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// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow/contrib/tpu/proto/topology.proto
package tensorflow.tpu;
public final class Topology {
private Topology() {}
public static void registerAllExtensions(
com.google.protobuf.ExtensionRegistryLite registry) {
}
public static void registerAllExtensions(
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registerAllExtensions(
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public interface TopologyProtoOrBuilder extends
// @@protoc_insertion_point(interface_extends:tensorflow.tpu.TopologyProto)
com.google.protobuf.MessageOrBuilder {
/**
*
* The dimensions of the TPU topology, in cores. Typically, this is a 3D
* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
java.util.List getMeshShapeList();
/**
*
* The dimensions of the TPU topology, in cores. Typically, this is a 3D
* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
int getMeshShapeCount();
/**
*
* The dimensions of the TPU topology, in cores. Typically, this is a 3D
* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
int getMeshShape(int index);
/**
*
* Number of TensorFlow tasks in the cluster.
*
*
* int32 num_tasks = 2;
*/
int getNumTasks();
/**
*
* Number of TPU devices per task.
*
*
* int32 num_tpu_devices_per_task = 3;
*/
int getNumTpuDevicesPerTask();
/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
java.util.List getDeviceCoordinatesList();
/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
int getDeviceCoordinatesCount();
/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
int getDeviceCoordinates(int index);
}
/**
*
* Describes the geometry of a TPU mesh.
*
*
* Protobuf type {@code tensorflow.tpu.TopologyProto}
*/
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TopologyProtoOrBuilder {
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/**
*
* The dimensions of the TPU topology, in cores. Typically, this is a 3D
* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
public java.util.List
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/**
*
* The dimensions of the TPU topology, in cores. Typically, this is a 3D
* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
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/**
*
* The dimensions of the TPU topology, in cores. Typically, this is a 3D
* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
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private int numTasks_;
/**
*
* Number of TensorFlow tasks in the cluster.
*
*
* int32 num_tasks = 2;
*/
public int getNumTasks() {
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}
public static final int NUM_TPU_DEVICES_PER_TASK_FIELD_NUMBER = 3;
private int numTpuDevicesPerTask_;
/**
*
* Number of TPU devices per task.
*
*
* int32 num_tpu_devices_per_task = 3;
*/
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private java.util.List deviceCoordinates_;
/**
*
* A flattened rank 3 int32 array with shape
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* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
public java.util.List
getDeviceCoordinatesList() {
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}
/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
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/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
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/**
*
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*
*
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/**
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*
*
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* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
public int getMeshShapeCount() {
return meshShape_.size();
}
/**
*
* The dimensions of the TPU topology, in cores. Typically, this is a 3D
* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
public int getMeshShape(int index) {
return meshShape_.get(index);
}
/**
*
* The dimensions of the TPU topology, in cores. Typically, this is a 3D
* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
public Builder setMeshShape(
int index, int value) {
ensureMeshShapeIsMutable();
meshShape_.set(index, value);
onChanged();
return this;
}
/**
*
* The dimensions of the TPU topology, in cores. Typically, this is a 3D
* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
public Builder addMeshShape(int value) {
ensureMeshShapeIsMutable();
meshShape_.add(value);
onChanged();
return this;
}
/**
*
* The dimensions of the TPU topology, in cores. Typically, this is a 3D
* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
public Builder addAllMeshShape(
java.lang.Iterable values) {
ensureMeshShapeIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, meshShape_);
onChanged();
return this;
}
/**
*
* The dimensions of the TPU topology, in cores. Typically, this is a 3D
* topology [x, y, core], where the major dimensions correspond to TPU chips,
* and the minor dimension describes the number of cores on a multicore chip.
*
*
* repeated int32 mesh_shape = 1;
*/
public Builder clearMeshShape() {
meshShape_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000001);
onChanged();
return this;
}
private int numTasks_ ;
/**
*
* Number of TensorFlow tasks in the cluster.
*
*
* int32 num_tasks = 2;
*/
public int getNumTasks() {
return numTasks_;
}
/**
*
* Number of TensorFlow tasks in the cluster.
