org.tensorflow.tf2xla.Feed Maven / Gradle / Ivy
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// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow/compiler/tf2xla/tf2xla.proto
package org.tensorflow.tf2xla;
/**
*
* Feed represents a single feed tensor in the graph, which corresponds to an
* input argument for the generated computation.
*
*
* Protobuf type {@code tensorflow.tf2xla.Feed}
*/
public final class Feed extends
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// @@protoc_insertion_point(message_implements:tensorflow.tf2xla.Feed)
FeedOrBuilder {
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/**
* .tensorflow.tf2xla.TensorId id = 1;
*/
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/**
* .tensorflow.TensorShapeProto shape = 2;
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/**
*
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*
*
* string name = 3;
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*
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private int type_;
/**
*
* Optional data type. This is not normally required, as the graph itself
* contains this information. However, if the node being fed is an op that is
* not linked into the binary, then the type cannot be inferred from the node;
* in this case, the type should be set here.
*
*
* .tensorflow.DataType type = 4;
*/
public int getTypeValue() {
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/**
*
* Optional data type. This is not normally required, as the graph itself
* contains this information. However, if the node being fed is an op that is
* not linked into the binary, then the type cannot be inferred from the node;
* in this case, the type should be set here.
*
*
* .tensorflow.DataType type = 4;
*/
public org.tensorflow.framework.DataType getType() {
@SuppressWarnings("deprecation")
org.tensorflow.framework.DataType result = org.tensorflow.framework.DataType.valueOf(type_);
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if (isInitialized == 0) return false;
memoizedIsInitialized = 1;
return true;
}
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if (id_ != null) {
output.writeMessage(1, getId());
}
if (shape_ != null) {
output.writeMessage(2, getShape());
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if (!getNameBytes().isEmpty()) {
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if (type_ != org.tensorflow.framework.DataType.DT_INVALID.getNumber()) {
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unknownFields.writeTo(output);
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boolean result = true;
result = result && (hasId() == other.hasId());
if (hasId()) {
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result = result && (hasShape() == other.hasShape());
if (hasShape()) {
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if (hasId()) {
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public static org.tensorflow.tf2xla.Feed parseFrom(
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public static org.tensorflow.tf2xla.Feed parseFrom(
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public static org.tensorflow.tf2xla.Feed parseFrom(
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public static org.tensorflow.tf2xla.Feed parseFrom(
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public static org.tensorflow.tf2xla.Feed parseFrom(
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com.google.protobuf.ExtensionRegistryLite extensionRegistry)
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/**
*
* Feed represents a single feed tensor in the graph, which corresponds to an
* input argument for the generated computation.
*
*
* Protobuf type {@code tensorflow.tf2xla.Feed}
*/
public static final class Builder extends
com.google.protobuf.GeneratedMessageV3.Builder implements
// @@protoc_insertion_point(builder_implements:tensorflow.tf2xla.Feed)
org.tensorflow.tf2xla.FeedOrBuilder {
public static final com.google.protobuf.Descriptors.Descriptor
getDescriptor() {
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private org.tensorflow.tf2xla.TensorId id_ = null;
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/**
* .tensorflow.tf2xla.TensorId id = 1;
*/
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/**
* .tensorflow.tf2xla.TensorId id = 1;
*/
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*/
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throw new NullPointerException();
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id_ = value;
onChanged();
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idBuilder_.setMessage(value);
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/**
* .tensorflow.tf2xla.TensorId id = 1;
*/
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org.tensorflow.tf2xla.TensorId.Builder builderForValue) {
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id_ = builderForValue.build();
onChanged();
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idBuilder_.setMessage(builderForValue.build());
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}
/**
* .tensorflow.tf2xla.TensorId id = 1;
*/
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if (idBuilder_ == null) {
if (id_ != null) {
id_ =
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id_ = value;
}
onChanged();
} else {
idBuilder_.mergeFrom(value);
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return this;
}
/**
* .tensorflow.tf2xla.TensorId id = 1;
*/
public Builder clearId() {
if (idBuilder_ == null) {
id_ = null;
onChanged();
} else {
id_ = null;
idBuilder_ = null;
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return this;
}
/**
* .tensorflow.tf2xla.TensorId id = 1;
*/
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onChanged();
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}
/**
* .tensorflow.tf2xla.TensorId id = 1;
*/
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*/
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getIdFieldBuilder() {
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private org.tensorflow.framework.TensorShapeProto shape_ = null;
