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/framework/node_def.proto
package org.tensorflow.framework;
/**
* Protobuf type {@code tensorflow.NodeDef}
*/
public final class NodeDef extends
org.nd4j.shade.protobuf.GeneratedMessageV3 implements
// @@protoc_insertion_point(message_implements:tensorflow.NodeDef)
NodeDefOrBuilder {
private static final long serialVersionUID = 0L;
// Use NodeDef.newBuilder() to construct.
private NodeDef(org.nd4j.shade.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private NodeDef() {
name_ = "";
op_ = "";
input_ = org.nd4j.shade.protobuf.LazyStringArrayList.EMPTY;
device_ = "";
}
@java.lang.Override
@SuppressWarnings({"unused"})
protected java.lang.Object newInstance(
UnusedPrivateParameter unused) {
return new NodeDef();
}
@java.lang.Override
public final org.nd4j.shade.protobuf.UnknownFieldSet
getUnknownFields() {
return this.unknownFields;
}
private NodeDef(
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;
case 10: {
java.lang.String s = input.readStringRequireUtf8();
name_ = s;
break;
}
case 18: {
java.lang.String s = input.readStringRequireUtf8();
op_ = s;
break;
}
case 26: {
java.lang.String s = input.readStringRequireUtf8();
if (!((mutable_bitField0_ & 0x00000001) != 0)) {
input_ = new org.nd4j.shade.protobuf.LazyStringArrayList();
mutable_bitField0_ |= 0x00000001;
}
input_.add(s);
break;
}
case 34: {
java.lang.String s = input.readStringRequireUtf8();
device_ = s;
break;
}
case 42: {
if (!((mutable_bitField0_ & 0x00000002) != 0)) {
attr_ = org.nd4j.shade.protobuf.MapField.newMapField(
AttrDefaultEntryHolder.defaultEntry);
mutable_bitField0_ |= 0x00000002;
}
org.nd4j.shade.protobuf.MapEntry
attr__ = input.readMessage(
AttrDefaultEntryHolder.defaultEntry.getParserForType(), extensionRegistry);
attr_.getMutableMap().put(
attr__.getKey(), attr__.getValue());
break;
}
default: {
if (!parseUnknownField(
input, unknownFields, extensionRegistry, tag)) {
done = true;
}
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 {
if (((mutable_bitField0_ & 0x00000001) != 0)) {
input_ = input_.getUnmodifiableView();
}
this.unknownFields = unknownFields.build();
makeExtensionsImmutable();
}
}
public static final org.nd4j.shade.protobuf.Descriptors.Descriptor
getDescriptor() {
return org.tensorflow.framework.NodeProto.internal_static_tensorflow_NodeDef_descriptor;
}
@SuppressWarnings({"rawtypes"})
@java.lang.Override
protected org.nd4j.shade.protobuf.MapField internalGetMapField(
int number) {
switch (number) {
case 5:
return internalGetAttr();
default:
throw new RuntimeException(
"Invalid map field number: " + number);
}
}
@java.lang.Override
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return org.tensorflow.framework.NodeProto.internal_static_tensorflow_NodeDef_fieldAccessorTable
.ensureFieldAccessorsInitialized(
org.tensorflow.framework.NodeDef.class, org.tensorflow.framework.NodeDef.Builder.class);
}
public static final int NAME_FIELD_NUMBER = 1;
private volatile java.lang.Object name_;
/**
*
* The name given to this operator. Used for naming inputs,
* logging, visualization, etc. Unique within a single GraphDef.
* Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_./]*".
*
* The name given to this operator. Used for naming inputs,
* logging, visualization, etc. Unique within a single GraphDef.
* Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_./]*".
*
*
* 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 OP_FIELD_NUMBER = 2;
private volatile java.lang.Object op_;
/**
*
* The operation name. There may be custom parameters in attrs.
* Op names starting with an underscore are reserved for internal use.
*
* The operation name. There may be custom parameters in attrs.
* Op names starting with an underscore are reserved for internal use.
