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update ConfigProto.

tags/v0.12
Oceania2018 6 years ago
parent
6931d5c425
commit
a589552ca9
1 changed files with 645 additions and 78 deletions
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  1. +645
    -78
      src/TensorFlowNET.Core/Protobuf/Config.cs

+ 645
- 78
src/TensorFlowNET.Core/Protobuf/Config.cs View File

@@ -27,10 +27,10 @@ namespace Tensorflow {
"CiV0ZW5zb3JmbG93L2NvcmUvcHJvdG9idWYvY29uZmlnLnByb3RvEgp0ZW5z",
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@@ -38,89 +38,102 @@ namespace Tensorflow {
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"BXZhbHVlGAIgASgJOgI4AUItChhvcmcudGVuc29yZmxvdy5mcmFtZXdvcmtC",
"DENvbmZpZ1Byb3Rvc1AB+AEBYgZwcm90bzM="));
descriptor = pbr::FileDescriptor.FromGeneratedCode(descriptorData,
new pbr::FileDescriptor[] { global::Tensorflow.CostGraphReflection.Descriptor, global::Tensorflow.GraphReflection.Descriptor, global::Tensorflow.StepStatsReflection.Descriptor, global::Tensorflow.DebugReflection.Descriptor, global::Tensorflow.ClusterReflection.Descriptor, global::Tensorflow.RewriterConfigReflection.Descriptor, },
new pbr::FileDescriptor[] { global::Tensorflow.CostGraphReflection.Descriptor, global::Tensorflow.GraphReflection.Descriptor, global::Tensorflow.StepStatsReflection.Descriptor, global::Tensorflow.ClusterReflection.Descriptor, global::Tensorflow.DebugReflection.Descriptor, global::Tensorflow.RewriterConfigReflection.Descriptor, },
new pbr::GeneratedClrTypeInfo(null, new pbr::GeneratedClrTypeInfo[] {
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.GPUOptions), global::Tensorflow.GPUOptions.Parser, new[]{ "PerProcessGpuMemoryFraction", "AllowGrowth", "AllocatorType", "DeferredDeletionBytes", "VisibleDeviceList", "PollingActiveDelayUsecs", "PollingInactiveDelayMsecs", "ForceGpuCompatible", "Experimental" }, null, null, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.GPUOptions.Types.Experimental), global::Tensorflow.GPUOptions.Types.Experimental.Parser, new[]{ "VirtualDevices", "UseUnifiedMemory", "NumDevToDevCopyStreams", "CollectiveRingOrder" }, null, null, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.GPUOptions.Types.Experimental.Types.VirtualDevices), global::Tensorflow.GPUOptions.Types.Experimental.Types.VirtualDevices.Parser, new[]{ "MemoryLimitMb" }, null, null, null)})}),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.GPUOptions), global::Tensorflow.GPUOptions.Parser, new[]{ "PerProcessGpuMemoryFraction", "AllowGrowth", "AllocatorType", "DeferredDeletionBytes", "VisibleDeviceList", "PollingActiveDelayUsecs", "PollingInactiveDelayMsecs", "ForceGpuCompatible", "Experimental" }, null, null, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.GPUOptions.Types.Experimental), global::Tensorflow.GPUOptions.Types.Experimental.Parser, new[]{ "VirtualDevices", "UseUnifiedMemory", "NumDevToDevCopyStreams", "CollectiveRingOrder", "TimestampedAllocator", "KernelTrackerMaxInterval", "KernelTrackerMaxBytes", "KernelTrackerMaxPending" }, null, null, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.GPUOptions.Types.Experimental.Types.VirtualDevices), global::Tensorflow.GPUOptions.Types.Experimental.Types.VirtualDevices.Parser, new[]{ "MemoryLimitMb" }, null, null, null)})}),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.OptimizerOptions), global::Tensorflow.OptimizerOptions.Parser, new[]{ "DoCommonSubexpressionElimination", "DoConstantFolding", "MaxFoldedConstantInBytes", "DoFunctionInlining", "OptLevel", "GlobalJitLevel" }, null, new[]{ typeof(global::Tensorflow.OptimizerOptions.Types.Level), typeof(global::Tensorflow.OptimizerOptions.Types.GlobalJitLevel) }, null),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.GraphOptions), global::Tensorflow.GraphOptions.Parser, new[]{ "EnableRecvScheduling", "OptimizerOptions", "BuildCostModel", "BuildCostModelAfter", "InferShapes", "PlacePrunedGraph", "EnableBfloat16Sendrecv", "TimelineStep", "RewriteOptions" }, null, null, null),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.ThreadPoolOptionProto), global::Tensorflow.ThreadPoolOptionProto.Parser, new[]{ "NumThreads", "GlobalName" }, null, null, null),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.RPCOptions), global::Tensorflow.RPCOptions.Parser, new[]{ "UseRpcForInprocessMaster", "CompressionAlgorithm", "CompressionLevel" }, null, null, null),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.ConfigProto), global::Tensorflow.ConfigProto.Parser, new[]{ "DeviceCount", "IntraOpParallelismThreads", "InterOpParallelismThreads", "UsePerSessionThreads", "SessionInterOpThreadPool", "PlacementPeriod", "DeviceFilters", "GpuOptions", "AllowSoftPlacement", "LogDevicePlacement", "GraphOptions", "OperationTimeoutInMs", "RpcOptions", "ClusterDef", "IsolateSessionState", "Experimental" }, null, null, new pbr::GeneratedClrTypeInfo[] { null, new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.ConfigProto.Types.Experimental), global::Tensorflow.ConfigProto.Types.Experimental.Parser, new[]{ "CollectiveGroupLeader", "ExecutorType", "RecvBufMaxChunk", "UseNumaAffinity" }, null, null, null)}),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.ConfigProto), global::Tensorflow.ConfigProto.Parser, new[]{ "DeviceCount", "IntraOpParallelismThreads", "InterOpParallelismThreads", "UsePerSessionThreads", "SessionInterOpThreadPool", "PlacementPeriod", "DeviceFilters", "GpuOptions", "AllowSoftPlacement", "LogDevicePlacement", "GraphOptions", "OperationTimeoutInMs", "RpcOptions", "ClusterDef", "IsolateSessionState", "Experimental" }, null, null, new pbr::GeneratedClrTypeInfo[] { null, new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.ConfigProto.Types.Experimental), global::Tensorflow.ConfigProto.Types.Experimental.Parser, new[]{ "CollectiveGroupLeader", "ExecutorType", "RecvBufMaxChunk", "UseNumaAffinity", "CollectiveDeterministicSequentialExecution", "CollectiveNccl", "ShareSessionStateInClusterspecPropagation", "DisableThreadSpinning", "ShareClusterDevicesInSession" }, null, null, null)}),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.RunOptions), global::Tensorflow.RunOptions.Parser, new[]{ "TraceLevel", "TimeoutInMs", "InterOpThreadPool", "OutputPartitionGraphs", "DebugOptions", "ReportTensorAllocationsUponOom", "Experimental" }, null, new[]{ typeof(global::Tensorflow.RunOptions.Types.TraceLevel) }, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.RunOptions.Types.Experimental), global::Tensorflow.RunOptions.Types.Experimental.Parser, new[]{ "CollectiveGraphKey", "UseRunHandlerPool" }, null, null, null)}),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.RunMetadata), global::Tensorflow.RunMetadata.Parser, new[]{ "StepStats", "CostGraph", "PartitionGraphs" }, null, null, null),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.RunMetadata), global::Tensorflow.RunMetadata.Parser, new[]{ "StepStats", "CostGraph", "PartitionGraphs", "FunctionGraphs" }, null, null, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.RunMetadata.Types.FunctionGraphs), global::Tensorflow.RunMetadata.Types.FunctionGraphs.Parser, new[]{ "PartitionGraphs", "PreOptimizationGraph", "PostOptimizationGraph" }, null, null, null)}),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.TensorConnection), global::Tensorflow.TensorConnection.Parser, new[]{ "FromTensor", "ToTensor" }, null, null, null),
new pbr::GeneratedClrTypeInfo(typeof(global::Tensorflow.CallableOptions), global::Tensorflow.CallableOptions.Parser, new[]{ "Feed", "Fetch", "Target", "RunOptions", "TensorConnection", "FeedDevices", "FetchDevices", "FetchSkipSync" }, null, null, new pbr::GeneratedClrTypeInfo[] { null, null, })
}));
@@ -605,6 +618,10 @@ namespace Tensorflow {
useUnifiedMemory_ = other.useUnifiedMemory_;
numDevToDevCopyStreams_ = other.numDevToDevCopyStreams_;
collectiveRingOrder_ = other.collectiveRingOrder_;
timestampedAllocator_ = other.timestampedAllocator_;
kernelTrackerMaxInterval_ = other.kernelTrackerMaxInterval_;
kernelTrackerMaxBytes_ = other.kernelTrackerMaxBytes_;
kernelTrackerMaxPending_ = other.kernelTrackerMaxPending_;
_unknownFields = pb::UnknownFieldSet.Clone(other._unknownFields);
}

