SparseTensorIndexCSF.java
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.arrow.flatbuf;
import com.google.flatbuffers.BaseVector;
import com.google.flatbuffers.BooleanVector;
import com.google.flatbuffers.ByteVector;
import com.google.flatbuffers.Constants;
import com.google.flatbuffers.DoubleVector;
import com.google.flatbuffers.FlatBufferBuilder;
import com.google.flatbuffers.FloatVector;
import com.google.flatbuffers.IntVector;
import com.google.flatbuffers.LongVector;
import com.google.flatbuffers.ShortVector;
import com.google.flatbuffers.StringVector;
import com.google.flatbuffers.Struct;
import com.google.flatbuffers.Table;
import com.google.flatbuffers.UnionVector;
import java.nio.ByteBuffer;
import java.nio.ByteOrder;
/**
* Compressed Sparse Fiber (CSF) sparse tensor index.
*/
@SuppressWarnings("unused")
public final class SparseTensorIndexCSF extends Table {
public static void ValidateVersion() { Constants.FLATBUFFERS_24_3_25(); }
public static SparseTensorIndexCSF getRootAsSparseTensorIndexCSF(ByteBuffer _bb) { return getRootAsSparseTensorIndexCSF(_bb, new SparseTensorIndexCSF()); }
public static SparseTensorIndexCSF getRootAsSparseTensorIndexCSF(ByteBuffer _bb, SparseTensorIndexCSF obj) { _bb.order(ByteOrder.LITTLE_ENDIAN); return (obj.__assign(_bb.getInt(_bb.position()) + _bb.position(), _bb)); }
public void __init(int _i, ByteBuffer _bb) { __reset(_i, _bb); }
public SparseTensorIndexCSF __assign(int _i, ByteBuffer _bb) { __init(_i, _bb); return this; }
/**
* CSF is a generalization of compressed sparse row (CSR) index.
* See [smith2017knl](http://shaden.io/pub-files/smith2017knl.pdf)
*
* CSF index recursively compresses each dimension of a tensor into a set
* of prefix trees. Each path from a root to leaf forms one tensor
* non-zero index. CSF is implemented with two arrays of buffers and one
* arrays of integers.
*
* For example, let X be a 2x3x4x5 tensor and let it have the following
* 8 non-zero values:
* ```text
* X[0, 0, 0, 1] := 1
* X[0, 0, 0, 2] := 2
* X[0, 1, 0, 0] := 3
* X[0, 1, 0, 2] := 4
* X[0, 1, 1, 0] := 5
* X[1, 1, 1, 0] := 6
* X[1, 1, 1, 1] := 7
* X[1, 1, 1, 2] := 8
* ```
* As a prefix tree this would be represented as:
* ```text
* 0 1
* / \ |
* 0 1 1
* / / \ |
* 0 0 1 1
* /| /| | /| |
* 1 2 0 2 0 0 1 2
* ```
* The type of values in indptrBuffers
*/
public org.apache.arrow.flatbuf.Int indptrType() { return indptrType(new org.apache.arrow.flatbuf.Int()); }
public org.apache.arrow.flatbuf.Int indptrType(org.apache.arrow.flatbuf.Int obj) { int o = __offset(4); return o != 0 ? obj.__assign(__indirect(o + bb_pos), bb) : null; }
/**
* indptrBuffers stores the sparsity structure.
* Each two consecutive dimensions in a tensor correspond to a buffer in
* indptrBuffers. A pair of consecutive values at `indptrBuffers[dim][i]`
* and `indptrBuffers[dim][i + 1]` signify a range of nodes in
* `indicesBuffers[dim + 1]` who are children of `indicesBuffers[dim][i]` node.
*
* For example, the indptrBuffers for the above X is:
* ```text
* indptrBuffer(X) = [
* [0, 2, 3],
* [0, 1, 3, 4],
* [0, 2, 4, 5, 8]
* ].
* ```
*/
public org.apache.arrow.flatbuf.Buffer indptrBuffers(int j) { return indptrBuffers(new org.apache.arrow.flatbuf.Buffer(), j); }
public org.apache.arrow.flatbuf.Buffer indptrBuffers(org.apache.arrow.flatbuf.Buffer obj, int j) { int o = __offset(6); return o != 0 ? obj.__assign(__vector(o) + j * 16, bb) : null; }
public int indptrBuffersLength() { int o = __offset(6); return o != 0 ? __vector_len(o) : 0; }
public org.apache.arrow.flatbuf.Buffer.Vector indptrBuffersVector() { return indptrBuffersVector(new org.apache.arrow.flatbuf.Buffer.Vector()); }
public org.apache.arrow.flatbuf.Buffer.Vector indptrBuffersVector(org.apache.arrow.flatbuf.Buffer.Vector obj) { int o = __offset(6); return o != 0 ? obj.__assign(__vector(o), 16, bb) : null; }
/**
* The type of values in indicesBuffers
*/
public org.apache.arrow.flatbuf.Int indicesType() { return indicesType(new org.apache.arrow.flatbuf.Int()); }
public org.apache.arrow.flatbuf.Int indicesType(org.apache.arrow.flatbuf.Int obj) { int o = __offset(8); return o != 0 ? obj.__assign(__indirect(o + bb_pos), bb) : null; }
/**
* indicesBuffers stores values of nodes.