*
*
* string op = 2;
*/
public org.nd4j.shade.protobuf.ByteString
getOpBytes() {
java.lang.Object ref = op_;
if (ref instanceof java.lang.String) {
org.nd4j.shade.protobuf.ByteString b =
org.nd4j.shade.protobuf.ByteString.copyFromUtf8(
(java.lang.String) ref);
op_ = b;
return b;
} else {
return (org.nd4j.shade.protobuf.ByteString) ref;
}
}
public static final int INPUT_FIELD_NUMBER = 3;
private org.nd4j.shade.protobuf.LazyStringList input_;
/**
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
*
* repeated string input = 3;
*/
public int getInputCount() {
return input_.size();
}
/**
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
*
* repeated string input = 3;
*/
public org.nd4j.shade.protobuf.ByteString
getInputBytes(int index) {
return input_.getByteString(index);
}
public static final int DEVICE_FIELD_NUMBER = 4;
private volatile java.lang.Object device_;
/**
*
* A (possibly partial) specification for the device on which this
* node should be placed.
* The expected syntax for this string is as follows:
* DEVICE_SPEC ::= PARTIAL_SPEC
* PARTIAL_SPEC ::= ("/" CONSTRAINT) *
* CONSTRAINT ::= ("job:" JOB_NAME)
* | ("replica:" [1-9][0-9]*)
* | ("task:" [1-9][0-9]*)
* | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
* Valid values for this string include:
* * "/job:worker/replica:0/task:1/device:GPU:3" (full specification)
* * "/job:worker/device:GPU:3" (partial specification)
* * "" (no specification)
* If the constraints do not resolve to a single device (or if this
* field is empty or not present), the runtime will attempt to
* choose a device automatically.
*
* A (possibly partial) specification for the device on which this
* node should be placed.
* The expected syntax for this string is as follows:
* DEVICE_SPEC ::= PARTIAL_SPEC
* PARTIAL_SPEC ::= ("/" CONSTRAINT) *
* CONSTRAINT ::= ("job:" JOB_NAME)
* | ("replica:" [1-9][0-9]*)
* | ("task:" [1-9][0-9]*)
* | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
* Valid values for this string include:
* * "/job:worker/replica:0/task:1/device:GPU:3" (full specification)
* * "/job:worker/device:GPU:3" (partial specification)
* * "" (no specification)
* If the constraints do not resolve to a single device (or if this
* field is empty or not present), the runtime will attempt to
* choose a device automatically.
*
*
* string device = 4;
*/
public org.nd4j.shade.protobuf.ByteString
getDeviceBytes() {
java.lang.Object ref = device_;
if (ref instanceof java.lang.String) {
org.nd4j.shade.protobuf.ByteString b =
org.nd4j.shade.protobuf.ByteString.copyFromUtf8(
(java.lang.String) ref);
device_ = b;
return b;
} else {
return (org.nd4j.shade.protobuf.ByteString) ref;
}
}
public static final int ATTR_FIELD_NUMBER = 5;
private static final class AttrDefaultEntryHolder {
static final org.nd4j.shade.protobuf.MapEntry<
java.lang.String, org.tensorflow.framework.AttrValue> defaultEntry =
org.nd4j.shade.protobuf.MapEntry
.newDefaultInstance(
org.tensorflow.framework.NodeProto.internal_static_tensorflow_NodeDef_AttrEntry_descriptor,
org.nd4j.shade.protobuf.WireFormat.FieldType.STRING,
"",
org.nd4j.shade.protobuf.WireFormat.FieldType.MESSAGE,
org.tensorflow.framework.AttrValue.getDefaultInstance());
}
private org.nd4j.shade.protobuf.MapField<
java.lang.String, org.tensorflow.framework.AttrValue> attr_;
private org.nd4j.shade.protobuf.MapField
internalGetAttr() {
if (attr_ == null) {
return org.nd4j.shade.protobuf.MapField.emptyMapField(
AttrDefaultEntryHolder.defaultEntry);
}
return attr_;
}
public int getAttrCount() {
return internalGetAttr().getMap().size();
}
/**
*
* Operation-specific graph-construction-time configuration.
* Note that this should include all attrs defined in the
* corresponding OpDef, including those with a value matching
* the default -- this allows the default to change and makes
* NodeDefs easier to interpret on their own. However, if
* an attr with a default is not specified in this list, the
* default will be used.
* The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
* one of the names from the corresponding OpDef's attr field).
