclosing class:
- GPUOptions.Experimental
public static final class GPUOptions.Experimental.Builder extends org.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder> implements GPUOptions.ExperimentalOrBuilder
Protobuf typetensorflow.GPUOptions.Experimental
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Method Summary
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Methods inherited from class org.nd4j.shade.protobuf.GeneratedMessageV3.Builder
getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof, internalGetMapField, internalGetMutableMapField, isClean, markClean, newBuilderForField, onBuilt, onChanged, setUnknownFieldsProto3
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Methods inherited from class org.nd4j.shade.protobuf.AbstractMessage.Builder
findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString
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Methods inherited from class org.nd4j.shade.protobuf.AbstractMessageLite.Builder
addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, newUninitializedMessageException
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Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
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Method Detail
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getDescriptor
public static final org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptor()
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internalGetFieldAccessorTable
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
- Specified by:
internalGetFieldAccessorTablein classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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clear
public GPUOptions.Experimental.Builder clear()
- Specified by:
clearin interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
clearin interfaceorg.nd4j.shade.protobuf.MessageLite.Builder- Overrides:
clearin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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getDescriptorForType
public org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptorForType()
- Specified by:
getDescriptorForTypein interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
getDescriptorForTypein interfaceorg.nd4j.shade.protobuf.MessageOrBuilder- Overrides:
getDescriptorForTypein classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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getDefaultInstanceForType
public GPUOptions.Experimental getDefaultInstanceForType()
- Specified by:
getDefaultInstanceForTypein interfaceorg.nd4j.shade.protobuf.MessageLiteOrBuilder- Specified by:
getDefaultInstanceForTypein interfaceorg.nd4j.shade.protobuf.MessageOrBuilder
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build
public GPUOptions.Experimental build()
- Specified by:
buildin interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
buildin interfaceorg.nd4j.shade.protobuf.MessageLite.Builder
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buildPartial
public GPUOptions.Experimental buildPartial()
- Specified by:
buildPartialin interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
buildPartialin interfaceorg.nd4j.shade.protobuf.MessageLite.Builder
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clone
public GPUOptions.Experimental.Builder clone()
- Specified by:
clonein interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
clonein interfaceorg.nd4j.shade.protobuf.MessageLite.Builder- Overrides:
clonein classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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setField
public GPUOptions.Experimental.Builder setField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)
- Specified by:
setFieldin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
setFieldin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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clearField
public GPUOptions.Experimental.Builder clearField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field)
- Specified by:
clearFieldin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
clearFieldin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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clearOneof
public GPUOptions.Experimental.Builder clearOneof(org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof)
- Specified by:
clearOneofin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
clearOneofin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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setRepeatedField
public GPUOptions.Experimental.Builder setRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
- Specified by:
setRepeatedFieldin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
setRepeatedFieldin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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addRepeatedField
public GPUOptions.Experimental.Builder addRepeatedField(org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field, Object value)
- Specified by:
addRepeatedFieldin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
addRepeatedFieldin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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mergeFrom
public GPUOptions.Experimental.Builder mergeFrom(org.nd4j.shade.protobuf.Message other)
- Specified by:
mergeFromin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
mergeFromin classorg.nd4j.shade.protobuf.AbstractMessage.Builder<GPUOptions.Experimental.Builder>
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mergeFrom
public GPUOptions.Experimental.Builder mergeFrom(GPUOptions.Experimental other)
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isInitialized
public final boolean isInitialized()
- Specified by:
isInitializedin interfaceorg.nd4j.shade.protobuf.MessageLiteOrBuilder- Overrides:
isInitializedin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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mergeFrom
