public static final class GPUOptions.Experimental.Builder extends com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder> implements GPUOptions.ExperimentalOrBuilder
tensorflow.GPUOptions.Experimental| Modifier and Type | Method and Description |
|---|---|
GPUOptions.Experimental.Builder |
addAllVirtualDevices(java.lang.Iterable<? extends GPUOptions.Experimental.VirtualDevices> values)
The multi virtual device settings.
|
GPUOptions.Experimental.Builder |
addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field,
java.lang.Object value) |
GPUOptions.Experimental.Builder |
addVirtualDevices(GPUOptions.Experimental.VirtualDevices.Builder builderForValue)
The multi virtual device settings.
|
GPUOptions.Experimental.Builder |
addVirtualDevices(GPUOptions.Experimental.VirtualDevices value)
The multi virtual device settings.
|
GPUOptions.Experimental.Builder |
addVirtualDevices(int index,
GPUOptions.Experimental.VirtualDevices.Builder builderForValue)
The multi virtual device settings.
|
GPUOptions.Experimental.Builder |
addVirtualDevices(int index,
GPUOptions.Experimental.VirtualDevices value)
The multi virtual device settings.
|
GPUOptions.Experimental.VirtualDevices.Builder |
addVirtualDevicesBuilder()
The multi virtual device settings.
|
GPUOptions.Experimental.VirtualDevices.Builder |
addVirtualDevicesBuilder(int index)
The multi virtual device settings.
|
GPUOptions.Experimental |
build() |
GPUOptions.Experimental |
buildPartial() |
GPUOptions.Experimental.Builder |
clear() |
GPUOptions.Experimental.Builder |
clearCollectiveRingOrder()
If non-empty, defines a good GPU ring order on a single worker based on
device interconnect.
|
GPUOptions.Experimental.Builder |
clearField(com.google.protobuf.Descriptors.FieldDescriptor field) |
GPUOptions.Experimental.Builder |
clearKernelTrackerMaxBytes()
If kernel_tracker_max_bytes = n > 0, then a tracking event is
inserted after every series of kernels allocating a sum of
memory >= n.
|
GPUOptions.Experimental.Builder |
clearKernelTrackerMaxInterval()
Parameters for GPUKernelTracker.
|
GPUOptions.Experimental.Builder |
clearKernelTrackerMaxPending()
If kernel_tracker_max_pending > 0 then no more than this many
tracking events can be outstanding at a time.
|
GPUOptions.Experimental.Builder |
clearNumDevToDevCopyStreams()
If > 1, the number of device-to-device copy streams to create
for each GPUDevice.
|
GPUOptions.Experimental.Builder |
clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) |
GPUOptions.Experimental.Builder |
clearTimestampedAllocator()
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.
|
GPUOptions.Experimental.Builder |
clearUseUnifiedMemory()
If true, uses CUDA unified memory for memory allocations.
|
GPUOptions.Experimental.Builder |
clearVirtualDevices()
The multi virtual device settings.
|
GPUOptions.Experimental.Builder |
clone() |
java.lang.String |
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 |
getDefaultInstanceForType() |
static com.google.protobuf.Descriptors.Descriptor |
getDescriptor() |
com.google.protobuf.Descriptors.Descriptor |
getDescriptorForType() |
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.
|
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.
|
boolean |
getUseUnifiedMemory()
If true, uses CUDA unified memory for memory allocations.
|
GPUOptions.Experimental.VirtualDevices |
getVirtualDevices(int index)
The multi virtual device settings.
|
GPUOptions.Experimental.VirtualDevices.Builder |
getVirtualDevicesBuilder(int index)
The multi virtual device settings.
|
java.util.List<GPUOptions.Experimental.VirtualDevices.Builder> |
getVirtualDevicesBuilderList()
The multi virtual device settings.
|
int |
getVirtualDevicesCount()
The multi virtual device settings.
|
java.util.List<GPUOptions.Experimental.VirtualDevices> |
getVirtualDevicesList()
The multi virtual device settings.
|
GPUOptions.Experimental.VirtualDevicesOrBuilder |
getVirtualDevicesOrBuilder(int index)
The multi virtual device settings.