* The values must have a type matching the corresponding OpDef
* attr's type field.
* TODO(josh11b): Add some examples here showing best practices.
*
*
* map<string, .tensorflow.AttrValue> attr = 5;
*/
public boolean containsAttr(
java.lang.String key) {
if (key == null) { throw new java.lang.NullPointerException(); }
return internalGetAttr().getMap().containsKey(key);
}
/**
* Use {@link #getAttrMap()} instead.
*/
@java.lang.Deprecated
public java.util.Map getAttr() {
return getAttrMap();
}
/**
*
* Operation-specific graph-construction-time configuration.
* Note that this should include all attrs defined in the
* corresponding OpDef, including those with a value matching
* the default -- this allows the default to change and makes
* NodeDefs easier to interpret on their own. However, if
* an attr with a default is not specified in this list, the
* default will be used.
* The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
* one of the names from the corresponding OpDef's attr field).
* The values must have a type matching the corresponding OpDef
* attr's type field.
* TODO(josh11b): Add some examples here showing best practices.
*
* Operation-specific graph-construction-time configuration.
* Note that this should include all attrs defined in the
* corresponding OpDef, including those with a value matching
* the default -- this allows the default to change and makes
* NodeDefs easier to interpret on their own. However, if
* an attr with a default is not specified in this list, the
* default will be used.
* The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
* one of the names from the corresponding OpDef's attr field).
* The values must have a type matching the corresponding OpDef
* attr's type field.
* TODO(josh11b): Add some examples here showing best practices.
*
* Operation-specific graph-construction-time configuration.
* Note that this should include all attrs defined in the
* corresponding OpDef, including those with a value matching
* the default -- this allows the default to change and makes
* NodeDefs easier to interpret on their own. However, if
* an attr with a default is not specified in this list, the
* default will be used.
* The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
* one of the names from the corresponding OpDef's attr field).
* The values must have a type matching the corresponding OpDef
* attr's type field.
* TODO(josh11b): Add some examples here showing best practices.
*
*
* map<string, .tensorflow.AttrValue> attr = 5;
*/
public org.tensorflow.framework.AttrValue getAttrOrThrow(
java.lang.String key) {
if (key == null) { throw new java.lang.NullPointerException(); }
java.util.Map map =
internalGetAttr().getMap();
if (!map.containsKey(key)) {
throw new java.lang.IllegalArgumentException();
}
return map.get(key);
}
private byte memoizedIsInitialized = -1;
@java.lang.Override
public final boolean isInitialized() {
byte isInitialized = memoizedIsInitialized;
if (isInitialized == 1) return true;
if (isInitialized == 0) return false;
memoizedIsInitialized = 1;
return true;
}
@java.lang.Override
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 (!getOpBytes().isEmpty()) {
org.nd4j.shade.protobuf.GeneratedMessageV3.writeString(output, 2, op_);
}
for (int i = 0; i < input_.size(); i++) {
org.nd4j.shade.protobuf.GeneratedMessageV3.writeString(output, 3, input_.getRaw(i));
}
if (!getDeviceBytes().isEmpty()) {
org.nd4j.shade.protobuf.GeneratedMessageV3.writeString(output, 4, device_);
}
org.nd4j.shade.protobuf.GeneratedMessageV3
.serializeStringMapTo(
output,
internalGetAttr(),
AttrDefaultEntryHolder.defaultEntry,
5);
unknownFields.writeTo(output);
}
@java.lang.Override
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 (!getOpBytes().isEmpty()) {
size += org.nd4j.shade.protobuf.GeneratedMessageV3.computeStringSize(2, op_);
}
{
int dataSize = 0;
for (int i = 0; i < input_.size(); i++) {
dataSize += computeStringSizeNoTag(input_.getRaw(i));
}
size += dataSize;
size += 1 * getInputList().size();
}
if (!getDeviceBytes().isEmpty()) {
size += org.nd4j.shade.protobuf.GeneratedMessageV3.computeStringSize(4, device_);
}
for (java.util.Map.Entry entry
