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// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow/core/protobuf/config.proto
package org.tensorflow.framework;
/**
*
* Metadata output (i.e., non-Tensor) for a single Run() call.
*
*
* Protobuf type {@code tensorflow.RunMetadata}
*/
public final class RunMetadata extends
com.google.protobuf.GeneratedMessageV3 implements
// @@protoc_insertion_point(message_implements:tensorflow.RunMetadata)
RunMetadataOrBuilder {
private static final long serialVersionUID = 0L;
// Use RunMetadata.newBuilder() to construct.
private RunMetadata(com.google.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private RunMetadata() {
partitionGraphs_ = java.util.Collections.emptyList();
functionGraphs_ = java.util.Collections.emptyList();
}
@java.lang.Override
public final com.google.protobuf.UnknownFieldSet
getUnknownFields() {
return this.unknownFields;
}
private RunMetadata(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
this();
if (extensionRegistry == null) {
throw new java.lang.NullPointerException();
}
int mutable_bitField0_ = 0;
com.google.protobuf.UnknownFieldSet.Builder unknownFields =
com.google.protobuf.UnknownFieldSet.newBuilder();
try {
boolean done = false;
while (!done) {
int tag = input.readTag();
switch (tag) {
case 0:
done = true;
break;
default: {
if (!parseUnknownFieldProto3(
input, unknownFields, extensionRegistry, tag)) {
done = true;
}
break;
}
case 10: {
org.tensorflow.framework.StepStats.Builder subBuilder = null;
if (stepStats_ != null) {
subBuilder = stepStats_.toBuilder();
}
stepStats_ = input.readMessage(org.tensorflow.framework.StepStats.parser(), extensionRegistry);
if (subBuilder != null) {
subBuilder.mergeFrom(stepStats_);
stepStats_ = subBuilder.buildPartial();
}
break;
}
case 18: {
org.tensorflow.framework.CostGraphDef.Builder subBuilder = null;
if (costGraph_ != null) {
subBuilder = costGraph_.toBuilder();
}
costGraph_ = input.readMessage(org.tensorflow.framework.CostGraphDef.parser(), extensionRegistry);
if (subBuilder != null) {
subBuilder.mergeFrom(costGraph_);
costGraph_ = subBuilder.buildPartial();
}
break;
}
case 26: {
if (!((mutable_bitField0_ & 0x00000004) == 0x00000004)) {
partitionGraphs_ = new java.util.ArrayList();
mutable_bitField0_ |= 0x00000004;
}
partitionGraphs_.add(
input.readMessage(org.tensorflow.framework.GraphDef.parser(), extensionRegistry));
break;
}
case 34: {
if (!((mutable_bitField0_ & 0x00000008) == 0x00000008)) {
functionGraphs_ = new java.util.ArrayList();
mutable_bitField0_ |= 0x00000008;
}
functionGraphs_.add(
input.readMessage(org.tensorflow.framework.RunMetadata.FunctionGraphs.parser(), extensionRegistry));
break;
}
}
}
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.setUnfinishedMessage(this);
} catch (java.io.IOException e) {
throw new com.google.protobuf.InvalidProtocolBufferException(
e).setUnfinishedMessage(this);
} finally {
if (((mutable_bitField0_ & 0x00000004) == 0x00000004)) {
partitionGraphs_ = java.util.Collections.unmodifiableList(partitionGraphs_);
}
if (((mutable_bitField0_ & 0x00000008) == 0x00000008)) {
functionGraphs_ = java.util.Collections.unmodifiableList(functionGraphs_);
}
this.unknownFields = unknownFields.build();
makeExtensionsImmutable();
}
}
public static final com.google.protobuf.Descriptors.Descriptor
getDescriptor() {
return org.tensorflow.framework.ConfigProtos.internal_static_tensorflow_RunMetadata_descriptor;
}
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return org.tensorflow.framework.ConfigProtos.internal_static_tensorflow_RunMetadata_fieldAccessorTable
.ensureFieldAccessorsInitialized(
org.tensorflow.framework.RunMetadata.class, org.tensorflow.framework.RunMetadata.Builder.class);
}
public interface FunctionGraphsOrBuilder extends
// @@protoc_insertion_point(interface_extends:tensorflow.RunMetadata.FunctionGraphs)
com.google.protobuf.MessageOrBuilder {
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
java.util.List
getPartitionGraphsList();
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
org.tensorflow.framework.GraphDef getPartitionGraphs(int index);
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
int getPartitionGraphsCount();
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
java.util.List
getPartitionGraphsOrBuilderList();
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
org.tensorflow.framework.GraphDefOrBuilder getPartitionGraphsOrBuilder(
int index);
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
boolean hasPreOptimizationGraph();
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
org.tensorflow.framework.GraphDef getPreOptimizationGraph();
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
org.tensorflow.framework.GraphDefOrBuilder getPreOptimizationGraphOrBuilder();
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
boolean hasPostOptimizationGraph();
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
org.tensorflow.framework.GraphDef getPostOptimizationGraph();
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
org.tensorflow.framework.GraphDefOrBuilder getPostOptimizationGraphOrBuilder();
}
/**
* Protobuf type {@code tensorflow.RunMetadata.FunctionGraphs}
*/
public static final class FunctionGraphs extends
com.google.protobuf.GeneratedMessageV3 implements
// @@protoc_insertion_point(message_implements:tensorflow.RunMetadata.FunctionGraphs)
FunctionGraphsOrBuilder {
private static final long serialVersionUID = 0L;
// Use FunctionGraphs.newBuilder() to construct.
