Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance. Project price only 1 $
You can buy this project and download/modify it how often you want.
// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow/core/protobuf/named_tensor.proto
package org.tensorflow.framework;
/**
*
* A pair of tensor name and tensor values.
*
*
* Protobuf type {@code tensorflow.NamedTensorProto}
*/
public final class NamedTensorProto extends
org.nd4j.shade.protobuf.GeneratedMessageV3 implements
// @@protoc_insertion_point(message_implements:tensorflow.NamedTensorProto)
NamedTensorProtoOrBuilder {
private static final long serialVersionUID = 0L;
// Use NamedTensorProto.newBuilder() to construct.
private NamedTensorProto(org.nd4j.shade.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private NamedTensorProto() {
name_ = "";
}
@java.lang.Override
public final org.nd4j.shade.protobuf.UnknownFieldSet
getUnknownFields() {
return this.unknownFields;
}
private NamedTensorProto(
org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
this();
if (extensionRegistry == null) {
throw new java.lang.NullPointerException();
}
int mutable_bitField0_ = 0;
org.nd4j.shade.protobuf.UnknownFieldSet.Builder unknownFields =
org.nd4j.shade.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: {
java.lang.String s = input.readStringRequireUtf8();
name_ = s;
break;
}
case 18: {
org.tensorflow.framework.TensorProto.Builder subBuilder = null;
if (tensor_ != null) {
subBuilder = tensor_.toBuilder();
}
tensor_ = input.readMessage(org.tensorflow.framework.TensorProto.parser(), extensionRegistry);
if (subBuilder != null) {
subBuilder.mergeFrom(tensor_);
tensor_ = subBuilder.buildPartial();
}
break;
}
}
}
} catch (org.nd4j.shade.protobuf.InvalidProtocolBufferException e) {
throw e.setUnfinishedMessage(this);
} catch (java.io.IOException e) {
throw new org.nd4j.shade.protobuf.InvalidProtocolBufferException(
e).setUnfinishedMessage(this);
} finally {
this.unknownFields = unknownFields.build();
makeExtensionsImmutable();
}
}
public static final org.nd4j.shade.protobuf.Descriptors.Descriptor
getDescriptor() {
return org.tensorflow.framework.NamedTensorProtos.internal_static_tensorflow_NamedTensorProto_descriptor;
}
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return org.tensorflow.framework.NamedTensorProtos.internal_static_tensorflow_NamedTensorProto_fieldAccessorTable
.ensureFieldAccessorsInitialized(
org.tensorflow.framework.NamedTensorProto.class, org.tensorflow.framework.NamedTensorProto.Builder.class);
}
public static final int NAME_FIELD_NUMBER = 1;
private volatile java.lang.Object name_;
/**
*
*
* string name = 1;
*/
public org.nd4j.shade.protobuf.ByteString
getNameBytes() {
java.lang.Object ref = name_;
if (ref instanceof java.lang.String) {
org.nd4j.shade.protobuf.ByteString b =
org.nd4j.shade.protobuf.ByteString.copyFromUtf8(
(java.lang.String) ref);
name_ = b;
return b;
} else {
return (org.nd4j.shade.protobuf.ByteString) ref;
}
}
public static final int TENSOR_FIELD_NUMBER = 2;
private org.tensorflow.framework.TensorProto tensor_;
/**
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
*
* .tensorflow.TensorProto tensor = 2;
*/
public org.tensorflow.framework.TensorProtoOrBuilder getTensorOrBuilder() {
return getTensor();
}
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(org.nd4j.shade.protobuf.CodedOutputStream output)
throws java.io.IOException {
if (!getNameBytes().isEmpty()) {
org.nd4j.shade.protobuf.GeneratedMessageV3.writeString(output, 1, name_);
}
if (tensor_ != null) {
output.writeMessage(2, getTensor());
}
unknownFields.writeTo(output);
}
public int getSerializedSize() {
int size = memoizedSize;
if (size != -1) return size;
size = 0;
if (!getNameBytes().isEmpty()) {
size += org.nd4j.shade.protobuf.GeneratedMessageV3.computeStringSize(1, name_);
}
if (tensor_ != null) {
size += org.nd4j.shade.protobuf.CodedOutputStream
.computeMessageSize(2, getTensor());
}
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.NamedTensorProto)) {
return super.equals(obj);
}
org.tensorflow.framework.NamedTensorProto other = (org.tensorflow.framework.NamedTensorProto) obj;
boolean result = true;
result = result && getName()
.equals(other.getName());
result = result && (hasTensor() == other.hasTensor());
if (hasTensor()) {
result = result && getTensor()
.equals(other.getTensor());
}
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();
hash = (37 * hash) + NAME_FIELD_NUMBER;
hash = (53 * hash) + getName().hashCode();