: internalGetAttr().getMap().entrySet()) {
org.nd4j.shade.protobuf.MapEntry
attr__ = AttrDefaultEntryHolder.defaultEntry.newBuilderForType()
.setKey(entry.getKey())
.setValue(entry.getValue())
.build();
size += org.nd4j.shade.protobuf.CodedOutputStream
.computeMessageSize(5, attr__);
}
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.NodeDef)) {
return super.equals(obj);
}
org.tensorflow.framework.NodeDef other = (org.tensorflow.framework.NodeDef) obj;
if (!getName()
.equals(other.getName())) return false;
if (!getOp()
.equals(other.getOp())) return false;
if (!getInputList()
.equals(other.getInputList())) return false;
if (!getDevice()
.equals(other.getDevice())) return false;
if (!internalGetAttr().equals(
other.internalGetAttr())) return false;
if (!unknownFields.equals(other.unknownFields)) return false;
return true;
}
@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();
hash = (37 * hash) + OP_FIELD_NUMBER;
hash = (53 * hash) + getOp().hashCode();
if (getInputCount() > 0) {
hash = (37 * hash) + INPUT_FIELD_NUMBER;
hash = (53 * hash) + getInputList().hashCode();
}
hash = (37 * hash) + DEVICE_FIELD_NUMBER;
hash = (53 * hash) + getDevice().hashCode();
if (!internalGetAttr().getMap().isEmpty()) {
hash = (37 * hash) + ATTR_FIELD_NUMBER;
hash = (53 * hash) + internalGetAttr().hashCode();
}
hash = (29 * hash) + unknownFields.hashCode();
memoizedHashCode = hash;
return hash;
}
public static org.tensorflow.framework.NodeDef parseFrom(
java.nio.ByteBuffer data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.NodeDef 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.NodeDef parseFrom(
org.nd4j.shade.protobuf.ByteString data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.NodeDef 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.NodeDef parseFrom(byte[] data)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static org.tensorflow.framework.NodeDef 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.NodeDef parseFrom(java.io.InputStream input)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseWithIOException(PARSER, input);
}
public static org.tensorflow.framework.NodeDef 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.NodeDef parseDelimitedFrom(java.io.InputStream input)
throws java.io.IOException {
return org.nd4j.shade.protobuf.GeneratedMessageV3
.parseDelimitedWithIOException(PARSER, input);
}
public static org.tensorflow.framework.NodeDef 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.NodeDef 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.NodeDef 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);
}
@java.lang.Override
public Builder newBuilderForType() { return newBuilder(); }
public static Builder newBuilder() {
return DEFAULT_INSTANCE.toBuilder();
}
public static Builder newBuilder(org.tensorflow.framework.NodeDef prototype) {
return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype);
}
@java.lang.Override
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;
}
/**
* Protobuf type {@code tensorflow.NodeDef}
*/
public static final class Builder extends
org.nd4j.shade.protobuf.GeneratedMessageV3.Builder implements
// @@protoc_insertion_point(builder_implements:tensorflow.NodeDef)
org.tensorflow.framework.NodeDefOrBuilder {
public static final org.nd4j.shade.protobuf.Descriptors.Descriptor
getDescriptor() {
return org.tensorflow.framework.NodeProto.internal_static_tensorflow_NodeDef_descriptor;
}
@SuppressWarnings({"rawtypes"})
protected org.nd4j.shade.protobuf.MapField internalGetMapField(
int number) {
switch (number) {
case 5:
return internalGetAttr();
default:
throw new RuntimeException(
"Invalid map field number: " + number);
}
}
@SuppressWarnings({"rawtypes"})
protected org.nd4j.shade.protobuf.MapField internalGetMutableMapField(
int number) {
switch (number) {
case 5:
return internalGetMutableAttr();
default:
throw new RuntimeException(
"Invalid map field number: " + number);
}
}
@java.lang.Override
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return org.tensorflow.framework.NodeProto.internal_static_tensorflow_NodeDef_fieldAccessorTable
.ensureFieldAccessorsInitialized(
