Repository navigation
Expand file tree
/
Copy pathSparseTensor_generated.h
More file actions
924 lines (852 loc) · 40.3 KB
/
Copy pathSparseTensor_generated.h
File metadata and controls
924 lines (852 loc) · 40.3 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
// automatically generated by the FlatBuffers compiler, do not modify
#ifndef FLATBUFFERS_GENERATED_SPARSETENSOR_ORG_APACHE_ARROW_FLATBUF_H_
#define FLATBUFFERS_GENERATED_SPARSETENSOR_ORG_APACHE_ARROW_FLATBUF_H_
#include "flatbuffers/flatbuffers.h"
#include "Schema_generated.h"
#include "Tensor_generated.h"
namespace org {
namespace apache {
namespace arrow {
namespace flatbuf {
struct SparseTensorIndexCOO;
struct SparseTensorIndexCOOBuilder;
struct SparseMatrixIndexCSX;
struct SparseMatrixIndexCSXBuilder;
struct SparseTensorIndexCSF;
struct SparseTensorIndexCSFBuilder;
struct SparseTensor;
struct SparseTensorBuilder;
enum class SparseMatrixCompressedAxis : int16_t {
Row = 0,
Column = 1,
MIN = Row,
MAX = Column
};
inline const SparseMatrixCompressedAxis (&EnumValuesSparseMatrixCompressedAxis())[2] {
static const SparseMatrixCompressedAxis values[] = {
SparseMatrixCompressedAxis::Row,
SparseMatrixCompressedAxis::Column
};
return values;
}
inline const char * const *EnumNamesSparseMatrixCompressedAxis() {
static const char * const names[3] = {
"Row",
"Column",
nullptr
};
return names;
}
inline const char *EnumNameSparseMatrixCompressedAxis(SparseMatrixCompressedAxis e) {
if (flatbuffers::IsOutRange(e, SparseMatrixCompressedAxis::Row, SparseMatrixCompressedAxis::Column)) return "";
const size_t index = static_cast<size_t>(e);
return EnumNamesSparseMatrixCompressedAxis()[index];
}
enum class SparseTensorIndex : uint8_t {
NONE = 0,
SparseTensorIndexCOO = 1,
SparseMatrixIndexCSX = 2,
SparseTensorIndexCSF = 3,
MIN = NONE,
MAX = SparseTensorIndexCSF
};
inline const SparseTensorIndex (&EnumValuesSparseTensorIndex())[4] {
static const SparseTensorIndex values[] = {
SparseTensorIndex::NONE,
SparseTensorIndex::SparseTensorIndexCOO,
SparseTensorIndex::SparseMatrixIndexCSX,
SparseTensorIndex::SparseTensorIndexCSF
};
return values;
}
inline const char * const *EnumNamesSparseTensorIndex() {
static const char * const names[5] = {
"NONE",
"SparseTensorIndexCOO",
"SparseMatrixIndexCSX",
"SparseTensorIndexCSF",
nullptr
};
return names;
}
inline const char *EnumNameSparseTensorIndex(SparseTensorIndex e) {
if (flatbuffers::IsOutRange(e, SparseTensorIndex::NONE, SparseTensorIndex::SparseTensorIndexCSF)) return "";
const size_t index = static_cast<size_t>(e);
return EnumNamesSparseTensorIndex()[index];
}
template<typename T> struct SparseTensorIndexTraits {
static const SparseTensorIndex enum_value = SparseTensorIndex::NONE;
};
template<> struct SparseTensorIndexTraits<org::apache::arrow::flatbuf::SparseTensorIndexCOO> {
static const SparseTensorIndex enum_value = SparseTensorIndex::SparseTensorIndexCOO;
};
template<> struct SparseTensorIndexTraits<org::apache::arrow::flatbuf::SparseMatrixIndexCSX> {
static const SparseTensorIndex enum_value = SparseTensorIndex::SparseMatrixIndexCSX;
};
template<> struct SparseTensorIndexTraits<org::apache::arrow::flatbuf::SparseTensorIndexCSF> {
static const SparseTensorIndex enum_value = SparseTensorIndex::SparseTensorIndexCSF;
};
bool VerifySparseTensorIndex(flatbuffers::Verifier &verifier, const void *obj, SparseTensorIndex type);
bool VerifySparseTensorIndexVector(flatbuffers::Verifier &verifier, const flatbuffers::Vector<flatbuffers::Offset<void>> *values, const flatbuffers::Vector<uint8_t> *types);
/// ----------------------------------------------------------------------
/// EXPERIMENTAL: Data structures for sparse tensors
/// Coordinate (COO) format of sparse tensor index.
