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// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow/core/protobuf/tensor_bundle.proto
package org.tensorflow.util;
/**
*
* Describes the metadata related to a checkpointed tensor.
*
*
* Protobuf type {@code tensorflow.BundleEntryProto}
*/
public final class BundleEntryProto extends
org.nd4j.shade.protobuf.GeneratedMessageV3 implements
// @@protoc_insertion_point(message_implements:tensorflow.BundleEntryProto)
BundleEntryProtoOrBuilder {
private static final long serialVersionUID = 0L;
// Use BundleEntryProto.newBuilder() to construct.
private BundleEntryProto(org.nd4j.shade.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private BundleEntryProto() {
dtype_ = 0;
slices_ = java.util.Collections.emptyList();
}
@java.lang.Override
@SuppressWarnings({"unused"})
protected java.lang.Object newInstance(
UnusedPrivateParameter unused) {
return new BundleEntryProto();
}
@java.lang.Override
public final org.nd4j.shade.protobuf.UnknownFieldSet
getUnknownFields() {
return this.unknownFields;
}
private BundleEntryProto(
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 8: {
int rawValue = input.readEnum();
dtype_ = rawValue;
break;
}
case 18: {
org.tensorflow.framework.TensorShapeProto.Builder subBuilder = null;
if (shape_ != null) {
subBuilder = shape_.toBuilder();
}
shape_ = input.readMessage(org.tensorflow.framework.TensorShapeProto.parser(), extensionRegistry);
if (subBuilder != null) {
subBuilder.mergeFrom(shape_);
shape_ = subBuilder.buildPartial();
}
break;
}
case 24: {
shardId_ = input.readInt32();
break;
}
case 32: {
offset_ = input.readInt64();
break;
}
case 40: {
size_ = input.readInt64();
break;
}
case 53: {
crc32C_ = input.readFixed32();
break;
}
case 58: {
if (!((mutable_bitField0_ & 0x00000001) != 0)) {
slices_ = new java.util.ArrayList();
mutable_bitField0_ |= 0x00000001;
}
slices_.add(
input.readMessage(org.tensorflow.framework.TensorSliceProto.parser(), extensionRegistry));
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)) {
slices_ = java.util.Collections.unmodifiableList(slices_);
}
this.unknownFields = unknownFields.build();
makeExtensionsImmutable();
}
}
public static final org.nd4j.shade.protobuf.Descriptors.Descriptor
getDescriptor() {
return org.tensorflow.util.TensorBundleProtos.internal_static_tensorflow_BundleEntryProto_descriptor;
}
@java.lang.Override
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return org.tensorflow.util.TensorBundleProtos.internal_static_tensorflow_BundleEntryProto_fieldAccessorTable
.ensureFieldAccessorsInitialized(
org.tensorflow.util.BundleEntryProto.class, org.tensorflow.util.BundleEntryProto.Builder.class);
}
public static final int DTYPE_FIELD_NUMBER = 1;
private int dtype_;
/**
*
* The tensor dtype and shape.
*
*
* .tensorflow.DataType dtype = 1;
* @return The enum numeric value on the wire for dtype.
*/
@java.lang.Override public int getDtypeValue() {
return dtype_;
}
/**
*
* The tensor dtype and shape.
*
*
* .tensorflow.DataType dtype = 1;
* @return The dtype.
*/
@java.lang.Override public org.tensorflow.framework.DataType getDtype() {
@SuppressWarnings("deprecation")
org.tensorflow.framework.DataType result = org.tensorflow.framework.DataType.valueOf(dtype_);
return result == null ? org.tensorflow.framework.DataType.UNRECOGNIZED : result;
}
public static final int SHAPE_FIELD_NUMBER = 2;
private org.tensorflow.framework.TensorShapeProto shape_;
/**
* .tensorflow.TensorShapeProto shape = 2;
* @return Whether the shape field is set.
*/
@java.lang.Override
public boolean hasShape() {
return shape_ != null;
}
/**
* .tensorflow.TensorShapeProto shape = 2;
* @return The shape.
*/
@java.lang.Override
public org.tensorflow.framework.TensorShapeProto getShape() {
return shape_ == null ? org.tensorflow.framework.TensorShapeProto.getDefaultInstance() : shape_;
}
/**
* .tensorflow.TensorShapeProto shape = 2;
*/
@java.lang.Override
public org.tensorflow.framework.TensorShapeProtoOrBuilder getShapeOrBuilder() {
return getShape();
}
public static final int SHARD_ID_FIELD_NUMBER = 3;
private int shardId_;
/**
*
* The binary content of the tensor lies in:
* File "shard_id": bytes [offset, offset + size).
*
*
* int32 shard_id = 3;
* @return The shardId.
*/
@java.lang.Override
public int getShardId() {
return shardId_;
}
public static final int OFFSET_FIELD_NUMBER = 4;
private long offset_;
/**
* int64 offset = 4;
* @return The offset.
*/
@java.lang.Override
public long getOffset() {
return offset_;
}
public static final int SIZE_FIELD_NUMBER = 5;
private long size_;
/**
* int64 size = 5;
* @return The size.
*/
@java.lang.Override
public long getSize() {
return size_;
}
public static final int CRC32C_FIELD_NUMBER = 6;
private int crc32C_;
/**
*
* The CRC32C checksum of the tensor bytes.
*
*
* fixed32 crc32c = 6;
* @return The crc32c.