org.tensorflow.framework.NodeDef.class, org.tensorflow.framework.NodeDef.Builder.class);
}
// Construct using org.tensorflow.framework.NodeDef.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) {
}
}
@java.lang.Override
public Builder clear() {
super.clear();
name_ = "";
op_ = "";
input_ = org.nd4j.shade.protobuf.LazyStringArrayList.EMPTY;
bitField0_ = (bitField0_ & ~0x00000001);
device_ = "";
internalGetMutableAttr().clear();
return this;
}
@java.lang.Override
public org.nd4j.shade.protobuf.Descriptors.Descriptor
getDescriptorForType() {
return org.tensorflow.framework.NodeProto.internal_static_tensorflow_NodeDef_descriptor;
}
@java.lang.Override
public org.tensorflow.framework.NodeDef getDefaultInstanceForType() {
return org.tensorflow.framework.NodeDef.getDefaultInstance();
}
@java.lang.Override
public org.tensorflow.framework.NodeDef build() {
org.tensorflow.framework.NodeDef result = buildPartial();
if (!result.isInitialized()) {
throw newUninitializedMessageException(result);
}
return result;
}
@java.lang.Override
public org.tensorflow.framework.NodeDef buildPartial() {
org.tensorflow.framework.NodeDef result = new org.tensorflow.framework.NodeDef(this);
int from_bitField0_ = bitField0_;
result.name_ = name_;
result.op_ = op_;
if (((bitField0_ & 0x00000001) != 0)) {
input_ = input_.getUnmodifiableView();
bitField0_ = (bitField0_ & ~0x00000001);
}
result.input_ = input_;
result.device_ = device_;
result.attr_ = internalGetAttr();
result.attr_.makeImmutable();
onBuilt();
return result;
}
@java.lang.Override
public Builder clone() {
return super.clone();
}
@java.lang.Override
public Builder setField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
java.lang.Object value) {
return super.setField(field, value);
}
@java.lang.Override
public Builder clearField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field) {
return super.clearField(field);
}
@java.lang.Override
public Builder clearOneof(
org.nd4j.shade.protobuf.Descriptors.OneofDescriptor oneof) {
return super.clearOneof(oneof);
}
@java.lang.Override
public Builder setRepeatedField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
int index, java.lang.Object value) {
return super.setRepeatedField(field, index, value);
}
@java.lang.Override
public Builder addRepeatedField(
org.nd4j.shade.protobuf.Descriptors.FieldDescriptor field,
java.lang.Object value) {
return super.addRepeatedField(field, value);
}
@java.lang.Override
public Builder mergeFrom(org.nd4j.shade.protobuf.Message other) {
if (other instanceof org.tensorflow.framework.NodeDef) {
return mergeFrom((org.tensorflow.framework.NodeDef)other);
} else {
super.mergeFrom(other);
return this;
}
}
public Builder mergeFrom(org.tensorflow.framework.NodeDef other) {
if (other == org.tensorflow.framework.NodeDef.getDefaultInstance()) return this;
if (!other.getName().isEmpty()) {
name_ = other.name_;
onChanged();
}
if (!other.getOp().isEmpty()) {
op_ = other.op_;
onChanged();
}
if (!other.input_.isEmpty()) {
if (input_.isEmpty()) {
input_ = other.input_;
bitField0_ = (bitField0_ & ~0x00000001);
} else {
ensureInputIsMutable();
input_.addAll(other.input_);
}
onChanged();
}
if (!other.getDevice().isEmpty()) {
device_ = other.device_;
onChanged();
}
internalGetMutableAttr().mergeFrom(
other.internalGetAttr());
this.mergeUnknownFields(other.unknownFields);
onChanged();
return this;
}
@java.lang.Override
public final boolean isInitialized() {
return true;
}
@java.lang.Override
public Builder mergeFrom(
org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
org.tensorflow.framework.NodeDef parsedMessage = null;
try {
parsedMessage = PARSER.parsePartialFrom(input, extensionRegistry);
} catch (org.nd4j.shade.protobuf.InvalidProtocolBufferException e) {
parsedMessage = (org.tensorflow.framework.NodeDef) e.getUnfinishedMessage();
throw e.unwrapIOException();
} finally {
if (parsedMessage != null) {
mergeFrom(parsedMessage);
}
}
return this;
}
private int bitField0_;
private java.lang.Object name_ = "";
/**
*
* The name given to this operator. Used for naming inputs,
* logging, visualization, etc. Unique within a single GraphDef.
* Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_./]*".