@@ -703,6 +720,77 @@ namespace Tensorflow {
}
}

/// <summary>Field number for the "timestamped_allocator" field.</summary>
public const int TimestampedAllocatorFieldNumber = 5;
private bool timestampedAllocator_;
/// <summary>
/// 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.
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public bool TimestampedAllocator {
get { return timestampedAllocator_; }
set {
timestampedAllocator_ = value;
}
}

/// <summary>Field number for the "kernel_tracker_max_interval" field.</summary>
public const int KernelTrackerMaxIntervalFieldNumber = 7;
private int kernelTrackerMaxInterval_;
/// <summary>
/// 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.
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public int KernelTrackerMaxInterval {
get { return kernelTrackerMaxInterval_; }
set {
kernelTrackerMaxInterval_ = value;
}
}

/// <summary>Field number for the "kernel_tracker_max_bytes" field.</summary>
public const int KernelTrackerMaxBytesFieldNumber = 8;
private int kernelTrackerMaxBytes_;
/// <summary>
/// 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.
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public int KernelTrackerMaxBytes {
get { return kernelTrackerMaxBytes_; }
set {
kernelTrackerMaxBytes_ = value;
}
}

/// <summary>Field number for the "kernel_tracker_max_pending" field.</summary>
public const int KernelTrackerMaxPendingFieldNumber = 9;
private int kernelTrackerMaxPending_;
/// <summary>
/// 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.
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public int KernelTrackerMaxPending {
get { return kernelTrackerMaxPending_; }
set {
kernelTrackerMaxPending_ = value;
}
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public override bool Equals(object other) {
return Equals(other as Experimental);
@@ -720,6 +808,10 @@ namespace Tensorflow {
if (UseUnifiedMemory != other.UseUnifiedMemory) return false;
if (NumDevToDevCopyStreams != other.NumDevToDevCopyStreams) return false;
if (CollectiveRingOrder != other.CollectiveRingOrder) return false;
if (TimestampedAllocator != other.TimestampedAllocator) return false;
if (KernelTrackerMaxInterval != other.KernelTrackerMaxInterval) return false;
if (KernelTrackerMaxBytes != other.KernelTrackerMaxBytes) return false;
if (KernelTrackerMaxPending != other.KernelTrackerMaxPending) return false;
return Equals(_unknownFields, other._unknownFields);
}

@@ -730,6 +822,10 @@ namespace Tensorflow {
if (UseUnifiedMemory != false) hash ^= UseUnifiedMemory.GetHashCode();
if (NumDevToDevCopyStreams != 0) hash ^= NumDevToDevCopyStreams.GetHashCode();
if (CollectiveRingOrder.Length != 0) hash ^= CollectiveRingOrder.GetHashCode();
if (TimestampedAllocator != false) hash ^= TimestampedAllocator.GetHashCode();
if (KernelTrackerMaxInterval != 0) hash ^= KernelTrackerMaxInterval.GetHashCode();
if (KernelTrackerMaxBytes != 0) hash ^= KernelTrackerMaxBytes.GetHashCode();
if (KernelTrackerMaxPending != 0) hash ^= KernelTrackerMaxPending.GetHashCode();
if (_unknownFields != null) {
hash ^= _unknownFields.GetHashCode();
}
@@ -756,6 +852,22 @@ namespace Tensorflow {
output.WriteRawTag(34);
output.WriteString(CollectiveRingOrder);
}
if (TimestampedAllocator != false) {
output.WriteRawTag(40);
output.WriteBool(TimestampedAllocator);
}
if (KernelTrackerMaxInterval != 0) {
output.WriteRawTag(56);
output.WriteInt32(KernelTrackerMaxInterval);
}
if (KernelTrackerMaxBytes != 0) {
output.WriteRawTag(64);
output.WriteInt32(KernelTrackerMaxBytes);
}
if (KernelTrackerMaxPending != 0) {
output.WriteRawTag(72);
output.WriteInt32(KernelTrackerMaxPending);
}
if (_unknownFields != null) {
_unknownFields.WriteTo(output);
}
@@ -774,6 +886,18 @@ namespace Tensorflow {
if (CollectiveRingOrder.Length != 0) {
size += 1 + pb::CodedOutputStream.ComputeStringSize(CollectiveRingOrder);
}
if (TimestampedAllocator != false) {
size += 1 + 1;
}
if (KernelTrackerMaxInterval != 0) {
size += 1 + pb::CodedOutputStream.ComputeInt32Size(KernelTrackerMaxInterval);
}
if (KernelTrackerMaxBytes != 0) {
size += 1 + pb::CodedOutputStream.ComputeInt32Size(KernelTrackerMaxBytes);
}
if (KernelTrackerMaxPending != 0) {
size += 1 + pb::CodedOutputStream.ComputeInt32Size(KernelTrackerMaxPending);
}
if (_unknownFields != null) {
size += _unknownFields.CalculateSize();
}
@@ -795,6 +919,18 @@ namespace Tensorflow {
if (other.CollectiveRingOrder.Length != 0) {
CollectiveRingOrder = other.CollectiveRingOrder;
}
if (other.TimestampedAllocator != false) {
TimestampedAllocator = other.TimestampedAllocator;
}
if (other.KernelTrackerMaxInterval != 0) {
KernelTrackerMaxInterval = other.KernelTrackerMaxInterval;
}
if (other.KernelTrackerMaxBytes != 0) {
KernelTrackerMaxBytes = other.KernelTrackerMaxBytes;
}
if (other.KernelTrackerMaxPending != 0) {
KernelTrackerMaxPending = other.KernelTrackerMaxPending;
}
_unknownFields = pb::UnknownFieldSet.MergeFrom(_unknownFields, other._unknownFields);
}