|
java.util.List<? extends GPUOptions.Experimental.VirtualDevicesOrBuilder> |
getVirtualDevicesOrBuilderList()
The multi virtual device settings.
|
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable |
internalGetFieldAccessorTable() |
boolean |
isInitialized() |
GPUOptions.Experimental.Builder |
mergeFrom(com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
GPUOptions.Experimental.Builder |
mergeFrom(GPUOptions.Experimental other) |
GPUOptions.Experimental.Builder |
mergeFrom(com.google.protobuf.Message other) |
GPUOptions.Experimental.Builder |
mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) |
GPUOptions.Experimental.Builder |
removeVirtualDevices(int index)
The multi virtual device settings.
|
GPUOptions.Experimental.Builder |
setCollectiveRingOrder(java.lang.String value)
If non-empty, defines a good GPU ring order on a single worker based on
device interconnect.
|
GPUOptions.Experimental.Builder |
setCollectiveRingOrderBytes(com.google.protobuf.ByteString value)
If non-empty, defines a good GPU ring order on a single worker based on
device interconnect.
|
GPUOptions.Experimental.Builder |
setField(com.google.protobuf.Descriptors.FieldDescriptor field,
java.lang.Object value) |
GPUOptions.Experimental.Builder |
setKernelTrackerMaxBytes(int value)
If kernel_tracker_max_bytes = n > 0, then a tracking event is
inserted after every series of kernels allocating a sum of
memory >= n.
|
GPUOptions.Experimental.Builder |
setKernelTrackerMaxInterval(int value)
Parameters for GPUKernelTracker.
|
GPUOptions.Experimental.Builder |
setKernelTrackerMaxPending(int value)
If kernel_tracker_max_pending > 0 then no more than this many
tracking events can be outstanding at a time.
|
GPUOptions.Experimental.Builder |
setNumDevToDevCopyStreams(int value)
If > 1, the number of device-to-device copy streams to create
for each GPUDevice.
|
GPUOptions.Experimental.Builder |
setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field,
int index,
java.lang.Object value) |
GPUOptions.Experimental.Builder |
setTimestampedAllocator(boolean value)
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.
|
GPUOptions.Experimental.Builder |
setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) |
GPUOptions.Experimental.Builder |
setUseUnifiedMemory(boolean value)
If true, uses CUDA unified memory for memory allocations.
|
GPUOptions.Experimental.Builder |
setVirtualDevices(int index,
GPUOptions.Experimental.VirtualDevices.Builder builderForValue)
The multi virtual device settings.
|
GPUOptions.Experimental.Builder |
setVirtualDevices(int index,
GPUOptions.Experimental.VirtualDevices value)
The multi virtual device settings.
|
getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof, internalGetMapField, internalGetMutableMapField, isClean, markClean, newBuilderForField, onBuilt, onChanged, setUnknownFieldsProto3findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringaddAll, addAll, mergeFrom, newUninitializedMessageExceptionequals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitpublic static final com.google.protobuf.Descriptors.Descriptor getDescriptor()
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>public GPUOptions.Experimental.Builder clear()
clear in interface com.google.protobuf.Message.Builderclear in interface com.google.protobuf.MessageLite.Builderclear in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
getDescriptorForType in interface com.google.protobuf.Message.BuildergetDescriptorForType in interface com.google.protobuf.MessageOrBuildergetDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>public GPUOptions.Experimental getDefaultInstanceForType()
getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuildergetDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilderpublic GPUOptions.Experimental build()
build in interface com.google.protobuf.Message.Builderbuild in interface com.google.protobuf.MessageLite.Builderpublic GPUOptions.Experimental buildPartial()
buildPartial in interface com.google.protobuf.Message.BuilderbuildPartial in interface com.google.protobuf.MessageLite.Builderpublic GPUOptions.Experimental.Builder clone()
clone in interface com.google.protobuf.Message.Builderclone in interface com.google.protobuf.MessageLite.Builderclone in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>public GPUOptions.Experimental.Builder setField(com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value)
setField in interface com.google.protobuf.Message.BuildersetField in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>public GPUOptions.Experimental.Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
clearField in interface com.google.protobuf.Message.BuilderclearField in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>public GPUOptions.Experimental.Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
clearOneof in interface com.google.protobuf.Message.BuilderclearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>public GPUOptions.Experimental.Builder setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, java.lang.Object value)
setRepeatedField in interface com.google.protobuf.Message.BuildersetRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>public GPUOptions.Experimental.Builder addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value)
addRepeatedField in interface com.google.protobuf.Message.BuilderaddRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>public GPUOptions.Experimental.Builder mergeFrom(com.google.protobuf.Message other)
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<GPUOptions.Experimental.Builder>public GPUOptions.Experimental.Builder mergeFrom(GPUOptions.Experimental other)