private FunctionGraphs(com.google.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private FunctionGraphs() {
partitionGraphs_ = java.util.Collections.emptyList();
}
@java.lang.Override
public final com.google.protobuf.UnknownFieldSet
getUnknownFields() {
return this.unknownFields;
}
private FunctionGraphs(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
this();
if (extensionRegistry == null) {
throw new java.lang.NullPointerException();
}
int mutable_bitField0_ = 0;
com.google.protobuf.UnknownFieldSet.Builder unknownFields =
com.google.protobuf.UnknownFieldSet.newBuilder();
try {
boolean done = false;
while (!done) {
int tag = input.readTag();
switch (tag) {
case 0:
done = true;
break;
default: {
if (!parseUnknownFieldProto3(
input, unknownFields, extensionRegistry, tag)) {
done = true;
}
break;
}
case 10: {
if (!((mutable_bitField0_ & 0x00000001) == 0x00000001)) {
partitionGraphs_ = new java.util.ArrayList();
mutable_bitField0_ |= 0x00000001;
}
partitionGraphs_.add(
input.readMessage(org.tensorflow.framework.GraphDef.parser(), extensionRegistry));
break;
}
case 18: {
org.tensorflow.framework.GraphDef.Builder subBuilder = null;
if (preOptimizationGraph_ != null) {
subBuilder = preOptimizationGraph_.toBuilder();
}
preOptimizationGraph_ = input.readMessage(org.tensorflow.framework.GraphDef.parser(), extensionRegistry);
if (subBuilder != null) {
subBuilder.mergeFrom(preOptimizationGraph_);
preOptimizationGraph_ = subBuilder.buildPartial();
}
break;
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case 26: {
org.tensorflow.framework.GraphDef.Builder subBuilder = null;
if (postOptimizationGraph_ != null) {
subBuilder = postOptimizationGraph_.toBuilder();
}
postOptimizationGraph_ = input.readMessage(org.tensorflow.framework.GraphDef.parser(), extensionRegistry);
if (subBuilder != null) {
subBuilder.mergeFrom(postOptimizationGraph_);
postOptimizationGraph_ = subBuilder.buildPartial();
}
break;
}
}
}
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.setUnfinishedMessage(this);
} catch (java.io.IOException e) {
throw new com.google.protobuf.InvalidProtocolBufferException(
e).setUnfinishedMessage(this);
} finally {
if (((mutable_bitField0_ & 0x00000001) == 0x00000001)) {
partitionGraphs_ = java.util.Collections.unmodifiableList(partitionGraphs_);
}
this.unknownFields = unknownFields.build();
makeExtensionsImmutable();
}
}
public static final com.google.protobuf.Descriptors.Descriptor
getDescriptor() {
return org.tensorflow.framework.ConfigProtos.internal_static_tensorflow_RunMetadata_FunctionGraphs_descriptor;
}
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return org.tensorflow.framework.ConfigProtos.internal_static_tensorflow_RunMetadata_FunctionGraphs_fieldAccessorTable
.ensureFieldAccessorsInitialized(
org.tensorflow.framework.RunMetadata.FunctionGraphs.class, org.tensorflow.framework.RunMetadata.FunctionGraphs.Builder.class);
}
private int bitField0_;
public static final int PARTITION_GRAPHS_FIELD_NUMBER = 1;
private java.util.List partitionGraphs_;
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public java.util.List getPartitionGraphsList() {
return partitionGraphs_;
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public java.util.List
getPartitionGraphsOrBuilderList() {
return partitionGraphs_;
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public int getPartitionGraphsCount() {
return partitionGraphs_.size();
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public org.tensorflow.framework.GraphDef getPartitionGraphs(int index) {
return partitionGraphs_.get(index);
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public org.tensorflow.framework.GraphDefOrBuilder getPartitionGraphsOrBuilder(
int index) {
return partitionGraphs_.get(index);
}
public static final int PRE_OPTIMIZATION_GRAPH_FIELD_NUMBER = 2;
private org.tensorflow.framework.GraphDef preOptimizationGraph_;
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
public boolean hasPreOptimizationGraph() {
return preOptimizationGraph_ != null;
}
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
public org.tensorflow.framework.GraphDef getPreOptimizationGraph() {
return preOptimizationGraph_ == null ? org.tensorflow.framework.GraphDef.getDefaultInstance() : preOptimizationGraph_;
}
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
public org.tensorflow.framework.GraphDefOrBuilder getPreOptimizationGraphOrBuilder() {
return getPreOptimizationGraph();
}
public static final int POST_OPTIMIZATION_GRAPH_FIELD_NUMBER = 3;
private org.tensorflow.framework.GraphDef postOptimizationGraph_;
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
public boolean hasPostOptimizationGraph() {
return postOptimizationGraph_ != null;
}
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
public org.tensorflow.framework.GraphDef getPostOptimizationGraph() {
return postOptimizationGraph_ == null ? org.tensorflow.framework.GraphDef.getDefaultInstance() : postOptimizationGraph_;
}
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
public org.tensorflow.framework.GraphDefOrBuilder getPostOptimizationGraphOrBuilder() {
return getPostOptimizationGraph();
}
private byte memoizedIsInitialized = -1;
public final boolean isInitialized() {
byte isInitialized = memoizedIsInitialized;
if (isInitialized == 1) return true;
if (isInitialized == 0) return false;
memoizedIsInitialized = 1;
return true;
}
public void writeTo(com.google.protobuf.CodedOutputStream output)
throws java.io.IOException {
for (int i = 0; i < partitionGraphs_.size(); i++) {
output.writeMessage(1, partitionGraphs_.get(i));
}
if (preOptimizationGraph_ != null) {
output.writeMessage(2, getPreOptimizationGraph());
}
if (postOptimizationGraph_ != null) {
output.writeMessage(3, getPostOptimizationGraph());
}
unknownFields.writeTo(output);
}
public int getSerializedSize() {
int size = memoizedSize;
if (size != -1) return size;
size = 0;
for (int i = 0; i < partitionGraphs_.size(); i++) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(1, partitionGraphs_.get(i));
}
if (preOptimizationGraph_ != null) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(2, getPreOptimizationGraph());
}
if (postOptimizationGraph_ != null) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(3, getPostOptimizationGraph());
}
size += unknownFields.getSerializedSize();
memoizedSize = size;
return size;
}
@java.lang.Override
public boolean equals(final java.lang.Object obj) {
if (obj == this) {
return true;
}
if (!(obj instanceof org.tensorflow.framework.RunMetadata.FunctionGraphs)) {
return super.equals(obj);
}
org.tensorflow.framework.RunMetadata.FunctionGraphs other = (org.tensorflow.framework.RunMetadata.FunctionGraphs) obj;
boolean result = true;
result = result && getPartitionGraphsList()
.equals(other.getPartitionGraphsList());
result = result && (hasPreOptimizationGraph() == other.hasPreOptimizationGraph());
if (hasPreOptimizationGraph()) {
result = result && getPreOptimizationGraph()
.equals(other.getPreOptimizationGraph());
}
result = result && (hasPostOptimizationGraph() == other.hasPostOptimizationGraph());
if (hasPostOptimizationGraph()) {
result = result && getPostOptimizationGraph()
.equals(other.getPostOptimizationGraph());
}
result = result && unknownFields.equals(other.unknownFields);
return result;
}
@java.lang.Override
public int hashCode() {
if (memoizedHashCode != 0) {
return memoizedHashCode;
}
int hash = 41;
hash = (19 * hash) + getDescriptor().hashCode();
if (getPartitionGraphsCount() > 0) {
hash = (37 * hash) + PARTITION_GRAPHS_FIELD_NUMBER;
hash = (53 * hash) + getPartitionGraphsList().hashCode();
}
if (hasPreOptimizationGraph()) {
hash = (37 * hash) + PRE_OPTIMIZATION_GRAPH_FIELD_NUMBER;
hash = (53 * hash) + getPreOptimizationGraph().hashCode();
}
if (hasPostOptimizationGraph()) {
hash = (37 * hash) + POST_OPTIMIZATION_GRAPH_FIELD_NUMBER;