private com.google.protobuf.SingleFieldBuilderV3<
org.tensorflow.framework.TensorShapeProto, org.tensorflow.framework.TensorShapeProto.Builder, org.tensorflow.framework.TensorShapeProtoOrBuilder> shapeBuilder_;
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*/
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/**
* .tensorflow.TensorShapeProto shape = 2;
*/
public Builder setShape(org.tensorflow.framework.TensorShapeProto value) {
if (shapeBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
shape_ = value;
onChanged();
} else {
shapeBuilder_.setMessage(value);
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return this;
}
/**
* .tensorflow.TensorShapeProto shape = 2;
*/
public Builder setShape(
org.tensorflow.framework.TensorShapeProto.Builder builderForValue) {
if (shapeBuilder_ == null) {
shape_ = builderForValue.build();
onChanged();
} else {
shapeBuilder_.setMessage(builderForValue.build());
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return this;
}
/**
* .tensorflow.TensorShapeProto shape = 2;
*/
public Builder mergeShape(org.tensorflow.framework.TensorShapeProto value) {
if (shapeBuilder_ == null) {
if (shape_ != null) {
shape_ =
org.tensorflow.framework.TensorShapeProto.newBuilder(shape_).mergeFrom(value).buildPartial();
} else {
shape_ = value;
}
onChanged();
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shapeBuilder_.mergeFrom(value);
}
return this;
}
/**
* .tensorflow.TensorShapeProto shape = 2;
*/
public Builder clearShape() {
if (shapeBuilder_ == null) {
shape_ = null;
onChanged();
} else {
shape_ = null;
shapeBuilder_ = null;
}
return this;
}
/**
* .tensorflow.TensorShapeProto shape = 2;
*/
public org.tensorflow.framework.TensorShapeProto.Builder getShapeBuilder() {
onChanged();
return getShapeFieldBuilder().getBuilder();
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/**
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*/
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/**
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getShapeFieldBuilder() {
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isClean());
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com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8(
(java.lang.String) ref);
name_ = b;
return b;
} else {
return (com.google.protobuf.ByteString) ref;
}
}
/**
*
* Optional name for generated code.
*
*
* string name = 3;
*/
public Builder setName(
java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
name_ = value;
onChanged();
return this;
}
/**
*
* Optional name for generated code.
*
*
* string name = 3;
*/
public Builder clearName() {
name_ = getDefaultInstance().getName();
onChanged();
return this;
}
/**
*
* Optional name for generated code.
*
*
* string name = 3;
*/
public Builder setNameBytes(
com.google.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
name_ = value;
onChanged();
return this;
}
private int type_ = 0;
/**
*
* Optional data type. This is not normally required, as the graph itself
* contains this information. However, if the node being fed is an op that is
* not linked into the binary, then the type cannot be inferred from the node;
* in this case, the type should be set here.
*
*
* .tensorflow.DataType type = 4;
*/
public int getTypeValue() {
return type_;
}
/**
*
* Optional data type. This is not normally required, as the graph itself
* contains this information. However, if the node being fed is an op that is
* not linked into the binary, then the type cannot be inferred from the node;
* in this case, the type should be set here.
*
*
* .tensorflow.DataType type = 4;
*/
public Builder setTypeValue(int value) {
type_ = value;
onChanged();
return this;
}
/**
*
* Optional data type. This is not normally required, as the graph itself
* contains this information. However, if the node being fed is an op that is
* not linked into the binary, then the type cannot be inferred from the node;
* in this case, the type should be set here.
*
*
* .tensorflow.DataType type = 4;
*/
public org.tensorflow.framework.DataType getType() {
@SuppressWarnings("deprecation")
org.tensorflow.framework.DataType result = org.tensorflow.framework.DataType.valueOf(type_);
return result == null ? org.tensorflow.framework.DataType.UNRECOGNIZED : result;
}
/**
*
* Optional data type. This is not normally required, as the graph itself
* contains this information. However, if the node being fed is an op that is
* not linked into the binary, then the type cannot be inferred from the node;
* in this case, the type should be set here.
*
*
* .tensorflow.DataType type = 4;
*/
public Builder setType(org.tensorflow.framework.DataType value) {
if (value == null) {
throw new NullPointerException();
}
type_ = value.getNumber();
onChanged();
return this;
}
/**
*
* Optional data type. This is not normally required, as the graph itself
* contains this information. However, if the node being fed is an op that is
* not linked into the binary, then the type cannot be inferred from the node;
* in this case, the type should be set here.
*
*
* .tensorflow.DataType type = 4;
*/
public Builder clearType() {
type_ = 0;
onChanged();
return this;
}
@java.lang.Override
public final Builder setUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFieldsProto3(unknownFields);
}
@java.lang.Override
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:tensorflow.tf2xla.Feed)
}
// @@protoc_insertion_point(class_scope:tensorflow.tf2xla.Feed)
private static final org.tensorflow.tf2xla.Feed DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new org.tensorflow.tf2xla.Feed();
}
public static org.tensorflow.tf2xla.Feed getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser
PARSER = new com.google.protobuf.AbstractParser() {
@java.lang.Override
public Feed parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return new Feed(input, extensionRegistry);
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public org.tensorflow.tf2xla.Feed getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
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