public final boolean isInitialized()
isInitialized in interface com.google.protobuf.MessageLiteOrBuilderisInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>public GPUOptions.Experimental.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws java.io.IOException
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in interface com.google.protobuf.MessageLite.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<GPUOptions.Experimental.Builder>java.io.IOExceptionpublic java.util.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;getVirtualDevicesList in interface GPUOptions.ExperimentalOrBuilderpublic 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;getVirtualDevicesCount in interface GPUOptions.ExperimentalOrBuilderpublic 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;getVirtualDevices in interface GPUOptions.ExperimentalOrBuilderpublic 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;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;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;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;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;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;public GPUOptions.Experimental.Builder addAllVirtualDevices(java.lang.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;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;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;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;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;getVirtualDevicesOrBuilder in interface GPUOptions.ExperimentalOrBuilderpublic java.util.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;getVirtualDevicesOrBuilderList in interface GPUOptions.ExperimentalOrBuilderpublic 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;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;public java.util.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;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;getUseUnifiedMemory in interface GPUOptions.ExperimentalOrBuilderpublic 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;value - The useUnifiedMemory to set.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;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;getNumDevToDevCopyStreams in interface GPUOptions.ExperimentalOrBuilderpublic GPUOptions.Experimental.Builder setNumDevToDevCopyStreams(int value)
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;value - The numDevToDevCopyStreams to set.public GPUOptions.Experimental.Builder clearNumDevToDevCopyStreams()
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;public java.lang.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;getCollectiveRingOrder in interface GPUOptions.ExperimentalOrBuilderpublic 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;getCollectiveRingOrderBytes in interface GPUOptions.ExperimentalOrBuilderpublic GPUOptions.Experimental.Builder setCollectiveRingOrder(java.lang.String value)
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;value - The collectiveRingOrder to set.public GPUOptions.Experimental.Builder clearCollectiveRingOrder()
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;public GPUOptions.Experimental.Builder setCollectiveRingOrderBytes(com.google.protobuf.ByteString value)
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;value - The bytes for collectiveRingOrder to set.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;getTimestampedAllocator in interface GPUOptions.ExperimentalOrBuilderpublic GPUOptions.Experimental.Builder setTimestampedAllocator(boolean value)
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;value - The timestampedAllocator to set.public GPUOptions.Experimental.Builder clearTimestampedAllocator()
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 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;getKernelTrackerMaxInterval in interface GPUOptions.ExperimentalOrBuilderpublic GPUOptions.Experimental.Builder setKernelTrackerMaxInterval(int value)
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;value - The kernelTrackerMaxInterval to set.public GPUOptions.Experimental.Builder clearKernelTrackerMaxInterval()
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 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;getKernelTrackerMaxBytes in interface GPUOptions.ExperimentalOrBuilderpublic GPUOptions.Experimental.Builder setKernelTrackerMaxBytes(int value)
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;value - The kernelTrackerMaxBytes to set.public GPUOptions.Experimental.Builder clearKernelTrackerMaxBytes()
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 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;getKernelTrackerMaxPending in interface GPUOptions.ExperimentalOrBuilderpublic GPUOptions.Experimental.Builder setKernelTrackerMaxPending(int value)
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;value - The kernelTrackerMaxPending to set.public GPUOptions.Experimental.Builder clearKernelTrackerMaxPending()
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 final GPUOptions.Experimental.Builder setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
setUnknownFields in interface com.google.protobuf.Message.BuildersetUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>public final GPUOptions.Experimental.Builder mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
mergeUnknownFields in interface com.google.protobuf.Message.BuildermergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<GPUOptions.Experimental.Builder>