*
* The name given to this operator. Used for naming inputs,
* logging, visualization, etc. Unique within a single GraphDef.
* Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_./]*".
*
* The name given to this operator. Used for naming inputs,
* logging, visualization, etc. Unique within a single GraphDef.
* Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_./]*".
*
*
* string name = 1;
*/
public Builder setName(
java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
name_ = value;
onChanged();
return this;
}
/**
*
* The name given to this operator. Used for naming inputs,
* logging, visualization, etc. Unique within a single GraphDef.
* Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_./]*".
*
*
* string name = 1;
*/
public Builder clearName() {
name_ = getDefaultInstance().getName();
onChanged();
return this;
}
/**
*
* The name given to this operator. Used for naming inputs,
* logging, visualization, etc. Unique within a single GraphDef.
* Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_./]*".
*
*
* string name = 1;
*/
public Builder setNameBytes(
org.nd4j.shade.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
name_ = value;
onChanged();
return this;
}
private java.lang.Object op_ = "";
/**
*
* The operation name. There may be custom parameters in attrs.
* Op names starting with an underscore are reserved for internal use.
*
* The operation name. There may be custom parameters in attrs.
* Op names starting with an underscore are reserved for internal use.
*
*
* string op = 2;
*/
public Builder setOp(
java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
op_ = value;
onChanged();
return this;
}
/**
*
* The operation name. There may be custom parameters in attrs.
* Op names starting with an underscore are reserved for internal use.
*
*
* string op = 2;
*/
public Builder clearOp() {
op_ = getDefaultInstance().getOp();
onChanged();
return this;
}
/**
*
* The operation name. There may be custom parameters in attrs.
* Op names starting with an underscore are reserved for internal use.
*
*
* string op = 2;
*/
public Builder setOpBytes(
org.nd4j.shade.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
op_ = value;
onChanged();
return this;
}
private org.nd4j.shade.protobuf.LazyStringList input_ = org.nd4j.shade.protobuf.LazyStringArrayList.EMPTY;
private void ensureInputIsMutable() {
if (!((bitField0_ & 0x00000001) != 0)) {
input_ = new org.nd4j.shade.protobuf.LazyStringArrayList(input_);
bitField0_ |= 0x00000001;
}
}
/**
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
*
* repeated string input = 3;
*/
public int getInputCount() {
return input_.size();
}
/**
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
*
* repeated string input = 3;
*/
public Builder setInput(
int index, java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
ensureInputIsMutable();
input_.set(index, value);
onChanged();
return this;
}
/**
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
* Each input is "node:src_output" with "node" being a string name and
* "src_output" indicating which output tensor to use from "node". If
* "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
* may optionally be followed by control inputs that have the format
* "^node".
*
* A (possibly partial) specification for the device on which this
* node should be placed.
* The expected syntax for this string is as follows:
* DEVICE_SPEC ::= PARTIAL_SPEC
* PARTIAL_SPEC ::= ("/" CONSTRAINT) *
* CONSTRAINT ::= ("job:" JOB_NAME)
* | ("replica:" [1-9][0-9]*)
* | ("task:" [1-9][0-9]*)
* | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
* Valid values for this string include:
* * "/job:worker/replica:0/task:1/device:GPU:3" (full specification)
* * "/job:worker/device:GPU:3" (partial specification)
* * "" (no specification)
* If the constraints do not resolve to a single device (or if this
* field is empty or not present), the runtime will attempt to
* choose a device automatically.
*
* A (possibly partial) specification for the device on which this
* node should be placed.
* The expected syntax for this string is as follows:
* DEVICE_SPEC ::= PARTIAL_SPEC
* PARTIAL_SPEC ::= ("/" CONSTRAINT) *
* CONSTRAINT ::= ("job:" JOB_NAME)
* | ("replica:" [1-9][0-9]*)
* | ("task:" [1-9][0-9]*)
* | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
* Valid values for this string include:
* * "/job:worker/replica:0/task:1/device:GPU:3" (full specification)
* * "/job:worker/device:GPU:3" (partial specification)
* * "" (no specification)
* If the constraints do not resolve to a single device (or if this
* field is empty or not present), the runtime will attempt to
* choose a device automatically.
*
* A (possibly partial) specification for the device on which this
* node should be placed.