hash = (53 * hash) + getPostOptimizationGraph().hashCode();
}
hash = (29 * hash) + unknownFields.hashCode();
memoizedHashCode = hash;
return hash;
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseFrom(
java.nio.ByteBuffer data)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseFrom(
java.nio.ByteBuffer data,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseFrom(
com.google.protobuf.ByteString data)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseFrom(
com.google.protobuf.ByteString data,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseFrom(byte[] data)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseFrom(
byte[] data,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseFrom(java.io.InputStream input)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input);
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseFrom(
java.io.InputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input, extensionRegistry);
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseDelimitedFrom(java.io.InputStream input)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3
.parseDelimitedWithIOException(PARSER, input);
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseDelimitedFrom(
java.io.InputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3
.parseDelimitedWithIOException(PARSER, input, extensionRegistry);
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseFrom(
com.google.protobuf.CodedInputStream input)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input);
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs parseFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input, extensionRegistry);
}
public Builder newBuilderForType() { return newBuilder(); }
public static Builder newBuilder() {
return DEFAULT_INSTANCE.toBuilder();
}
public static Builder newBuilder(org.tensorflow.framework.RunMetadata.FunctionGraphs prototype) {
return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype);
}
public Builder toBuilder() {
return this == DEFAULT_INSTANCE
? new Builder() : new Builder().mergeFrom(this);
}
@java.lang.Override
protected Builder newBuilderForType(
com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
Builder builder = new Builder(parent);
return builder;
}
/**
* Protobuf type {@code tensorflow.RunMetadata.FunctionGraphs}
*/
public static final class Builder extends
com.google.protobuf.GeneratedMessageV3.Builder implements
// @@protoc_insertion_point(builder_implements:tensorflow.RunMetadata.FunctionGraphs)
org.tensorflow.framework.RunMetadata.FunctionGraphsOrBuilder {
public static final com.google.protobuf.Descriptors.Descriptor
getDescriptor() {
return org.tensorflow.framework.ConfigProtos.internal_static_tensorflow_RunMetadata_FunctionGraphs_descriptor;
}
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return org.tensorflow.framework.ConfigProtos.internal_static_tensorflow_RunMetadata_FunctionGraphs_fieldAccessorTable
.ensureFieldAccessorsInitialized(
org.tensorflow.framework.RunMetadata.FunctionGraphs.class, org.tensorflow.framework.RunMetadata.FunctionGraphs.Builder.class);
}
// Construct using org.tensorflow.framework.RunMetadata.FunctionGraphs.newBuilder()
private Builder() {
maybeForceBuilderInitialization();
}
private Builder(
com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
super(parent);
maybeForceBuilderInitialization();
}
private void maybeForceBuilderInitialization() {
if (com.google.protobuf.GeneratedMessageV3
.alwaysUseFieldBuilders) {
getPartitionGraphsFieldBuilder();
}
}
public Builder clear() {
super.clear();
if (partitionGraphsBuilder_ == null) {
partitionGraphs_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000001);
} else {
partitionGraphsBuilder_.clear();
}
if (preOptimizationGraphBuilder_ == null) {
preOptimizationGraph_ = null;
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preOptimizationGraph_ = null;
preOptimizationGraphBuilder_ = null;
}
if (postOptimizationGraphBuilder_ == null) {
postOptimizationGraph_ = null;
} else {
postOptimizationGraph_ = null;
postOptimizationGraphBuilder_ = null;
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return this;
}
public com.google.protobuf.Descriptors.Descriptor
getDescriptorForType() {
return org.tensorflow.framework.ConfigProtos.internal_static_tensorflow_RunMetadata_FunctionGraphs_descriptor;
}
public org.tensorflow.framework.RunMetadata.FunctionGraphs getDefaultInstanceForType() {
return org.tensorflow.framework.RunMetadata.FunctionGraphs.getDefaultInstance();
}
public org.tensorflow.framework.RunMetadata.FunctionGraphs build() {
org.tensorflow.framework.RunMetadata.FunctionGraphs result = buildPartial();
if (!result.isInitialized()) {
throw newUninitializedMessageException(result);
}
return result;
}
public org.tensorflow.framework.RunMetadata.FunctionGraphs buildPartial() {
org.tensorflow.framework.RunMetadata.FunctionGraphs result = new org.tensorflow.framework.RunMetadata.FunctionGraphs(this);
int from_bitField0_ = bitField0_;
int to_bitField0_ = 0;
if (partitionGraphsBuilder_ == null) {
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partitionGraphs_ = java.util.Collections.unmodifiableList(partitionGraphs_);
bitField0_ = (bitField0_ & ~0x00000001);
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result.partitionGraphs_ = partitionGraphs_;
} else {
result.partitionGraphs_ = partitionGraphsBuilder_.build();
}
if (preOptimizationGraphBuilder_ == null) {
result.preOptimizationGraph_ = preOptimizationGraph_;
} else {
result.preOptimizationGraph_ = preOptimizationGraphBuilder_.build();
}
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result.postOptimizationGraph_ = postOptimizationGraph_;
} else {
result.postOptimizationGraph_ = postOptimizationGraphBuilder_.build();
}
result.bitField0_ = to_bitField0_;
onBuilt();
return result;
}
public Builder clone() {
return (Builder) super.clone();
}
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com.google.protobuf.Descriptors.FieldDescriptor field,
java.lang.Object value) {
return (Builder) super.setField(field, value);
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public Builder clearField(
com.google.protobuf.Descriptors.FieldDescriptor field) {
return (Builder) super.clearField(field);
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public Builder clearOneof(
com.google.protobuf.Descriptors.OneofDescriptor oneof) {
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public Builder setRepeatedField(
com.google.protobuf.Descriptors.FieldDescriptor field,
int index, java.lang.Object value) {
return (Builder) super.setRepeatedField(field, index, value);
}
public Builder addRepeatedField(
com.google.protobuf.Descriptors.FieldDescriptor field,
java.lang.Object value) {
return (Builder) super.addRepeatedField(field, value);
}
public Builder mergeFrom(com.google.protobuf.Message other) {
if (other instanceof org.tensorflow.framework.RunMetadata.FunctionGraphs) {
return mergeFrom((org.tensorflow.framework.RunMetadata.FunctionGraphs)other);
} else {
super.mergeFrom(other);
return this;
}
}
public Builder mergeFrom(org.tensorflow.framework.RunMetadata.FunctionGraphs other) {
if (other == org.tensorflow.framework.RunMetadata.FunctionGraphs.getDefaultInstance()) return this;
if (partitionGraphsBuilder_ == null) {
if (!other.partitionGraphs_.isEmpty()) {
if (partitionGraphs_.isEmpty()) {
partitionGraphs_ = other.partitionGraphs_;
bitField0_ = (bitField0_ & ~0x00000001);
} else {
ensurePartitionGraphsIsMutable();
partitionGraphs_.addAll(other.partitionGraphs_);
}
onChanged();
}
} else {
if (!other.partitionGraphs_.isEmpty()) {
if (partitionGraphsBuilder_.isEmpty()) {
partitionGraphsBuilder_.dispose();
partitionGraphsBuilder_ = null;
partitionGraphs_ = other.partitionGraphs_;
bitField0_ = (bitField0_ & ~0x00000001);
partitionGraphsBuilder_ =
com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders ?