*
*
* int32 num_tasks = 2;
*/
public Builder setNumTasks(int value) {
numTasks_ = value;
onChanged();
return this;
}
/**
*
* Number of TensorFlow tasks in the cluster.
*
*
* int32 num_tasks = 2;
*/
public Builder clearNumTasks() {
numTasks_ = 0;
onChanged();
return this;
}
private int numTpuDevicesPerTask_ ;
/**
*
* Number of TPU devices per task.
*
*
* int32 num_tpu_devices_per_task = 3;
*/
public int getNumTpuDevicesPerTask() {
return numTpuDevicesPerTask_;
}
/**
*
* Number of TPU devices per task.
*
*
* int32 num_tpu_devices_per_task = 3;
*/
public Builder setNumTpuDevicesPerTask(int value) {
numTpuDevicesPerTask_ = value;
onChanged();
return this;
}
/**
*
* Number of TPU devices per task.
*
*
* int32 num_tpu_devices_per_task = 3;
*/
public Builder clearNumTpuDevicesPerTask() {
numTpuDevicesPerTask_ = 0;
onChanged();
return this;
}
private java.util.List deviceCoordinates_ = java.util.Collections.emptyList();
private void ensureDeviceCoordinatesIsMutable() {
if (!((bitField0_ & 0x00000008) == 0x00000008)) {
deviceCoordinates_ = new java.util.ArrayList(deviceCoordinates_);
bitField0_ |= 0x00000008;
}
}
/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
public java.util.List
getDeviceCoordinatesList() {
return java.util.Collections.unmodifiableList(deviceCoordinates_);
}
/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
public int getDeviceCoordinatesCount() {
return deviceCoordinates_.size();
}
/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
public int getDeviceCoordinates(int index) {
return deviceCoordinates_.get(index);
}
/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
public Builder setDeviceCoordinates(
int index, int value) {
ensureDeviceCoordinatesIsMutable();
deviceCoordinates_.set(index, value);
onChanged();
return this;
}
/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
public Builder addDeviceCoordinates(int value) {
ensureDeviceCoordinatesIsMutable();
deviceCoordinates_.add(value);
onChanged();
return this;
}
/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
public Builder addAllDeviceCoordinates(
java.lang.Iterable values) {
ensureDeviceCoordinatesIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, deviceCoordinates_);
onChanged();
return this;
}
/**
*
* A flattened rank 3 int32 array with shape
* [num_tasks, num_tpu_devices_per_task, len(mesh_shape)].
* `tasks` is the number of tasks in the TPU cluster, `devices` is the number
* of TPU devices per task, and the minor dimension corresponds to a position
* in the TPU mesh topology. Each entry [task, device, axis] gives the
* `axis`-th coordinate in the topology of a task/device pair.
*
*
* repeated int32 device_coordinates = 4;
*/
public Builder clearDeviceCoordinates() {
deviceCoordinates_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000008);
onChanged();
return this;
}
@java.lang.Override
public final Builder setUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFieldsProto3(unknownFields);
}
@java.lang.Override
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:tensorflow.tpu.TopologyProto)
}
// @@protoc_insertion_point(class_scope:tensorflow.tpu.TopologyProto)
private static final tensorflow.tpu.Topology.TopologyProto DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new tensorflow.tpu.Topology.TopologyProto();
}
public static tensorflow.tpu.Topology.TopologyProto getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser
PARSER = new com.google.protobuf.AbstractParser() {
@java.lang.Override
public TopologyProto parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return new TopologyProto(input, extensionRegistry);
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public tensorflow.tpu.Topology.TopologyProto getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
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internal_static_tensorflow_tpu_TopologyProto_descriptor;
private static final
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descriptor;
static {
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"\030num_tpu_devices_per_task\030\003 \001(\005\022\032\n\022devic" +
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com.google.protobuf.Descriptors.FileDescriptor.InternalDescriptorAssigner assigner =
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internal_static_tensorflow_tpu_TopologyProto_descriptor =
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// @@protoc_insertion_point(outer_class_scope)
}
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