* The expected syntax for this string is as follows:
* DEVICE_SPEC ::= PARTIAL_SPEC
* PARTIAL_SPEC ::= ("/" CONSTRAINT) *
* CONSTRAINT ::= ("job:" JOB_NAME)
* | ("replica:" [1-9][0-9]*)
* | ("task:" [1-9][0-9]*)
* | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
* Valid values for this string include:
* * "/job:worker/replica:0/task:1/device:GPU:3" (full specification)
* * "/job:worker/device:GPU:3" (partial specification)
* * "" (no specification)
* If the constraints do not resolve to a single device (or if this
* field is empty or not present), the runtime will attempt to
* choose a device automatically.
*
* A (possibly partial) specification for the device on which this
* node should be placed.
* The expected syntax for this string is as follows:
* DEVICE_SPEC ::= PARTIAL_SPEC
* PARTIAL_SPEC ::= ("/" CONSTRAINT) *
* CONSTRAINT ::= ("job:" JOB_NAME)
* | ("replica:" [1-9][0-9]*)
* | ("task:" [1-9][0-9]*)
* | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
* Valid values for this string include:
* * "/job:worker/replica:0/task:1/device:GPU:3" (full specification)
* * "/job:worker/device:GPU:3" (partial specification)
* * "" (no specification)
* If the constraints do not resolve to a single device (or if this
* field is empty or not present), the runtime will attempt to
* choose a device automatically.
*
* A (possibly partial) specification for the device on which this
* node should be placed.
* The expected syntax for this string is as follows:
* DEVICE_SPEC ::= PARTIAL_SPEC
* PARTIAL_SPEC ::= ("/" CONSTRAINT) *
* CONSTRAINT ::= ("job:" JOB_NAME)
* | ("replica:" [1-9][0-9]*)
* | ("task:" [1-9][0-9]*)
* | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
* Valid values for this string include:
* * "/job:worker/replica:0/task:1/device:GPU:3" (full specification)
* * "/job:worker/device:GPU:3" (partial specification)
* * "" (no specification)
* If the constraints do not resolve to a single device (or if this
* field is empty or not present), the runtime will attempt to
* choose a device automatically.
*
* Operation-specific graph-construction-time configuration.
* Note that this should include all attrs defined in the
* corresponding OpDef, including those with a value matching
* the default -- this allows the default to change and makes
* NodeDefs easier to interpret on their own. However, if
* an attr with a default is not specified in this list, the
* default will be used.
* The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
* one of the names from the corresponding OpDef's attr field).
* The values must have a type matching the corresponding OpDef
* attr's type field.
* TODO(josh11b): Add some examples here showing best practices.
*
*
* map<string, .tensorflow.AttrValue> attr = 5;
*/
public boolean containsAttr(
java.lang.String key) {
if (key == null) { throw new java.lang.NullPointerException(); }
return internalGetAttr().getMap().containsKey(key);
}
/**
* Use {@link #getAttrMap()} instead.
*/
@java.lang.Deprecated
public java.util.Map getAttr() {
return getAttrMap();
}
/**
*
* Operation-specific graph-construction-time configuration.
* Note that this should include all attrs defined in the
* corresponding OpDef, including those with a value matching
* the default -- this allows the default to change and makes
* NodeDefs easier to interpret on their own. However, if
* an attr with a default is not specified in this list, the
* default will be used.
* The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
* one of the names from the corresponding OpDef's attr field).
* The values must have a type matching the corresponding OpDef
* attr's type field.
* TODO(josh11b): Add some examples here showing best practices.
*
* Operation-specific graph-construction-time configuration.
* Note that this should include all attrs defined in the
* corresponding OpDef, including those with a value matching
* the default -- this allows the default to change and makes
* NodeDefs easier to interpret on their own. However, if
* an attr with a default is not specified in this list, the
* default will be used.
* The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
* one of the names from the corresponding OpDef's attr field).
* The values must have a type matching the corresponding OpDef
* attr's type field.
* TODO(josh11b): Add some examples here showing best practices.
*
* Operation-specific graph-construction-time configuration.
* Note that this should include all attrs defined in the
* corresponding OpDef, including those with a value matching
* the default -- this allows the default to change and makes
* NodeDefs easier to interpret on their own. However, if
* an attr with a default is not specified in this list, the
* default will be used.