getPartitionGraphsFieldBuilder() : null;
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partitionGraphsBuilder_.addAllMessages(other.partitionGraphs_);
}
}
}
if (other.hasPreOptimizationGraph()) {
mergePreOptimizationGraph(other.getPreOptimizationGraph());
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mergePostOptimizationGraph(other.getPostOptimizationGraph());
}
this.mergeUnknownFields(other.unknownFields);
onChanged();
return this;
}
public final boolean isInitialized() {
return true;
}
public Builder mergeFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
org.tensorflow.framework.RunMetadata.FunctionGraphs parsedMessage = null;
try {
parsedMessage = PARSER.parsePartialFrom(input, extensionRegistry);
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
parsedMessage = (org.tensorflow.framework.RunMetadata.FunctionGraphs) e.getUnfinishedMessage();
throw e.unwrapIOException();
} finally {
if (parsedMessage != null) {
mergeFrom(parsedMessage);
}
}
return this;
}
private int bitField0_;
private java.util.List partitionGraphs_ =
java.util.Collections.emptyList();
private void ensurePartitionGraphsIsMutable() {
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partitionGraphs_ = new java.util.ArrayList(partitionGraphs_);
bitField0_ |= 0x00000001;
}
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.framework.GraphDef, org.tensorflow.framework.GraphDef.Builder, org.tensorflow.framework.GraphDefOrBuilder> partitionGraphsBuilder_;
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public java.util.List getPartitionGraphsList() {
if (partitionGraphsBuilder_ == null) {
return java.util.Collections.unmodifiableList(partitionGraphs_);
} else {
return partitionGraphsBuilder_.getMessageList();
}
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public int getPartitionGraphsCount() {
if (partitionGraphsBuilder_ == null) {
return partitionGraphs_.size();
} else {
return partitionGraphsBuilder_.getCount();
}
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public org.tensorflow.framework.GraphDef getPartitionGraphs(int index) {
if (partitionGraphsBuilder_ == null) {
return partitionGraphs_.get(index);
} else {
return partitionGraphsBuilder_.getMessage(index);
}
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public Builder setPartitionGraphs(
int index, org.tensorflow.framework.GraphDef value) {
if (partitionGraphsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensurePartitionGraphsIsMutable();
partitionGraphs_.set(index, value);
onChanged();
} else {
partitionGraphsBuilder_.setMessage(index, value);
}
return this;
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public Builder setPartitionGraphs(
int index, org.tensorflow.framework.GraphDef.Builder builderForValue) {
if (partitionGraphsBuilder_ == null) {
ensurePartitionGraphsIsMutable();
partitionGraphs_.set(index, builderForValue.build());
onChanged();
} else {
partitionGraphsBuilder_.setMessage(index, builderForValue.build());
}
return this;
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public Builder addPartitionGraphs(org.tensorflow.framework.GraphDef value) {
if (partitionGraphsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensurePartitionGraphsIsMutable();
partitionGraphs_.add(value);
onChanged();
} else {
partitionGraphsBuilder_.addMessage(value);
}
return this;
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public Builder addPartitionGraphs(
int index, org.tensorflow.framework.GraphDef value) {
if (partitionGraphsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensurePartitionGraphsIsMutable();
partitionGraphs_.add(index, value);
onChanged();
} else {
partitionGraphsBuilder_.addMessage(index, value);
}
return this;
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public Builder addPartitionGraphs(
org.tensorflow.framework.GraphDef.Builder builderForValue) {
if (partitionGraphsBuilder_ == null) {
ensurePartitionGraphsIsMutable();
partitionGraphs_.add(builderForValue.build());
onChanged();
} else {
partitionGraphsBuilder_.addMessage(builderForValue.build());
}
return this;
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public Builder addPartitionGraphs(
int index, org.tensorflow.framework.GraphDef.Builder builderForValue) {
if (partitionGraphsBuilder_ == null) {
ensurePartitionGraphsIsMutable();
partitionGraphs_.add(index, builderForValue.build());
onChanged();
} else {
partitionGraphsBuilder_.addMessage(index, builderForValue.build());
}
return this;
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public Builder addAllPartitionGraphs(
java.lang.Iterable values) {
if (partitionGraphsBuilder_ == null) {
ensurePartitionGraphsIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, partitionGraphs_);
onChanged();
} else {
partitionGraphsBuilder_.addAllMessages(values);
}
return this;
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public Builder clearPartitionGraphs() {
if (partitionGraphsBuilder_ == null) {
partitionGraphs_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000001);
onChanged();
} else {
partitionGraphsBuilder_.clear();
}
return this;
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public Builder removePartitionGraphs(int index) {
if (partitionGraphsBuilder_ == null) {
ensurePartitionGraphsIsMutable();
partitionGraphs_.remove(index);
onChanged();
} else {
partitionGraphsBuilder_.remove(index);
}
return this;
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public org.tensorflow.framework.GraphDef.Builder getPartitionGraphsBuilder(
int index) {
return getPartitionGraphsFieldBuilder().getBuilder(index);
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public org.tensorflow.framework.GraphDefOrBuilder getPartitionGraphsOrBuilder(
int index) {
if (partitionGraphsBuilder_ == null) {
return partitionGraphs_.get(index); } else {
return partitionGraphsBuilder_.getMessageOrBuilder(index);
}
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public java.util.List
getPartitionGraphsOrBuilderList() {
if (partitionGraphsBuilder_ != null) {
return partitionGraphsBuilder_.getMessageOrBuilderList();
} else {
return java.util.Collections.unmodifiableList(partitionGraphs_);
}
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public org.tensorflow.framework.GraphDef.Builder addPartitionGraphsBuilder() {
return getPartitionGraphsFieldBuilder().addBuilder(
org.tensorflow.framework.GraphDef.getDefaultInstance());
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public org.tensorflow.framework.GraphDef.Builder addPartitionGraphsBuilder(
int index) {
return getPartitionGraphsFieldBuilder().addBuilder(
index, org.tensorflow.framework.GraphDef.getDefaultInstance());
}
/**
*
* TODO(nareshmodi): Include some sort of function/cache-key identifier?
*
*
* repeated .tensorflow.GraphDef partition_graphs = 1;
*/
public java.util.List
getPartitionGraphsBuilderList() {
return getPartitionGraphsFieldBuilder().getBuilderList();
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.framework.GraphDef, org.tensorflow.framework.GraphDef.Builder, org.tensorflow.framework.GraphDefOrBuilder>
getPartitionGraphsFieldBuilder() {
if (partitionGraphsBuilder_ == null) {
partitionGraphsBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.framework.GraphDef, org.tensorflow.framework.GraphDef.Builder, org.tensorflow.framework.GraphDefOrBuilder>(
partitionGraphs_,
((bitField0_ & 0x00000001) == 0x00000001),
getParentForChildren(),
isClean());
partitionGraphs_ = null;
}
return partitionGraphsBuilder_;
}
private org.tensorflow.framework.GraphDef preOptimizationGraph_ = null;
private com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.framework.GraphDef, org.tensorflow.framework.GraphDef.Builder, org.tensorflow.framework.GraphDefOrBuilder> preOptimizationGraphBuilder_;
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
public boolean hasPreOptimizationGraph() {
return preOptimizationGraphBuilder_ != null || preOptimizationGraph_ != null;
}
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
public org.tensorflow.framework.GraphDef getPreOptimizationGraph() {
if (preOptimizationGraphBuilder_ == null) {
return preOptimizationGraph_ == null ? org.tensorflow.framework.GraphDef.getDefaultInstance() : preOptimizationGraph_;
} else {
return preOptimizationGraphBuilder_.getMessage();
}
}
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
public Builder setPreOptimizationGraph(org.tensorflow.framework.GraphDef value) {
if (preOptimizationGraphBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
preOptimizationGraph_ = value;
onChanged();
} else {
preOptimizationGraphBuilder_.setMessage(value);
}
return this;
}
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
public Builder setPreOptimizationGraph(
org.tensorflow.framework.GraphDef.Builder builderForValue) {
if (preOptimizationGraphBuilder_ == null) {
preOptimizationGraph_ = builderForValue.build();
onChanged();
} else {
preOptimizationGraphBuilder_.setMessage(builderForValue.build());
}
return this;
}
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
public Builder mergePreOptimizationGraph(org.tensorflow.framework.GraphDef value) {
if (preOptimizationGraphBuilder_ == null) {
if (preOptimizationGraph_ != null) {
preOptimizationGraph_ =
org.tensorflow.framework.GraphDef.newBuilder(preOptimizationGraph_).mergeFrom(value).buildPartial();
} else {
preOptimizationGraph_ = value;
}
onChanged();
} else {
preOptimizationGraphBuilder_.mergeFrom(value);
}
return this;
}
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
public Builder clearPreOptimizationGraph() {
if (preOptimizationGraphBuilder_ == null) {
preOptimizationGraph_ = null;
onChanged();
} else {
preOptimizationGraph_ = null;
preOptimizationGraphBuilder_ = null;
}
return this;
}
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
public org.tensorflow.framework.GraphDef.Builder getPreOptimizationGraphBuilder() {
onChanged();
return getPreOptimizationGraphFieldBuilder().getBuilder();
}
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
public org.tensorflow.framework.GraphDefOrBuilder getPreOptimizationGraphOrBuilder() {
if (preOptimizationGraphBuilder_ != null) {
return preOptimizationGraphBuilder_.getMessageOrBuilder();
} else {
return preOptimizationGraph_ == null ?