@@ -822,6 +958,22 @@ namespace Tensorflow {
CollectiveRingOrder = input.ReadString();
break;
}
case 40: {
TimestampedAllocator = input.ReadBool();
break;
}
case 56: {
KernelTrackerMaxInterval = input.ReadInt32();
break;
}
case 64: {
KernelTrackerMaxBytes = input.ReadInt32();
break;
}
case 72: {
KernelTrackerMaxPending = input.ReadInt32();
break;
}
}
}
}
@@ -2189,6 +2341,7 @@ namespace Tensorflow {
/// inter_op_parallelism_threads available in each process.
///
/// 0 means the system picks an appropriate number.
/// Negative means all operations are performed in caller's thread.
///
/// Note that the first Session created in the process sets the
/// number of threads for all future sessions unless use_per_session_threads is
@@ -2397,7 +2550,8 @@ namespace Tensorflow {
private bool isolateSessionState_;
/// <summary>
/// If true, any resources such as Variables used in the session will not be
/// shared with other sessions.
/// shared with other sessions. However, when clusterspec propagation is
/// enabled, this field is ignored and sessions are always isolated.
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public bool IsolateSessionState {
@@ -2787,6 +2941,11 @@ namespace Tensorflow {
executorType_ = other.executorType_;
recvBufMaxChunk_ = other.recvBufMaxChunk_;
useNumaAffinity_ = other.useNumaAffinity_;
collectiveDeterministicSequentialExecution_ = other.collectiveDeterministicSequentialExecution_;
collectiveNccl_ = other.collectiveNccl_;
shareSessionStateInClusterspecPropagation_ = other.shareSessionStateInClusterspecPropagation_;
disableThreadSpinning_ = other.disableThreadSpinning_;
shareClusterDevicesInSession_ = other.shareClusterDevicesInSession_;
_unknownFields = pb::UnknownFieldSet.Clone(other._unknownFields);
}

@@ -2856,6 +3015,103 @@ namespace Tensorflow {
}
}

/// <summary>Field number for the "collective_deterministic_sequential_execution" field.</summary>
public const int CollectiveDeterministicSequentialExecutionFieldNumber = 6;
private bool collectiveDeterministicSequentialExecution_;
/// <summary>
/// If true, make collective op execution order sequential and deterministic
/// for potentially concurrent collective instances.
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public bool CollectiveDeterministicSequentialExecution {
get { return collectiveDeterministicSequentialExecution_; }
set {
collectiveDeterministicSequentialExecution_ = value;
}
}

/// <summary>Field number for the "collective_nccl" field.</summary>
public const int CollectiveNcclFieldNumber = 7;
private bool collectiveNccl_;
/// <summary>
/// If true, use NCCL for CollectiveOps. This feature is highly
/// experimental.
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public bool CollectiveNccl {
get { return collectiveNccl_; }
set {
collectiveNccl_ = value;
}
}