public GPUOptions.Experimental.Builder mergeFrom(org.nd4j.shade.protobuf.CodedInputStream input, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
- Specified by:
mergeFromin interfaceorg.nd4j.shade.protobuf.Message.Builder- Specified by:
mergeFromin interfaceorg.nd4j.shade.protobuf.MessageLite.Builder- Overrides:
mergeFromin classorg.nd4j.shade.protobuf.AbstractMessage.Builder<GPUOptions.Experimental.Builder>- Throws:
IOException
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getVirtualDevicesList
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;- Specified by:
getVirtualDevicesListin interfaceGPUOptions.ExperimentalOrBuilder
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getVirtualDevicesCount
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;- Specified by:
getVirtualDevicesCountin interfaceGPUOptions.ExperimentalOrBuilder
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getVirtualDevices
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;- Specified by:
getVirtualDevicesin interfaceGPUOptions.ExperimentalOrBuilder
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setVirtualDevices
public GPUOptions.Experimental.Builder setVirtualDevices(int index, GPUOptions.Experimental.VirtualDevices value)
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;
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setVirtualDevices
public GPUOptions.Experimental.Builder setVirtualDevices(int index, GPUOptions.Experimental.VirtualDevices.Builder builderForValue)
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;
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addVirtualDevices
public GPUOptions.Experimental.Builder addVirtualDevices(GPUOptions.Experimental.VirtualDevices value)
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;
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addVirtualDevices
public GPUOptions.Experimental.Builder addVirtualDevices(int index, GPUOptions.Experimental.VirtualDevices value)
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;
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addVirtualDevices
public GPUOptions.Experimental.Builder addVirtualDevices(GPUOptions.Experimental.VirtualDevices.Builder builderForValue)
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;
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addVirtualDevices
public GPUOptions.Experimental.Builder addVirtualDevices(int index, GPUOptions.Experimental.VirtualDevices.Builder builderForValue)
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;
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addAllVirtualDevices
public GPUOptions.Experimental.Builder addAllVirtualDevices(Iterable<? extends GPUOptions.Experimental.VirtualDevices> values)
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;
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clearVirtualDevices
public GPUOptions.Experimental.Builder clearVirtualDevices()
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;
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removeVirtualDevices
public GPUOptions.Experimental.Builder removeVirtualDevices(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;
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getVirtualDevicesBuilder
public GPUOptions.Experimental.VirtualDevices.Builder getVirtualDevicesBuilder(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;
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getVirtualDevicesOrBuilder
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;- Specified by:
getVirtualDevicesOrBuilderin interfaceGPUOptions.ExperimentalOrBuilder
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getVirtualDevicesOrBuilderList
public List<? 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;- Specified by:
getVirtualDevicesOrBuilderListin interfaceGPUOptions.ExperimentalOrBuilder
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addVirtualDevicesBuilder
public GPUOptions.Experimental.VirtualDevices.Builder addVirtualDevicesBuilder()
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;
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addVirtualDevicesBuilder
public GPUOptions.Experimental.VirtualDevices.Builder addVirtualDevicesBuilder(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;
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getVirtualDevicesBuilderList
public List<GPUOptions.Experimental.VirtualDevices.Builder> getVirtualDevicesBuilderList()
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;
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getUseUnifiedMemory
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;- Specified by:
getUseUnifiedMemoryin interfaceGPUOptions.ExperimentalOrBuilder- Returns:
- The useUnifiedMemory.
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setUseUnifiedMemory
public GPUOptions.Experimental.Builder setUseUnifiedMemory(boolean value)
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;- Parameters:
value- The useUnifiedMemory to set.- Returns:
- This builder for chaining.
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clearUseUnifiedMemory
public GPUOptions.Experimental.Builder clearUseUnifiedMemory()
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;- Returns:
- This builder for chaining.
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setUnknownFields
public final GPUOptions.Experimental.Builder setUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)
- Specified by:
setUnknownFieldsin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
setUnknownFieldsin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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mergeUnknownFields
public final GPUOptions.Experimental.Builder mergeUnknownFields(org.nd4j.shade.protobuf.UnknownFieldSet unknownFields)
- Specified by:
mergeUnknownFieldsin interfaceorg.nd4j.shade.protobuf.Message.Builder- Overrides:
mergeUnknownFieldsin classorg.nd4j.shade.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>
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