org.tensorflow.framework.GraphDef.getDefaultInstance() : preOptimizationGraph_;
}
}
/**
* .tensorflow.GraphDef pre_optimization_graph = 2;
*/
private com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.framework.GraphDef, org.tensorflow.framework.GraphDef.Builder, org.tensorflow.framework.GraphDefOrBuilder>
getPreOptimizationGraphFieldBuilder() {
if (preOptimizationGraphBuilder_ == null) {
preOptimizationGraphBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.framework.GraphDef, org.tensorflow.framework.GraphDef.Builder, org.tensorflow.framework.GraphDefOrBuilder>(
getPreOptimizationGraph(),
getParentForChildren(),
isClean());
preOptimizationGraph_ = null;
}
return preOptimizationGraphBuilder_;
}
private org.tensorflow.framework.GraphDef postOptimizationGraph_ = null;
private com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.framework.GraphDef, org.tensorflow.framework.GraphDef.Builder, org.tensorflow.framework.GraphDefOrBuilder> postOptimizationGraphBuilder_;
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
public boolean hasPostOptimizationGraph() {
return postOptimizationGraphBuilder_ != null || postOptimizationGraph_ != null;
}
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
public org.tensorflow.framework.GraphDef getPostOptimizationGraph() {
if (postOptimizationGraphBuilder_ == null) {
return postOptimizationGraph_ == null ? org.tensorflow.framework.GraphDef.getDefaultInstance() : postOptimizationGraph_;
} else {
return postOptimizationGraphBuilder_.getMessage();
}
}
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
public Builder setPostOptimizationGraph(org.tensorflow.framework.GraphDef value) {
if (postOptimizationGraphBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
postOptimizationGraph_ = value;
onChanged();
} else {
postOptimizationGraphBuilder_.setMessage(value);
}
return this;
}
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
public Builder setPostOptimizationGraph(
org.tensorflow.framework.GraphDef.Builder builderForValue) {
if (postOptimizationGraphBuilder_ == null) {
postOptimizationGraph_ = builderForValue.build();
onChanged();
} else {
postOptimizationGraphBuilder_.setMessage(builderForValue.build());
}
return this;
}
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
public Builder mergePostOptimizationGraph(org.tensorflow.framework.GraphDef value) {
if (postOptimizationGraphBuilder_ == null) {
if (postOptimizationGraph_ != null) {
postOptimizationGraph_ =
org.tensorflow.framework.GraphDef.newBuilder(postOptimizationGraph_).mergeFrom(value).buildPartial();
} else {
postOptimizationGraph_ = value;
}
onChanged();
} else {
postOptimizationGraphBuilder_.mergeFrom(value);
}
return this;
}
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
public Builder clearPostOptimizationGraph() {
if (postOptimizationGraphBuilder_ == null) {
postOptimizationGraph_ = null;
onChanged();
} else {
postOptimizationGraph_ = null;
postOptimizationGraphBuilder_ = null;
}
return this;
}
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
public org.tensorflow.framework.GraphDef.Builder getPostOptimizationGraphBuilder() {
onChanged();
return getPostOptimizationGraphFieldBuilder().getBuilder();
}
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
public org.tensorflow.framework.GraphDefOrBuilder getPostOptimizationGraphOrBuilder() {
if (postOptimizationGraphBuilder_ != null) {
return postOptimizationGraphBuilder_.getMessageOrBuilder();
} else {
return postOptimizationGraph_ == null ?
org.tensorflow.framework.GraphDef.getDefaultInstance() : postOptimizationGraph_;
}
}
/**
* .tensorflow.GraphDef post_optimization_graph = 3;
*/
private com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.framework.GraphDef, org.tensorflow.framework.GraphDef.Builder, org.tensorflow.framework.GraphDefOrBuilder>
getPostOptimizationGraphFieldBuilder() {
if (postOptimizationGraphBuilder_ == null) {
postOptimizationGraphBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.framework.GraphDef, org.tensorflow.framework.GraphDef.Builder, org.tensorflow.framework.GraphDefOrBuilder>(
getPostOptimizationGraph(),
getParentForChildren(),
isClean());
postOptimizationGraph_ = null;
}
return postOptimizationGraphBuilder_;
}
public final Builder setUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFieldsProto3(unknownFields);
}
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:tensorflow.RunMetadata.FunctionGraphs)
}
// @@protoc_insertion_point(class_scope:tensorflow.RunMetadata.FunctionGraphs)
private static final org.tensorflow.framework.RunMetadata.FunctionGraphs DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new org.tensorflow.framework.RunMetadata.FunctionGraphs();
}
public static org.tensorflow.framework.RunMetadata.FunctionGraphs getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser
PARSER = new com.google.protobuf.AbstractParser() {
public FunctionGraphs parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return new FunctionGraphs(input, extensionRegistry);
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
public org.tensorflow.framework.RunMetadata.FunctionGraphs getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
private int bitField0_;
public static final int STEP_STATS_FIELD_NUMBER = 1;
private org.tensorflow.framework.StepStats stepStats_;
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
public boolean hasStepStats() {
return stepStats_ != null;
}
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
public org.tensorflow.framework.StepStats getStepStats() {
return stepStats_ == null ? org.tensorflow.framework.StepStats.getDefaultInstance() : stepStats_;
}
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
public org.tensorflow.framework.StepStatsOrBuilder getStepStatsOrBuilder() {
return getStepStats();
}
public static final int COST_GRAPH_FIELD_NUMBER = 2;
private org.tensorflow.framework.CostGraphDef costGraph_;
/**
*
* The cost graph for the computation defined by the run call.
*
*
* .tensorflow.CostGraphDef cost_graph = 2;
*/
public boolean hasCostGraph() {
return costGraph_ != null;
}
/**
*
* The cost graph for the computation defined by the run call.
*
*
* .tensorflow.CostGraphDef cost_graph = 2;
*/
public org.tensorflow.framework.CostGraphDef getCostGraph() {
return costGraph_ == null ? org.tensorflow.framework.CostGraphDef.getDefaultInstance() : costGraph_;
}
/**
*
* The cost graph for the computation defined by the run call.