/// <summary>Field number for the "share_session_state_in_clusterspec_propagation" field.</summary>
public const int ShareSessionStateInClusterspecPropagationFieldNumber = 8;
private bool shareSessionStateInClusterspecPropagation_;
/// <summary>
/// In the following, session state means the value of a variable, elements
/// in a hash table, or any other resource, accessible by worker sessions
/// held by a TF server.
///
/// When ClusterSpec propagation is enabled, the value of
/// isolate_session_state is ignored when deciding whether to share session
/// states in a TF server (for backwards compatibility reasons).
/// - If share_session_state_in_clusterspec_propagation is true, the session
/// states are shared.
/// - If share_session_state_in_clusterspec_propagation is false, session
/// states are isolated.
///
/// When clusterspec propagation is not used, the value of
/// share_session_state_in_clusterspec_propagation is ignored when deciding
/// whether to share session states in a TF server.
/// - If isolate_session_state is true, session states are isolated.
/// - If isolate_session_state is false, session states are shared.
///
/// TODO(b/129330037): Add a single API that consistently treats
/// isolate_session_state and ClusterSpec propagation.
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public bool ShareSessionStateInClusterspecPropagation {
get { return shareSessionStateInClusterspecPropagation_; }
set {
shareSessionStateInClusterspecPropagation_ = value;
}
}

/// <summary>Field number for the "disable_thread_spinning" field.</summary>
public const int DisableThreadSpinningFieldNumber = 9;
private bool disableThreadSpinning_;
/// <summary>
/// If using a direct session, disable spinning while waiting for work in
/// the thread pool. This may result in higher latency for completing ops,
/// but in the case where there is a lot of spinning may result in lower
/// CPU usage.
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public bool DisableThreadSpinning {
get { return disableThreadSpinning_; }
set {
disableThreadSpinning_ = value;
}
}

/// <summary>Field number for the "share_cluster_devices_in_session" field.</summary>
public const int ShareClusterDevicesInSessionFieldNumber = 10;
private bool shareClusterDevicesInSession_;
/// <summary>
/// When true, WorkerSessions are created with device attributes from the
/// full cluster.
/// This is helpful when a worker wants to partition a graph
/// (for example during a PartitionedCallOp).
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public bool ShareClusterDevicesInSession {
get { return shareClusterDevicesInSession_; }
set {
shareClusterDevicesInSession_ = value;
}
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public override bool Equals(object other) {
return Equals(other as Experimental);
@@ -2873,6 +3129,11 @@ namespace Tensorflow {
if (ExecutorType != other.ExecutorType) return false;
if (RecvBufMaxChunk != other.RecvBufMaxChunk) return false;
if (UseNumaAffinity != other.UseNumaAffinity) return false;
if (CollectiveDeterministicSequentialExecution != other.CollectiveDeterministicSequentialExecution) return false;
if (CollectiveNccl != other.CollectiveNccl) return false;
if (ShareSessionStateInClusterspecPropagation != other.ShareSessionStateInClusterspecPropagation) return false;
if (DisableThreadSpinning != other.DisableThreadSpinning) return false;
if (ShareClusterDevicesInSession != other.ShareClusterDevicesInSession) return false;
return Equals(_unknownFields, other._unknownFields);
}