if (hasTensor()) {
hash = (37 * hash) + TENSOR_FIELD_NUMBER;
hash = (53 * hash) + getTensor().hashCode();
}
hash = (29 * hash) + unknownFields.hashCode();
memoizedHashCode = hash;
return hash;
}
public static org.tensorflow.framework.NamedTensorProto parseFrom(
java.nio.ByteBuffer data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.NamedTensorProto parseFrom(
java.nio.ByteBuffer data,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static org.tensorflow.framework.NamedTensorProto parseFrom(
org.nd4j.shade.protobuf.ByteString data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.NamedTensorProto parseFrom(
org.nd4j.shade.protobuf.ByteString data,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static org.tensorflow.framework.NamedTensorProto parseFrom(byte[] data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.NamedTensorProto parseFrom(
byte[] data,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static org.tensorflow.framework.NamedTensorProto parseFrom(java.io.InputStream input)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input);
}
public static org.tensorflow.framework.NamedTensorProto parseFrom(
java.io.InputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input, extensionRegistry);
}
public static org.tensorflow.framework.NamedTensorProto parseDelimitedFrom(java.io.InputStream input)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseDelimitedWithIOException(PARSER, input);
}
public static org.tensorflow.framework.NamedTensorProto parseDelimitedFrom(
java.io.InputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseDelimitedWithIOException(PARSER, input, extensionRegistry);
}
public static org.tensorflow.framework.NamedTensorProto parseFrom(
org.nd4j.shade.protobuf.CodedInputStream input)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input);
}
public static org.tensorflow.framework.NamedTensorProto parseFrom(
org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return org.nd4j.shade.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.NamedTensorProto 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(
org.nd4j.shade.protobuf.GeneratedMessageV3.BuilderParent parent) {
Builder builder = new Builder(parent);
return builder;
}
/**
*
* A pair of tensor name and tensor values.
*
*
* Protobuf type {@code tensorflow.NamedTensorProto}
*/
public static final class Builder extends
org.nd4j.shade.protobuf.GeneratedMessageV3.Builder implements
// @@protoc_insertion_point(builder_implements:tensorflow.NamedTensorProto)
org.tensorflow.framework.NamedTensorProtoOrBuilder {
public static final org.nd4j.shade.protobuf.Descriptors.Descriptor
getDescriptor() {
return org.tensorflow.framework.NamedTensorProtos.internal_static_tensorflow_NamedTensorProto_descriptor;
}
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return org.tensorflow.framework.NamedTensorProtos.internal_static_tensorflow_NamedTensorProto_fieldAccessorTable
.ensureFieldAccessorsInitialized(
org.tensorflow.framework.NamedTensorProto.class, org.tensorflow.framework.NamedTensorProto.Builder.class);
}
// Construct using org.tensorflow.framework.NamedTensorProto.newBuilder()
private Builder() {
maybeForceBuilderInitialization();
}
private Builder(
org.nd4j.shade.protobuf.GeneratedMessageV3.BuilderParent parent) {
super(parent);
maybeForceBuilderInitialization();
}
private void maybeForceBuilderInitialization() {
if (org.nd4j.shade.protobuf.GeneratedMessageV3
.alwaysUseFieldBuilders) {
}
}
public Builder clear() {
super.clear();
name_ = "";
if (tensorBuilder_ == null) {
tensor_ = null;
} else {
tensor_ = null;
tensorBuilder_ = null;
}
return this;
}
public org.nd4j.shade.protobuf.Descriptors.Descriptor
getDescriptorForType() {
return org.tensorflow.framework.NamedTensorProtos.internal_static_tensorflow_NamedTensorProto_descriptor;
}
public org.tensorflow.framework.NamedTensorProto getDefaultInstanceForType() {
return org.tensorflow.framework.NamedTensorProto.getDefaultInstance();
}
public org.tensorflow.framework.NamedTensorProto build() {
org.tensorflow.framework.NamedTensorProto result = buildPartial();
if (!result.isInitialized()) {
throw newUninitializedMessageException(result);
}
return result;
}
public org.tensorflow.framework.NamedTensorProto buildPartial() {
org.tensorflow.framework.NamedTensorProto result = new org.tensorflow.framework.NamedTensorProto(this);
result.name_ = name_;
if (tensorBuilder_ == null) {
result.tensor_ = tensor_;
} else {
result.tensor_ = tensorBuilder_.build();