*
*
* .tensorflow.CostGraphDef cost_graph = 2;
*/
public org.tensorflow.framework.CostGraphDefOrBuilder getCostGraphOrBuilder() {
return getCostGraph();
}
public static final int PARTITION_GRAPHS_FIELD_NUMBER = 3;
private java.util.List partitionGraphs_;
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public java.util.List getPartitionGraphsList() {
return partitionGraphs_;
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public java.util.List
getPartitionGraphsOrBuilderList() {
return partitionGraphs_;
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public int getPartitionGraphsCount() {
return partitionGraphs_.size();
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public org.tensorflow.framework.GraphDef getPartitionGraphs(int index) {
return partitionGraphs_.get(index);
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public org.tensorflow.framework.GraphDefOrBuilder getPartitionGraphsOrBuilder(
int index) {
return partitionGraphs_.get(index);
}
public static final int FUNCTION_GRAPHS_FIELD_NUMBER = 4;
private java.util.List functionGraphs_;
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public java.util.List getFunctionGraphsList() {
return functionGraphs_;
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public java.util.List
getFunctionGraphsOrBuilderList() {
return functionGraphs_;
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public int getFunctionGraphsCount() {
return functionGraphs_.size();
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public org.tensorflow.framework.RunMetadata.FunctionGraphs getFunctionGraphs(int index) {
return functionGraphs_.get(index);
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public org.tensorflow.framework.RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder(
int index) {
return functionGraphs_.get(index);
}
private byte memoizedIsInitialized = -1;
public final boolean isInitialized() {
byte isInitialized = memoizedIsInitialized;
if (isInitialized == 1) return true;
if (isInitialized == 0) return false;
memoizedIsInitialized = 1;
return true;
}
public void writeTo(com.google.protobuf.CodedOutputStream output)
throws java.io.IOException {
if (stepStats_ != null) {
output.writeMessage(1, getStepStats());
}
if (costGraph_ != null) {
output.writeMessage(2, getCostGraph());
}
for (int i = 0; i < partitionGraphs_.size(); i++) {
output.writeMessage(3, partitionGraphs_.get(i));
}
for (int i = 0; i < functionGraphs_.size(); i++) {
output.writeMessage(4, functionGraphs_.get(i));
}
unknownFields.writeTo(output);
}
public int getSerializedSize() {
int size = memoizedSize;
if (size != -1) return size;
size = 0;
if (stepStats_ != null) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(1, getStepStats());
}
if (costGraph_ != null) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(2, getCostGraph());
}
for (int i = 0; i < partitionGraphs_.size(); i++) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(3, partitionGraphs_.get(i));
}
for (int i = 0; i < functionGraphs_.size(); i++) {
size += com.google.protobuf.CodedOutputStream
.computeMessageSize(4, functionGraphs_.get(i));
}
size += unknownFields.getSerializedSize();
memoizedSize = size;
return size;
}
@java.lang.Override
public boolean equals(final java.lang.Object obj) {
if (obj == this) {
return true;
}
if (!(obj instanceof org.tensorflow.framework.RunMetadata)) {
return super.equals(obj);
}
org.tensorflow.framework.RunMetadata other = (org.tensorflow.framework.RunMetadata) obj;
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protected Builder newBuilderForType(
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/**
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public static final class Builder extends
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public Builder mergeFrom(org.tensorflow.framework.RunMetadata other) {
if (other == org.tensorflow.framework.RunMetadata.getDefaultInstance()) return this;
if (other.hasStepStats()) {
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com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
org.tensorflow.framework.RunMetadata parsedMessage = null;
try {
parsedMessage = PARSER.parsePartialFrom(input, extensionRegistry);
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parsedMessage = (org.tensorflow.framework.RunMetadata) e.getUnfinishedMessage();
throw e.unwrapIOException();
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private int bitField0_;
private org.tensorflow.framework.StepStats stepStats_ = null;
private com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.framework.StepStats, org.tensorflow.framework.StepStats.Builder, org.tensorflow.framework.StepStatsOrBuilder> stepStatsBuilder_;
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
public boolean hasStepStats() {
return stepStatsBuilder_ != null || stepStats_ != null;
}
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
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if (stepStatsBuilder_ == null) {
return stepStats_ == null ? org.tensorflow.framework.StepStats.getDefaultInstance() : stepStats_;
} else {
return stepStatsBuilder_.getMessage();
}
}
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
public Builder setStepStats(org.tensorflow.framework.StepStats value) {
if (stepStatsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
stepStats_ = value;
onChanged();
} else {
stepStatsBuilder_.setMessage(value);
}
return this;
}
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
public Builder setStepStats(
org.tensorflow.framework.StepStats.Builder builderForValue) {
if (stepStatsBuilder_ == null) {
stepStats_ = builderForValue.build();
onChanged();
} else {
stepStatsBuilder_.setMessage(builderForValue.build());
}
return this;
}
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
public Builder mergeStepStats(org.tensorflow.framework.StepStats value) {
if (stepStatsBuilder_ == null) {
if (stepStats_ != null) {
stepStats_ =
org.tensorflow.framework.StepStats.newBuilder(stepStats_).mergeFrom(value).buildPartial();
} else {
stepStats_ = value;
}
onChanged();
} else {
stepStatsBuilder_.mergeFrom(value);
}
return this;
}
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
public Builder clearStepStats() {
if (stepStatsBuilder_ == null) {
stepStats_ = null;
onChanged();
} else {
stepStats_ = null;
stepStatsBuilder_ = null;
}
return this;
}
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
public org.tensorflow.framework.StepStats.Builder getStepStatsBuilder() {
onChanged();
return getStepStatsFieldBuilder().getBuilder();
}
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
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if (stepStatsBuilder_ != null) {
return stepStatsBuilder_.getMessageOrBuilder();
} else {
return stepStats_ == null ?
org.tensorflow.framework.StepStats.getDefaultInstance() : stepStats_;
}
}
/**
*
* Statistics traced for this step. Populated if tracing is turned on via the
* "RunOptions" proto.
* EXPERIMENTAL: The format and set of events may change in future versions.
*
*
* .tensorflow.StepStats step_stats = 1;
*/
private com.google.protobuf.SingleFieldBuilderV3<
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getStepStatsFieldBuilder() {
if (stepStatsBuilder_ == null) {
stepStatsBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
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getStepStats(),
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isClean());
stepStats_ = null;
}
return stepStatsBuilder_;
}
private org.tensorflow.framework.CostGraphDef costGraph_ = null;
private com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.framework.CostGraphDef, org.tensorflow.framework.CostGraphDef.Builder, org.tensorflow.framework.CostGraphDefOrBuilder> costGraphBuilder_;
/**
*
* The cost graph for the computation defined by the run call.
*
*
* .tensorflow.CostGraphDef cost_graph = 2;
*/
public boolean hasCostGraph() {
return costGraphBuilder_ != null || costGraph_ != null;
}
/**
*
* The cost graph for the computation defined by the run call.
*
*
* .tensorflow.CostGraphDef cost_graph = 2;
*/
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if (costGraphBuilder_ == null) {
return costGraph_ == null ? org.tensorflow.framework.CostGraphDef.getDefaultInstance() : costGraph_;
} else {
return costGraphBuilder_.getMessage();
}
}
/**
*
* The cost graph for the computation defined by the run call.