@@ -2883,6 +3144,11 @@ namespace Tensorflow {
if (ExecutorType.Length != 0) hash ^= ExecutorType.GetHashCode();
if (RecvBufMaxChunk != 0) hash ^= RecvBufMaxChunk.GetHashCode();
if (UseNumaAffinity != false) hash ^= UseNumaAffinity.GetHashCode();
if (CollectiveDeterministicSequentialExecution != false) hash ^= CollectiveDeterministicSequentialExecution.GetHashCode();
if (CollectiveNccl != false) hash ^= CollectiveNccl.GetHashCode();
if (ShareSessionStateInClusterspecPropagation != false) hash ^= ShareSessionStateInClusterspecPropagation.GetHashCode();
if (DisableThreadSpinning != false) hash ^= DisableThreadSpinning.GetHashCode();
if (ShareClusterDevicesInSession != false) hash ^= ShareClusterDevicesInSession.GetHashCode();
if (_unknownFields != null) {
hash ^= _unknownFields.GetHashCode();
}
@@ -2912,6 +3178,26 @@ namespace Tensorflow {
output.WriteRawTag(40);
output.WriteBool(UseNumaAffinity);
}
if (CollectiveDeterministicSequentialExecution != false) {
output.WriteRawTag(48);
output.WriteBool(CollectiveDeterministicSequentialExecution);
}
if (CollectiveNccl != false) {
output.WriteRawTag(56);
output.WriteBool(CollectiveNccl);
}
if (ShareSessionStateInClusterspecPropagation != false) {
output.WriteRawTag(64);
output.WriteBool(ShareSessionStateInClusterspecPropagation);
}
if (DisableThreadSpinning != false) {
output.WriteRawTag(72);
output.WriteBool(DisableThreadSpinning);
}
if (ShareClusterDevicesInSession != false) {
output.WriteRawTag(80);
output.WriteBool(ShareClusterDevicesInSession);
}
if (_unknownFields != null) {
_unknownFields.WriteTo(output);
}
@@ -2932,6 +3218,21 @@ namespace Tensorflow {
if (UseNumaAffinity != false) {
size += 1 + 1;
}
if (CollectiveDeterministicSequentialExecution != false) {
size += 1 + 1;
}
if (CollectiveNccl != false) {
size += 1 + 1;
}
if (ShareSessionStateInClusterspecPropagation != false) {
size += 1 + 1;
}
if (DisableThreadSpinning != false) {
size += 1 + 1;
}
if (ShareClusterDevicesInSession != false) {
size += 1 + 1;
}
if (_unknownFields != null) {
size += _unknownFields.CalculateSize();
}
@@ -2955,6 +3256,21 @@ namespace Tensorflow {
if (other.UseNumaAffinity != false) {
UseNumaAffinity = other.UseNumaAffinity;
}
if (other.CollectiveDeterministicSequentialExecution != false) {
CollectiveDeterministicSequentialExecution = other.CollectiveDeterministicSequentialExecution;
}
if (other.CollectiveNccl != false) {
CollectiveNccl = other.CollectiveNccl;
}
if (other.ShareSessionStateInClusterspecPropagation != false) {
ShareSessionStateInClusterspecPropagation = other.ShareSessionStateInClusterspecPropagation;
}
if (other.DisableThreadSpinning != false) {
DisableThreadSpinning = other.DisableThreadSpinning;
}
if (other.ShareClusterDevicesInSession != false) {
ShareClusterDevicesInSession = other.ShareClusterDevicesInSession;
}
_unknownFields = pb::UnknownFieldSet.MergeFrom(_unknownFields, other._unknownFields);
}

@@ -2982,6 +3298,26 @@ namespace Tensorflow {
UseNumaAffinity = input.ReadBool();
break;
}
case 48: {
CollectiveDeterministicSequentialExecution = input.ReadBool();
break;
}
case 56: {
CollectiveNccl = input.ReadBool();
break;
}
case 64: {
ShareSessionStateInClusterspecPropagation = input.ReadBool();
break;
}
case 72: {
DisableThreadSpinning = input.ReadBool();
break;
}
case 80: {
ShareClusterDevicesInSession = input.ReadBool();
break;
}
}
}
}
@@ -3553,6 +3889,7 @@ namespace Tensorflow {
stepStats_ = other.stepStats_ != null ? other.stepStats_.Clone() : null;
costGraph_ = other.costGraph_ != null ? other.costGraph_.Clone() : null;
partitionGraphs_ = other.partitionGraphs_.Clone();
functionGraphs_ = other.functionGraphs_.Clone();
_unknownFields = pb::UnknownFieldSet.Clone(other._unknownFields);
}

@@ -3604,6 +3941,28 @@ namespace Tensorflow {
get { return partitionGraphs_; }
}

/// <summary>Field number for the "function_graphs" field.</summary>
public const int FunctionGraphsFieldNumber = 4;
private static readonly pb::FieldCodec<global::Tensorflow.RunMetadata.Types.FunctionGraphs> _repeated_functionGraphs_codec
= pb::FieldCodec.ForMessage(34, global::Tensorflow.RunMetadata.Types.FunctionGraphs.Parser);
private readonly pbc::RepeatedField<global::Tensorflow.RunMetadata.Types.FunctionGraphs> functionGraphs_ = new pbc::RepeatedField<global::Tensorflow.RunMetadata.Types.FunctionGraphs>();
/// <summary>
/// This is only populated for graphs that are run as functions in TensorFlow
/// V2. There will be an entry below for each function that is traced.
/// The main use cases of the post_optimization_graph and the partition_graphs
/// is to give the caller insight into the graphs that were actually run by the
/// runtime. Additional information (such as those in step_stats) will match
/// these graphs.
/// We also include the pre_optimization_graph since it is usually easier to
/// read, and is helpful in situations where the caller wants to get a high
/// level idea of what the built graph looks like (since the various graph
/// optimization passes might change the structure of the graph significantly).
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public pbc::RepeatedField<global::Tensorflow.RunMetadata.Types.FunctionGraphs> FunctionGraphs {
get { return functionGraphs_; }
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public override bool Equals(object other) {
return Equals(other as RunMetadata);
@@ -3620,6 +3979,7 @@ namespace Tensorflow {
if (!object.Equals(StepStats, other.StepStats)) return false;
if (!object.Equals(CostGraph, other.CostGraph)) return false;
if(!partitionGraphs_.Equals(other.partitionGraphs_)) return false;
if(!functionGraphs_.Equals(other.functionGraphs_)) return false;
return Equals(_unknownFields, other._unknownFields);
}