* The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
* one of the names from the corresponding OpDef's attr field).
* The values must have a type matching the corresponding OpDef
* attr's type field.
* TODO(josh11b): Add some examples here showing best practices.
*
*
* map<string, .tensorflow.AttrValue> attr = 5;
*/
public org.tensorflow.framework.AttrValue getAttrOrThrow(
java.lang.String key) {
if (key == null) { throw new java.lang.NullPointerException(); }
java.util.Map map =
internalGetAttr().getMap();
if (!map.containsKey(key)) {
throw new java.lang.IllegalArgumentException();
}
return map.get(key);
}
public Builder clearAttr() {
internalGetMutableAttr().getMutableMap()
.clear();
return this;
}
/**
*
* Operation-specific graph-construction-time configuration.
* Note that this should include all attrs defined in the
* corresponding OpDef, including those with a value matching
* the default -- this allows the default to change and makes
* NodeDefs easier to interpret on their own. However, if
* an attr with a default is not specified in this list, the
* default will be used.
* The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
* one of the names from the corresponding OpDef's attr field).
* The values must have a type matching the corresponding OpDef
* attr's type field.
* TODO(josh11b): Add some examples here showing best practices.
*
*
* map<string, .tensorflow.AttrValue> attr = 5;
*/
public Builder removeAttr(
java.lang.String key) {
if (key == null) { throw new java.lang.NullPointerException(); }
internalGetMutableAttr().getMutableMap()
.remove(key);
return this;
}
/**
* Use alternate mutation accessors instead.
*/
@java.lang.Deprecated
public java.util.Map
getMutableAttr() {
return internalGetMutableAttr().getMutableMap();
}
/**
*
* Operation-specific graph-construction-time configuration.
* Note that this should include all attrs defined in the
* corresponding OpDef, including those with a value matching
* the default -- this allows the default to change and makes
* NodeDefs easier to interpret on their own. However, if
* an attr with a default is not specified in this list, the
* default will be used.
* The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
* one of the names from the corresponding OpDef's attr field).
* The values must have a type matching the corresponding OpDef
* attr's type field.
* TODO(josh11b): Add some examples here showing best practices.
*
*
* map<string, .tensorflow.AttrValue> attr = 5;
*/
public Builder putAttr(
java.lang.String key,
org.tensorflow.framework.AttrValue value) {
if (key == null) { throw new java.lang.NullPointerException(); }
if (value == null) { throw new java.lang.NullPointerException(); }
internalGetMutableAttr().getMutableMap()
.put(key, value);
return this;
}
/**
*
* Operation-specific graph-construction-time configuration.
* Note that this should include all attrs defined in the
* corresponding OpDef, including those with a value matching
* the default -- this allows the default to change and makes
* NodeDefs easier to interpret on their own. However, if
* an attr with a default is not specified in this list, the
* default will be used.
* The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
* one of the names from the corresponding OpDef's attr field).
* The values must have a type matching the corresponding OpDef
* attr's type field.
* TODO(josh11b): Add some examples here showing best practices.
*
*
* map<string, .tensorflow.AttrValue> attr = 5;
*/
public Builder putAllAttr(
java.util.Map values) {
internalGetMutableAttr().getMutableMap()
.putAll(values);
return this;
}
@java.lang.Override
public final Builder setUnknownFields(
final org.nd4j.shade.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFields(unknownFields);
}
@java.lang.Override
public final Builder mergeUnknownFields(
final org.nd4j.shade.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:tensorflow.NodeDef)
}
// @@protoc_insertion_point(class_scope:tensorflow.NodeDef)
private static final org.tensorflow.framework.NodeDef DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new org.tensorflow.framework.NodeDef();
}
public static org.tensorflow.framework.NodeDef getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final org.nd4j.shade.protobuf.Parser
PARSER = new org.nd4j.shade.protobuf.AbstractParser() {
@java.lang.Override
public NodeDef parsePartialFrom(
org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return new NodeDef(input, extensionRegistry);
}
};
public static org.nd4j.shade.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public org.nd4j.shade.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public org.tensorflow.framework.NodeDef getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