*
*
* .tensorflow.CostGraphDef cost_graph = 2;
*/
public Builder setCostGraph(org.tensorflow.framework.CostGraphDef value) {
if (costGraphBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
costGraph_ = value;
onChanged();
} else {
costGraphBuilder_.setMessage(value);
}
return this;
}
/**
*
* The cost graph for the computation defined by the run call.
*
*
* .tensorflow.CostGraphDef cost_graph = 2;
*/
public Builder setCostGraph(
org.tensorflow.framework.CostGraphDef.Builder builderForValue) {
if (costGraphBuilder_ == null) {
costGraph_ = builderForValue.build();
onChanged();
} else {
costGraphBuilder_.setMessage(builderForValue.build());
}
return this;
}
/**
*
* The cost graph for the computation defined by the run call.
*
*
* .tensorflow.CostGraphDef cost_graph = 2;
*/
public Builder mergeCostGraph(org.tensorflow.framework.CostGraphDef value) {
if (costGraphBuilder_ == null) {
if (costGraph_ != null) {
costGraph_ =
org.tensorflow.framework.CostGraphDef.newBuilder(costGraph_).mergeFrom(value).buildPartial();
} else {
costGraph_ = value;
}
onChanged();
} else {
costGraphBuilder_.mergeFrom(value);
}
return this;
}
/**
*
* The cost graph for the computation defined by the run call.
*
*
* .tensorflow.CostGraphDef cost_graph = 2;
*/
public Builder clearCostGraph() {
if (costGraphBuilder_ == null) {
costGraph_ = null;
onChanged();
} else {
costGraph_ = null;
costGraphBuilder_ = null;
}
return this;
}
/**
*
* The cost graph for the computation defined by the run call.
*
*
* .tensorflow.CostGraphDef cost_graph = 2;
*/
public org.tensorflow.framework.CostGraphDef.Builder getCostGraphBuilder() {
onChanged();
return getCostGraphFieldBuilder().getBuilder();
}
/**
*
* The cost graph for the computation defined by the run call.
*
*
* .tensorflow.CostGraphDef cost_graph = 2;
*/
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return costGraphBuilder_.getMessageOrBuilder();
} else {
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org.tensorflow.framework.CostGraphDef.getDefaultInstance() : costGraph_;
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/**
*
* The cost graph for the computation defined by the run call.
*
*
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*/
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getCostGraphFieldBuilder() {
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getCostGraph(),
getParentForChildren(),
isClean());
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/**
*
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*
*
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*/
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/**
*
* Graphs of the partitions executed by executors.
*
*
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*/
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/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
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if (partitionGraphsBuilder_ == null) {
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return partitionGraphsBuilder_.getMessage(index);
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}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public Builder setPartitionGraphs(
int index, org.tensorflow.framework.GraphDef value) {
if (partitionGraphsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensurePartitionGraphsIsMutable();
partitionGraphs_.set(index, value);
onChanged();
} else {
partitionGraphsBuilder_.setMessage(index, value);
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return this;
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public Builder setPartitionGraphs(
int index, org.tensorflow.framework.GraphDef.Builder builderForValue) {
if (partitionGraphsBuilder_ == null) {
ensurePartitionGraphsIsMutable();
partitionGraphs_.set(index, builderForValue.build());
onChanged();
} else {
partitionGraphsBuilder_.setMessage(index, builderForValue.build());
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return this;
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public Builder addPartitionGraphs(org.tensorflow.framework.GraphDef value) {
if (partitionGraphsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensurePartitionGraphsIsMutable();
partitionGraphs_.add(value);
onChanged();
} else {
partitionGraphsBuilder_.addMessage(value);
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return this;
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public Builder addPartitionGraphs(
int index, org.tensorflow.framework.GraphDef value) {
if (partitionGraphsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensurePartitionGraphsIsMutable();
partitionGraphs_.add(index, value);
onChanged();
} else {
partitionGraphsBuilder_.addMessage(index, value);
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return this;
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/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public Builder addPartitionGraphs(
org.tensorflow.framework.GraphDef.Builder builderForValue) {
if (partitionGraphsBuilder_ == null) {
ensurePartitionGraphsIsMutable();
partitionGraphs_.add(builderForValue.build());
onChanged();
} else {
partitionGraphsBuilder_.addMessage(builderForValue.build());
}
return this;
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public Builder addPartitionGraphs(
int index, org.tensorflow.framework.GraphDef.Builder builderForValue) {
if (partitionGraphsBuilder_ == null) {
ensurePartitionGraphsIsMutable();
partitionGraphs_.add(index, builderForValue.build());
onChanged();
} else {
partitionGraphsBuilder_.addMessage(index, builderForValue.build());
}
return this;
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public Builder addAllPartitionGraphs(
java.lang.Iterable values) {
if (partitionGraphsBuilder_ == null) {
ensurePartitionGraphsIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, partitionGraphs_);
onChanged();
} else {
partitionGraphsBuilder_.addAllMessages(values);
}
return this;
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public Builder clearPartitionGraphs() {
if (partitionGraphsBuilder_ == null) {
partitionGraphs_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000004);
onChanged();
} else {
partitionGraphsBuilder_.clear();
}
return this;
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public Builder removePartitionGraphs(int index) {
if (partitionGraphsBuilder_ == null) {
ensurePartitionGraphsIsMutable();
partitionGraphs_.remove(index);
onChanged();
} else {
partitionGraphsBuilder_.remove(index);
}
return this;
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public org.tensorflow.framework.GraphDef.Builder getPartitionGraphsBuilder(
int index) {
return getPartitionGraphsFieldBuilder().getBuilder(index);
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public org.tensorflow.framework.GraphDefOrBuilder getPartitionGraphsOrBuilder(
int index) {
if (partitionGraphsBuilder_ == null) {
return partitionGraphs_.get(index); } else {
return partitionGraphsBuilder_.getMessageOrBuilder(index);
}
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public java.util.List
getPartitionGraphsOrBuilderList() {
if (partitionGraphsBuilder_ != null) {
return partitionGraphsBuilder_.getMessageOrBuilderList();
} else {
return java.util.Collections.unmodifiableList(partitionGraphs_);
}
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public org.tensorflow.framework.GraphDef.Builder addPartitionGraphsBuilder() {
return getPartitionGraphsFieldBuilder().addBuilder(
org.tensorflow.framework.GraphDef.getDefaultInstance());
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public org.tensorflow.framework.GraphDef.Builder addPartitionGraphsBuilder(
int index) {
return getPartitionGraphsFieldBuilder().addBuilder(
index, org.tensorflow.framework.GraphDef.getDefaultInstance());
}
/**
*
* Graphs of the partitions executed by executors.