@@ -3629,6 +3989,7 @@ namespace Tensorflow {
if (stepStats_ != null) hash ^= StepStats.GetHashCode();
if (costGraph_ != null) hash ^= CostGraph.GetHashCode();
hash ^= partitionGraphs_.GetHashCode();
hash ^= functionGraphs_.GetHashCode();
if (_unknownFields != null) {
hash ^= _unknownFields.GetHashCode();
}
@@ -3651,6 +4012,7 @@ namespace Tensorflow {
output.WriteMessage(CostGraph);
}
partitionGraphs_.WriteTo(output, _repeated_partitionGraphs_codec);
functionGraphs_.WriteTo(output, _repeated_functionGraphs_codec);
if (_unknownFields != null) {
_unknownFields.WriteTo(output);
}
@@ -3666,6 +4028,7 @@ namespace Tensorflow {
size += 1 + pb::CodedOutputStream.ComputeMessageSize(CostGraph);
}
size += partitionGraphs_.CalculateSize(_repeated_partitionGraphs_codec);
size += functionGraphs_.CalculateSize(_repeated_functionGraphs_codec);
if (_unknownFields != null) {
size += _unknownFields.CalculateSize();
}
@@ -3690,6 +4053,7 @@ namespace Tensorflow {
CostGraph.MergeFrom(other.CostGraph);
}
partitionGraphs_.Add(other.partitionGraphs_);
functionGraphs_.Add(other.functionGraphs_);
_unknownFields = pb::UnknownFieldSet.MergeFrom(_unknownFields, other._unknownFields);
}

@@ -3719,9 +4083,212 @@ namespace Tensorflow {
partitionGraphs_.AddEntriesFrom(input, _repeated_partitionGraphs_codec);
break;
}
case 34: {
functionGraphs_.AddEntriesFrom(input, _repeated_functionGraphs_codec);
break;
}
}
}
}

#region Nested types
/// <summary>Container for nested types declared in the RunMetadata message type.</summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public static partial class Types {
public sealed partial class FunctionGraphs : pb::IMessage<FunctionGraphs> {
private static readonly pb::MessageParser<FunctionGraphs> _parser = new pb::MessageParser<FunctionGraphs>(() => new FunctionGraphs());
private pb::UnknownFieldSet _unknownFields;
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public static pb::MessageParser<FunctionGraphs> Parser { get { return _parser; } }

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public static pbr::MessageDescriptor Descriptor {
get { return global::Tensorflow.RunMetadata.Descriptor.NestedTypes[0]; }
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
pbr::MessageDescriptor pb::IMessage.Descriptor {
get { return Descriptor; }
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public FunctionGraphs() {
OnConstruction();
}

partial void OnConstruction();

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public FunctionGraphs(FunctionGraphs other) : this() {
partitionGraphs_ = other.partitionGraphs_.Clone();
preOptimizationGraph_ = other.preOptimizationGraph_ != null ? other.preOptimizationGraph_.Clone() : null;
postOptimizationGraph_ = other.postOptimizationGraph_ != null ? other.postOptimizationGraph_.Clone() : null;
_unknownFields = pb::UnknownFieldSet.Clone(other._unknownFields);
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public FunctionGraphs Clone() {
return new FunctionGraphs(this);
}

/// <summary>Field number for the "partition_graphs" field.</summary>
public const int PartitionGraphsFieldNumber = 1;
private static readonly pb::FieldCodec<global::Tensorflow.GraphDef> _repeated_partitionGraphs_codec
= pb::FieldCodec.ForMessage(10, global::Tensorflow.GraphDef.Parser);
private readonly pbc::RepeatedField<global::Tensorflow.GraphDef> partitionGraphs_ = new pbc::RepeatedField<global::Tensorflow.GraphDef>();
/// <summary>
/// TODO(nareshmodi): Include some sort of function/cache-key identifier?
/// </summary>
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public pbc::RepeatedField<global::Tensorflow.GraphDef> PartitionGraphs {
get { return partitionGraphs_; }
}