*/
@java.lang.Override
public int getCrc32C() {
return crc32C_;
}
public static final int SLICES_FIELD_NUMBER = 7;
private java.util.List slices_;
/**
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
*
* repeated .tensorflow.TensorSliceProto slices = 7;
*/
@java.lang.Override
public int getSlicesCount() {
return slices_.size();
}
/**
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
*
* .tensorflow.DataType dtype = 1;
* @return The enum numeric value on the wire for dtype.
*/
@java.lang.Override public int getDtypeValue() {
return dtype_;
}
/**
*
* The tensor dtype and shape.
*
*
* .tensorflow.DataType dtype = 1;
* @param value The enum numeric value on the wire for dtype to set.
* @return This builder for chaining.
*/
public Builder setDtypeValue(int value) {
dtype_ = value;
onChanged();
return this;
}
/**
*
* The tensor dtype and shape.
*
*
* .tensorflow.DataType dtype = 1;
* @return The dtype.
*/
@java.lang.Override
public org.tensorflow.framework.DataType getDtype() {
@SuppressWarnings("deprecation")
org.tensorflow.framework.DataType result = org.tensorflow.framework.DataType.valueOf(dtype_);
return result == null ? org.tensorflow.framework.DataType.UNRECOGNIZED : result;
}
/**
*
* The tensor dtype and shape.
*
*
* .tensorflow.DataType dtype = 1;
* @param value The dtype to set.
* @return This builder for chaining.
*/
public Builder setDtype(org.tensorflow.framework.DataType value) {
if (value == null) {
throw new NullPointerException();
}
dtype_ = value.getNumber();
onChanged();
return this;
}
/**
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
*
* repeated .tensorflow.TensorSliceProto slices = 7;
*/
public int getSlicesCount() {
if (slicesBuilder_ == null) {
return slices_.size();
} else {
return slicesBuilder_.getCount();
}
}
/**
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
*
* repeated .tensorflow.TensorSliceProto slices = 7;
*/
public Builder setSlices(
int index, org.tensorflow.framework.TensorSliceProto value) {
if (slicesBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureSlicesIsMutable();
slices_.set(index, value);
onChanged();
} else {
slicesBuilder_.setMessage(index, value);
}
return this;
}
/**
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
*
* repeated .tensorflow.TensorSliceProto slices = 7;
*/
public Builder addSlices(org.tensorflow.framework.TensorSliceProto value) {
if (slicesBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureSlicesIsMutable();
slices_.add(value);
onChanged();
} else {
slicesBuilder_.addMessage(value);
}
return this;
}
/**
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
*
* repeated .tensorflow.TensorSliceProto slices = 7;
*/
public Builder addSlices(
int index, org.tensorflow.framework.TensorSliceProto value) {
if (slicesBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureSlicesIsMutable();
slices_.add(index, value);
onChanged();
} else {
slicesBuilder_.addMessage(index, value);
}
return this;
}
/**
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
*
* repeated .tensorflow.TensorSliceProto slices = 7;
*/
public org.tensorflow.framework.TensorSliceProto.Builder getSlicesBuilder(
int index) {
return getSlicesFieldBuilder().getBuilder(index);
}
/**
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
*
* repeated .tensorflow.TensorSliceProto slices = 7;
*/
public org.tensorflow.framework.TensorSliceProtoOrBuilder getSlicesOrBuilder(
int index) {
if (slicesBuilder_ == null) {
return slices_.get(index); } else {
return slicesBuilder_.getMessageOrBuilder(index);
}
}
/**
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
* Iff present, this entry represents a partitioned tensor. The previous
* fields are interpreted as follows:
* "dtype", "shape": describe the full tensor.
* "shard_id", "offset", "size", "crc32c": all IGNORED.
* These information for each slice can be looked up in their own
* BundleEntryProto, keyed by each "slice_name".
*
*
* repeated .tensorflow.TensorSliceProto slices = 7;
*/
public java.util.List
getSlicesBuilderList() {
return getSlicesFieldBuilder().getBuilderList();
}
private org.nd4j.shade.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.framework.TensorSliceProto, org.tensorflow.framework.TensorSliceProto.Builder, org.tensorflow.framework.TensorSliceProtoOrBuilder>
getSlicesFieldBuilder() {
if (slicesBuilder_ == null) {
slicesBuilder_ = new org.nd4j.shade.protobuf.RepeatedFieldBuilderV3<
org.tensorflow.framework.TensorSliceProto, org.tensorflow.framework.TensorSliceProto.Builder, org.tensorflow.framework.TensorSliceProtoOrBuilder>(
slices_,
((bitField0_ & 0x00000001) != 0),
getParentForChildren(),
isClean());
slices_ = null;
}
return slicesBuilder_;
}
@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.BundleEntryProto)
}
// @@protoc_insertion_point(class_scope:tensorflow.BundleEntryProto)
private static final org.tensorflow.util.BundleEntryProto DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE = new org.tensorflow.util.BundleEntryProto();
}
public static org.tensorflow.util.BundleEntryProto getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final org.nd4j.shade.protobuf.Parser
PARSER = new org.nd4j.shade.protobuf.AbstractParser() {
@java.lang.Override
public BundleEntryProto parsePartialFrom(
org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry)
throws org.nd4j.shade.protobuf.InvalidProtocolBufferException {
return new BundleEntryProto(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.util.BundleEntryProto getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}