*
*
* repeated .tensorflow.GraphDef partition_graphs = 3;
*/
public java.util.List
getPartitionGraphsBuilderList() {
return getPartitionGraphsFieldBuilder().getBuilderList();
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.framework.GraphDef, org.tensorflow.framework.GraphDef.Builder, org.tensorflow.framework.GraphDefOrBuilder>
getPartitionGraphsFieldBuilder() {
if (partitionGraphsBuilder_ == null) {
partitionGraphsBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.framework.GraphDef, org.tensorflow.framework.GraphDef.Builder, org.tensorflow.framework.GraphDefOrBuilder>(
partitionGraphs_,
((bitField0_ & 0x00000004) == 0x00000004),
getParentForChildren(),
isClean());
partitionGraphs_ = null;
}
return partitionGraphsBuilder_;
}
private java.util.List functionGraphs_ =
java.util.Collections.emptyList();
private void ensureFunctionGraphsIsMutable() {
if (!((bitField0_ & 0x00000008) == 0x00000008)) {
functionGraphs_ = new java.util.ArrayList(functionGraphs_);
bitField0_ |= 0x00000008;
}
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.framework.RunMetadata.FunctionGraphs, org.tensorflow.framework.RunMetadata.FunctionGraphs.Builder, org.tensorflow.framework.RunMetadata.FunctionGraphsOrBuilder> functionGraphsBuilder_;
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public java.util.List getFunctionGraphsList() {
if (functionGraphsBuilder_ == null) {
return java.util.Collections.unmodifiableList(functionGraphs_);
} else {
return functionGraphsBuilder_.getMessageList();
}
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public int getFunctionGraphsCount() {
if (functionGraphsBuilder_ == null) {
return functionGraphs_.size();
} else {
return functionGraphsBuilder_.getCount();
}
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public org.tensorflow.framework.RunMetadata.FunctionGraphs getFunctionGraphs(int index) {
if (functionGraphsBuilder_ == null) {
return functionGraphs_.get(index);
} else {
return functionGraphsBuilder_.getMessage(index);
}
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public Builder setFunctionGraphs(
int index, org.tensorflow.framework.RunMetadata.FunctionGraphs value) {
if (functionGraphsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureFunctionGraphsIsMutable();
functionGraphs_.set(index, value);
onChanged();
} else {
functionGraphsBuilder_.setMessage(index, value);
}
return this;
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public Builder setFunctionGraphs(
int index, org.tensorflow.framework.RunMetadata.FunctionGraphs.Builder builderForValue) {
if (functionGraphsBuilder_ == null) {
ensureFunctionGraphsIsMutable();
functionGraphs_.set(index, builderForValue.build());
onChanged();
} else {
functionGraphsBuilder_.setMessage(index, builderForValue.build());
}
return this;
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public Builder addFunctionGraphs(org.tensorflow.framework.RunMetadata.FunctionGraphs value) {
if (functionGraphsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureFunctionGraphsIsMutable();
functionGraphs_.add(value);
onChanged();
} else {
functionGraphsBuilder_.addMessage(value);
}
return this;
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public Builder addFunctionGraphs(
int index, org.tensorflow.framework.RunMetadata.FunctionGraphs value) {
if (functionGraphsBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureFunctionGraphsIsMutable();
functionGraphs_.add(index, value);
onChanged();
} else {
functionGraphsBuilder_.addMessage(index, value);
}
return this;
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public Builder addFunctionGraphs(
org.tensorflow.framework.RunMetadata.FunctionGraphs.Builder builderForValue) {
if (functionGraphsBuilder_ == null) {
ensureFunctionGraphsIsMutable();
functionGraphs_.add(builderForValue.build());
onChanged();
} else {
functionGraphsBuilder_.addMessage(builderForValue.build());
}
return this;
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public Builder addFunctionGraphs(
int index, org.tensorflow.framework.RunMetadata.FunctionGraphs.Builder builderForValue) {
if (functionGraphsBuilder_ == null) {
ensureFunctionGraphsIsMutable();
functionGraphs_.add(index, builderForValue.build());
onChanged();
} else {
functionGraphsBuilder_.addMessage(index, builderForValue.build());
}
return this;
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public Builder addAllFunctionGraphs(
java.lang.Iterable values) {
if (functionGraphsBuilder_ == null) {
ensureFunctionGraphsIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(
values, functionGraphs_);
onChanged();
} else {
functionGraphsBuilder_.addAllMessages(values);
}
return this;
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public Builder clearFunctionGraphs() {
if (functionGraphsBuilder_ == null) {
functionGraphs_ = java.util.Collections.emptyList();
bitField0_ = (bitField0_ & ~0x00000008);
onChanged();
} else {
functionGraphsBuilder_.clear();
}
return this;
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public Builder removeFunctionGraphs(int index) {
if (functionGraphsBuilder_ == null) {
ensureFunctionGraphsIsMutable();
functionGraphs_.remove(index);
onChanged();
} else {
functionGraphsBuilder_.remove(index);
}
return this;
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public org.tensorflow.framework.RunMetadata.FunctionGraphs.Builder getFunctionGraphsBuilder(
int index) {
return getFunctionGraphsFieldBuilder().getBuilder(index);
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public org.tensorflow.framework.RunMetadata.FunctionGraphsOrBuilder getFunctionGraphsOrBuilder(
int index) {
if (functionGraphsBuilder_ == null) {
return functionGraphs_.get(index); } else {
return functionGraphsBuilder_.getMessageOrBuilder(index);
}
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public java.util.List
getFunctionGraphsOrBuilderList() {
if (functionGraphsBuilder_ != null) {
return functionGraphsBuilder_.getMessageOrBuilderList();
} else {
return java.util.Collections.unmodifiableList(functionGraphs_);
}
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public org.tensorflow.framework.RunMetadata.FunctionGraphs.Builder addFunctionGraphsBuilder() {
return getFunctionGraphsFieldBuilder().addBuilder(
org.tensorflow.framework.RunMetadata.FunctionGraphs.getDefaultInstance());
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public org.tensorflow.framework.RunMetadata.FunctionGraphs.Builder addFunctionGraphsBuilder(
int index) {
return getFunctionGraphsFieldBuilder().addBuilder(
index, org.tensorflow.framework.RunMetadata.FunctionGraphs.getDefaultInstance());
}
/**
*
* 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).
*
*
* repeated .tensorflow.RunMetadata.FunctionGraphs function_graphs = 4;
*/
public java.util.List
getFunctionGraphsBuilderList() {
return getFunctionGraphsFieldBuilder().getBuilderList();
}
private com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.framework.RunMetadata.FunctionGraphs, org.tensorflow.framework.RunMetadata.FunctionGraphs.Builder, org.tensorflow.framework.RunMetadata.FunctionGraphsOrBuilder>
getFunctionGraphsFieldBuilder() {
if (functionGraphsBuilder_ == null) {
functionGraphsBuilder_ = new com.google.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.framework.RunMetadata.FunctionGraphs, org.tensorflow.framework.RunMetadata.FunctionGraphs.Builder, org.tensorflow.framework.RunMetadata.FunctionGraphsOrBuilder>(
functionGraphs_,
((bitField0_ & 0x00000008) == 0x00000008),
getParentForChildren(),
isClean());
functionGraphs_ = null;
}
return functionGraphsBuilder_;
}
public final Builder setUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFieldsProto3(unknownFields);
}
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:tensorflow.RunMetadata)
}
// @@protoc_insertion_point(class_scope:tensorflow.RunMetadata)
private static final org.tensorflow.framework.RunMetadata DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new org.tensorflow.framework.RunMetadata();
}
public static org.tensorflow.framework.RunMetadata getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser
PARSER = new com.google.protobuf.AbstractParser() {
public RunMetadata parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return new RunMetadata(input, extensionRegistry);
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
public org.tensorflow.framework.RunMetadata getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
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