}
onBuilt();
return result;
}
public Builder clone() {
return (Builder) super.clone();
}
public Builder setField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
java.lang.Object value) {
return (Builder) super.setField(field, value);
}
public Builder clearField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field) {
return (Builder) super.clearField(field);
}
public Builder clearOneof(
org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof) {
return (Builder) super.clearOneof(oneof);
}
public Builder setRepeatedField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
int index, java.lang.Object value) {
return (Builder) super.setRepeatedField(field, index, value);
}
public Builder addRepeatedField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
java.lang.Object value) {
return (Builder) super.addRepeatedField(field, value);
}
public Builder mergeFrom(org.nd4j.shade.protobuf.Message other) {
if (other instanceof org.tensorflow.framework.NamedTensorProto) {
return mergeFrom((org.tensorflow.framework.NamedTensorProto)other);
} else {
super.mergeFrom(other);
return this;
}
}
public Builder mergeFrom(org.tensorflow.framework.NamedTensorProto other) {
if (other == org.tensorflow.framework.NamedTensorProto.getDefaultInstance()) return this;
if (!other.getName().isEmpty()) {
name_ = other.name_;
onChanged();
}
if (other.hasTensor()) {
mergeTensor(other.getTensor());
}
this.mergeUnknownFields(other.unknownFields);
onChanged();
return this;
}
public final boolean isInitialized() {
return true;
}
public Builder mergeFrom(
org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
org.tensorflow.framework.NamedTensorProto parsedMessage = null;
try {
parsedMessage = PARSER.parsePartialFrom(input, extensionRegistry);
} catch (org.nd4j.shade.protobuf.InvalidProtocolBufferException e) {
parsedMessage = (org.tensorflow.framework.NamedTensorProto) e.getUnfinishedMessage();
throw e.unwrapIOException();
} finally {
if (parsedMessage != null) {
mergeFrom(parsedMessage);
}
}
return this;
}
private java.lang.Object name_ = "";
/**
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
*
* .tensorflow.TensorProto tensor = 2;
*/
public Builder setTensor(org.tensorflow.framework.TensorProto value) {
if (tensorBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
tensor_ = value;
onChanged();
} else {
tensorBuilder_.setMessage(value);
}
return this;
}
/**
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
* The client can populate a TensorProto using a tensorflow::Tensor`, or
* directly using the protobuf field accessors.
* The client specifies whether the returned tensor values should be
* filled tensor fields (float_val, int_val, etc.) or encoded in a
* compact form in tensor.tensor_content.
*
*
* .tensorflow.TensorProto tensor = 2;
*/
private org.nd4j.shade.protobuf.SingleFieldBuilderV3<
org.tensorflow.framework.TensorProto, org.tensorflow.framework.TensorProto.Builder, org.tensorflow.framework.TensorProtoOrBuilder>
getTensorFieldBuilder() {
if (tensorBuilder_ == null) {
tensorBuilder_ = new org.nd4j.shade.protobuf.SingleFieldBuilderV3<
org.tensorflow.framework.TensorProto, org.tensorflow.framework.TensorProto.Builder, org.tensorflow.framework.TensorProtoOrBuilder>(
getTensor(),
getParentForChildren(),
isClean());
tensor_ = null;
}
return tensorBuilder_;
}
public final Builder setUnknownFields(
final org.nd4j.shade.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFieldsProto3(unknownFields);
}
public final Builder mergeUnknownFields(
final org.nd4j.shade.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:tensorflow.NamedTensorProto)
}
// @@protoc_insertion_point(class_scope:tensorflow.NamedTensorProto)
private static final org.tensorflow.framework.NamedTensorProto DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new org.tensorflow.framework.NamedTensorProto();
}
public static org.tensorflow.framework.NamedTensorProto getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final org.nd4j.shade.protobuf.Parser
PARSER = new org.nd4j.shade.protobuf.AbstractParser() {
public NamedTensorProto parsePartialFrom(
org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return new NamedTensorProto(input, extensionRegistry);
}
};
public static org.nd4j.shade.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public org.nd4j.shade.protobuf.Parser getParserForType() {
return PARSER;
}
public org.tensorflow.framework.NamedTensorProto getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