/// <summary>Field number for the "pre_optimization_graph" field.</summary>
public const int PreOptimizationGraphFieldNumber = 2;
private global::Tensorflow.GraphDef preOptimizationGraph_;
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public global::Tensorflow.GraphDef PreOptimizationGraph {
get { return preOptimizationGraph_; }
set {
preOptimizationGraph_ = value;
}
}

/// <summary>Field number for the "post_optimization_graph" field.</summary>
public const int PostOptimizationGraphFieldNumber = 3;
private global::Tensorflow.GraphDef postOptimizationGraph_;
[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public global::Tensorflow.GraphDef PostOptimizationGraph {
get { return postOptimizationGraph_; }
set {
postOptimizationGraph_ = value;
}
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public override bool Equals(object other) {
return Equals(other as FunctionGraphs);
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public bool Equals(FunctionGraphs other) {
if (ReferenceEquals(other, null)) {
return false;
}
if (ReferenceEquals(other, this)) {
return true;
}
if(!partitionGraphs_.Equals(other.partitionGraphs_)) return false;
if (!object.Equals(PreOptimizationGraph, other.PreOptimizationGraph)) return false;
if (!object.Equals(PostOptimizationGraph, other.PostOptimizationGraph)) return false;
return Equals(_unknownFields, other._unknownFields);
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public override int GetHashCode() {
int hash = 1;
hash ^= partitionGraphs_.GetHashCode();
if (preOptimizationGraph_ != null) hash ^= PreOptimizationGraph.GetHashCode();
if (postOptimizationGraph_ != null) hash ^= PostOptimizationGraph.GetHashCode();
if (_unknownFields != null) {
hash ^= _unknownFields.GetHashCode();
}
return hash;
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public override string ToString() {
return pb::JsonFormatter.ToDiagnosticString(this);
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public void WriteTo(pb::CodedOutputStream output) {
partitionGraphs_.WriteTo(output, _repeated_partitionGraphs_codec);
if (preOptimizationGraph_ != null) {
output.WriteRawTag(18);
output.WriteMessage(PreOptimizationGraph);
}
if (postOptimizationGraph_ != null) {
output.WriteRawTag(26);
output.WriteMessage(PostOptimizationGraph);
}
if (_unknownFields != null) {
_unknownFields.WriteTo(output);
}
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public int CalculateSize() {
int size = 0;
size += partitionGraphs_.CalculateSize(_repeated_partitionGraphs_codec);
if (preOptimizationGraph_ != null) {
size += 1 + pb::CodedOutputStream.ComputeMessageSize(PreOptimizationGraph);
}
if (postOptimizationGraph_ != null) {
size += 1 + pb::CodedOutputStream.ComputeMessageSize(PostOptimizationGraph);
}
if (_unknownFields != null) {
size += _unknownFields.CalculateSize();
}
return size;
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public void MergeFrom(FunctionGraphs other) {
if (other == null) {
return;
}
partitionGraphs_.Add(other.partitionGraphs_);
if (other.preOptimizationGraph_ != null) {
if (preOptimizationGraph_ == null) {
preOptimizationGraph_ = new global::Tensorflow.GraphDef();
}
PreOptimizationGraph.MergeFrom(other.PreOptimizationGraph);
}
if (other.postOptimizationGraph_ != null) {
if (postOptimizationGraph_ == null) {
postOptimizationGraph_ = new global::Tensorflow.GraphDef();
}
PostOptimizationGraph.MergeFrom(other.PostOptimizationGraph);
}
_unknownFields = pb::UnknownFieldSet.MergeFrom(_unknownFields, other._unknownFields);
}

[global::System.Diagnostics.DebuggerNonUserCodeAttribute]
public void MergeFrom(pb::CodedInputStream input) {
uint tag;
while ((tag = input.ReadTag()) != 0) {
switch(tag) {
default:
_unknownFields = pb::UnknownFieldSet.MergeFieldFrom(_unknownFields, input);
break;
case 10: {
partitionGraphs_.AddEntriesFrom(input, _repeated_partitionGraphs_codec);
break;
}
case 18: {
if (preOptimizationGraph_ == null) {
preOptimizationGraph_ = new global::Tensorflow.GraphDef();
}
input.ReadMessage(preOptimizationGraph_);
break;
}
case 26: {
if (postOptimizationGraph_ == null) {
postOptimizationGraph_ = new global::Tensorflow.GraphDef();
}
input.ReadMessage(postOptimizationGraph_);
break;
}
}
}
}

}

}
#endregion

}



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