* Each tensor dimension corresponds to a buffer in indicesBuffers.
* For example, the indicesBuffers for the above X is:
* ```text
* indicesBuffer(X) = [
* [0, 1],
* [0, 1, 1],
* [0, 0, 1, 1],
* [1, 2, 0, 2, 0, 0, 1, 2]
* ].
* ```
*/
public org.apache.arrow.flatbuf.Buffer indicesBuffers(int j) { return indicesBuffers(new org.apache.arrow.flatbuf.Buffer(), j); }
public org.apache.arrow.flatbuf.Buffer indicesBuffers(org.apache.arrow.flatbuf.Buffer obj, int j) { int o = __offset(10); return o != 0 ? obj.__assign(__vector(o) + j * 16, bb) : null; }
public int indicesBuffersLength() { int o = __offset(10); return o != 0 ? __vector_len(o) : 0; }
public org.apache.arrow.flatbuf.Buffer.Vector indicesBuffersVector() { return indicesBuffersVector(new org.apache.arrow.flatbuf.Buffer.Vector()); }
public org.apache.arrow.flatbuf.Buffer.Vector indicesBuffersVector(org.apache.arrow.flatbuf.Buffer.Vector obj) { int o = __offset(10); return o != 0 ? obj.__assign(__vector(o), 16, bb) : null; }
/**
* axisOrder stores the sequence in which dimensions were traversed to
* produce the prefix tree.
* For example, the axisOrder for the above X is:
* ```text
* axisOrder(X) = [0, 1, 2, 3].
* ```
*/
public int axisOrder(int j) { int o = __offset(12); return o != 0 ? bb.getInt(__vector(o) + j * 4) : 0; }
public int axisOrderLength() { int o = __offset(12); return o != 0 ? __vector_len(o) : 0; }
public IntVector axisOrderVector() { return axisOrderVector(new IntVector()); }
public IntVector axisOrderVector(IntVector obj) { int o = __offset(12); return o != 0 ? obj.__assign(__vector(o), bb) : null; }
public ByteBuffer axisOrderAsByteBuffer() { return __vector_as_bytebuffer(12, 4); }
public ByteBuffer axisOrderInByteBuffer(ByteBuffer _bb) { return __vector_in_bytebuffer(_bb, 12, 4); }
public static int createSparseTensorIndexCSF(FlatBufferBuilder builder,
int indptrTypeOffset,
int indptrBuffersOffset,
int indicesTypeOffset,
int indicesBuffersOffset,
int axisOrderOffset) {
builder.startTable(5);
SparseTensorIndexCSF.addAxisOrder(builder, axisOrderOffset);
SparseTensorIndexCSF.addIndicesBuffers(builder, indicesBuffersOffset);
SparseTensorIndexCSF.addIndicesType(builder, indicesTypeOffset);
SparseTensorIndexCSF.addIndptrBuffers(builder, indptrBuffersOffset);
SparseTensorIndexCSF.addIndptrType(builder, indptrTypeOffset);
return SparseTensorIndexCSF.endSparseTensorIndexCSF(builder);
}
public static void startSparseTensorIndexCSF(FlatBufferBuilder builder) { builder.startTable(5); }
public static void addIndptrType(FlatBufferBuilder builder, int indptrTypeOffset) { builder.addOffset(0, indptrTypeOffset, 0); }
public static void addIndptrBuffers(FlatBufferBuilder builder, int indptrBuffersOffset) { builder.addOffset(1, indptrBuffersOffset, 0); }
public static void startIndptrBuffersVector(FlatBufferBuilder builder, int numElems) { builder.startVector(16, numElems, 8); }
public static void addIndicesType(FlatBufferBuilder builder, int indicesTypeOffset) { builder.addOffset(2, indicesTypeOffset, 0); }
public static void addIndicesBuffers(FlatBufferBuilder builder, int indicesBuffersOffset) { builder.addOffset(3, indicesBuffersOffset, 0); }
public static void startIndicesBuffersVector(FlatBufferBuilder builder, int numElems) { builder.startVector(16, numElems, 8); }
public static void addAxisOrder(FlatBufferBuilder builder, int axisOrderOffset) { builder.addOffset(4, axisOrderOffset, 0); }
public static int createAxisOrderVector(FlatBufferBuilder builder, int[] data) { builder.startVector(4, data.length, 4); for (int i = data.length - 1; i >= 0; i--) builder.addInt(data[i]); return builder.endVector(); }
public static void startAxisOrderVector(FlatBufferBuilder builder, int numElems) { builder.startVector(4, numElems, 4); }
public static int endSparseTensorIndexCSF(FlatBufferBuilder builder) {
int o = builder.endTable();
builder.required(o, 4); // indptrType
builder.required(o, 6); // indptrBuffers
builder.required(o, 8); // indicesType
builder.required(o, 10); // indicesBuffers
builder.required(o, 12); // axisOrder
return o;
}
public static final class Vector extends BaseVector {
public Vector __assign(int _vector, int _element_size, ByteBuffer _bb) { __reset(_vector, _element_size, _bb); return this; }
public SparseTensorIndexCSF get(int j) { return get(new SparseTensorIndexCSF(), j); }
public SparseTensorIndexCSF get(SparseTensorIndexCSF obj, int j) { return obj.__assign(__indirect(__element(j), bb), bb); }
}
}