Source File
	SparseTensorIndexCSF.go

Belonging Package
	github.com/apache/arrow-go/v18/arrow/internal/flatbuf

// 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.

// Code generated by the FlatBuffers compiler. DO NOT EDIT.

package flatbuf

import (
	flatbuffers "github.com/google/flatbuffers/go"
)

// / Compressed Sparse Fiber (CSF) sparse tensor index.
type SparseTensorIndexCSF struct {
	_tab flatbuffers.Table
}

func GetRootAsSparseTensorIndexCSF(buf []byte, offset flatbuffers.UOffsetT) *SparseTensorIndexCSF {
	n := flatbuffers.GetUOffsetT(buf[offset:])
	x := &SparseTensorIndexCSF{}
	x.Init(buf, n+offset)
	return x
}

func (rcv *SparseTensorIndexCSF) Init(buf []byte, i flatbuffers.UOffsetT) {
	rcv._tab.Bytes = buf
	rcv._tab.Pos = i
}

func (rcv *SparseTensorIndexCSF) Table() flatbuffers.Table {
	return rcv._tab
}

// / 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
func (rcv *SparseTensorIndexCSF) IndptrType(obj *Int) *Int {
	o := flatbuffers.UOffsetT(rcv._tab.Offset(4))
	if o != 0 {
		x := rcv._tab.Indirect(o + rcv._tab.Pos)
		if obj == nil {
			obj = new(Int)
		}
		obj.Init(rcv._tab.Bytes, x)
		return obj
	}
	return nil
}

// / 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
// / 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]
// /                     ].
// / ```
func (rcv *SparseTensorIndexCSF) IndptrBuffers(obj *Buffer, j int) bool {
	o := flatbuffers.UOffsetT(rcv._tab.Offset(6))
	if o != 0 {
		x := rcv._tab.Vector(o)
		x += flatbuffers.UOffsetT(j) * 16
		obj.Init(rcv._tab.Bytes, x)
		return true
	}
	return false
}

func (rcv *SparseTensorIndexCSF) IndptrBuffersLength() int {
	o := flatbuffers.UOffsetT(rcv._tab.Offset(6))
	if o != 0 {
		return rcv._tab.VectorLen(o)
	}
	return 0
}

// / 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]
// /                     ].
// / ```
// / The type of values in indicesBuffers
func (rcv *SparseTensorIndexCSF) IndicesType(obj *Int) *Int {
	o := flatbuffers.UOffsetT(rcv._tab.Offset(8))
	if o != 0 {
		x := rcv._tab.Indirect(o + rcv._tab.Pos)
		if obj == nil {
			obj = new(Int)
		}
		obj.Init(rcv._tab.Bytes, x)
		return obj
	}
	return nil
}

// / The type of values in indicesBuffers
// / 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]
// /                      ].
// / ```
func (rcv *SparseTensorIndexCSF) IndicesBuffers(obj *Buffer, j int) bool {
	o := flatbuffers.UOffsetT(rcv._tab.Offset(10))
	if o != 0 {
		x := rcv._tab.Vector(o)
		x += flatbuffers.UOffsetT(j) * 16
		obj.Init(rcv._tab.Bytes, x)
		return true
	}
	return false
}

func (rcv *SparseTensorIndexCSF) IndicesBuffersLength() int {
	o := flatbuffers.UOffsetT(rcv._tab.Offset(10))
	if o != 0 {
		return rcv._tab.VectorLen(o)
	}
	return 0
}

// / 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]
// /                      ].
// / ```
// / 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].
// / ```
func (rcv *SparseTensorIndexCSF) AxisOrder(j int) int32 {
	o := flatbuffers.UOffsetT(rcv._tab.Offset(12))
	if o != 0 {
		a := rcv._tab.Vector(o)
		return rcv._tab.GetInt32(a + flatbuffers.UOffsetT(j*4))
	}
	return 0
}

func (rcv *SparseTensorIndexCSF) AxisOrderLength() int {
	o := flatbuffers.UOffsetT(rcv._tab.Offset(12))
	if o != 0 {
		return rcv._tab.VectorLen(o)
	}
	return 0
}

// / 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].
// / ```
func (rcv *SparseTensorIndexCSF) MutateAxisOrder(j int, n int32) bool {
	o := flatbuffers.UOffsetT(rcv._tab.Offset(12))
	if o != 0 {
		a := rcv._tab.Vector(o)
		return rcv._tab.MutateInt32(a+flatbuffers.UOffsetT(j*4), n)
	}
	return false
}

func SparseTensorIndexCSFStart(builder *flatbuffers.Builder) {
	builder.StartObject(5)
}
func SparseTensorIndexCSFAddIndptrType(builder *flatbuffers.Builder, indptrType flatbuffers.UOffsetT) {
	builder.PrependUOffsetTSlot(0, flatbuffers.UOffsetT(indptrType), 0)
}
func SparseTensorIndexCSFAddIndptrBuffers(builder *flatbuffers.Builder, indptrBuffers flatbuffers.UOffsetT) {
	builder.PrependUOffsetTSlot(1, flatbuffers.UOffsetT(indptrBuffers), 0)
}
func SparseTensorIndexCSFStartIndptrBuffersVector(builder *flatbuffers.Builder, numElems int) flatbuffers.UOffsetT {
	return builder.StartVector(16, numElems, 8)
}
func SparseTensorIndexCSFAddIndicesType(builder *flatbuffers.Builder, indicesType flatbuffers.UOffsetT) {
	builder.PrependUOffsetTSlot(2, flatbuffers.UOffsetT(indicesType), 0)
}
func SparseTensorIndexCSFAddIndicesBuffers(builder *flatbuffers.Builder, indicesBuffers flatbuffers.UOffsetT) {
	builder.PrependUOffsetTSlot(3, flatbuffers.UOffsetT(indicesBuffers), 0)
}
func SparseTensorIndexCSFStartIndicesBuffersVector(builder *flatbuffers.Builder, numElems int) flatbuffers.UOffsetT {
	return builder.StartVector(16, numElems, 8)
}
func SparseTensorIndexCSFAddAxisOrder(builder *flatbuffers.Builder, axisOrder flatbuffers.UOffsetT) {
	builder.PrependUOffsetTSlot(4, flatbuffers.UOffsetT(axisOrder), 0)
}
func SparseTensorIndexCSFStartAxisOrderVector(builder *flatbuffers.Builder, numElems int) flatbuffers.UOffsetT {
	return builder.StartVector(4, numElems, 4)
}
func SparseTensorIndexCSFEnd(builder *flatbuffers.Builder) flatbuffers.UOffsetT {
	return builder.EndObject()
}

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