///
/// COO's index list are represented as a NxM matrix,
/// where N is the number of non-zero values,
/// and M is the number of dimensions of a sparse tensor.
///
/// indicesBuffer stores the location and size of the data of this indices
/// matrix. The value type and the stride of the indices matrix is
/// specified in indicesType and indicesStrides fields.
///
/// For example, let X be a 2x3x4x5 tensor, and it has the following
/// 6 non-zero values:
/// ```text
/// X[0, 1, 2, 0] := 1
/// X[1, 1, 2, 3] := 2
/// X[0, 2, 1, 0] := 3
/// X[0, 1, 3, 0] := 4
/// X[0, 1, 2, 1] := 5
/// X[1, 2, 0, 4] := 6
/// ```
/// In COO format, the index matrix of X is the following 4x6 matrix:
/// ```text
/// [[0, 0, 0, 0, 1, 1],
/// [1, 1, 1, 2, 1, 2],
/// [2, 2, 3, 1, 2, 0],
/// [0, 1, 0, 0, 3, 4]]
/// ```
/// When isCanonical is true, the indices is sorted in lexicographical order
/// (row-major order), and it does not have duplicated entries. Otherwise,
/// the indices may not be sorted, or may have duplicated entries.
struct SparseTensorIndexCOO FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
typedef SparseTensorIndexCOOBuilder Builder;
enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
VT_INDICESTYPE = 4,
VT_INDICESSTRIDES = 6,
VT_INDICESBUFFER = 8,
VT_ISCANONICAL = 10
};
/// The type of values in indicesBuffer
const org::apache::arrow::flatbuf::Int *indicesType() const {
return GetPointer<const org::apache::arrow::flatbuf::Int *>(VT_INDICESTYPE);
}
/// Non-negative byte offsets to advance one value cell along each dimension
/// If omitted, default to row-major order (C-like).
const flatbuffers::Vector<int64_t> *indicesStrides() const {
return GetPointer<const flatbuffers::Vector<int64_t> *>(VT_INDICESSTRIDES);
}
/// The location and size of the indices matrix's data
const org::apache::arrow::flatbuf::Buffer *indicesBuffer() const {
return GetStruct<const org::apache::arrow::flatbuf::Buffer *>(VT_INDICESBUFFER);
}
/// This flag is true if and only if the indices matrix is sorted in
/// row-major order, and does not have duplicated entries.
/// This sort order is the same as of Tensorflow's SparseTensor,
/// but it is inverse order of SciPy's canonical coo_matrix
/// (SciPy employs column-major order for its coo_matrix).
bool isCanonical() const {
return GetField<uint8_t>(VT_ISCANONICAL, 0) != 0;
}
bool Verify(flatbuffers::Verifier &verifier) const {
return VerifyTableStart(verifier) &&
VerifyOffsetRequired(verifier, VT_INDICESTYPE) &&
verifier.VerifyTable(indicesType()) &&
VerifyOffset(verifier, VT_INDICESSTRIDES) &&
verifier.VerifyVector(indicesStrides()) &&
VerifyFieldRequired<org::apache::arrow::flatbuf::Buffer>(verifier, VT_INDICESBUFFER) &&
VerifyField<uint8_t>(verifier, VT_ISCANONICAL) &&
verifier.EndTable();
}
};
struct SparseTensorIndexCOOBuilder {
typedef SparseTensorIndexCOO Table;
flatbuffers::FlatBufferBuilder &fbb_;
flatbuffers::uoffset_t start_;
void add_indicesType(flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indicesType) {
fbb_.AddOffset(SparseTensorIndexCOO::VT_INDICESTYPE, indicesType);
}
void add_indicesStrides(flatbuffers::Offset<flatbuffers::Vector<int64_t>> indicesStrides) {
fbb_.AddOffset(SparseTensorIndexCOO::VT_INDICESSTRIDES, indicesStrides);
}
void add_indicesBuffer(const org::apache::arrow::flatbuf::Buffer *indicesBuffer) {
fbb_.AddStruct(SparseTensorIndexCOO::VT_INDICESBUFFER, indicesBuffer);
}
void add_isCanonical(bool isCanonical) {
fbb_.AddElement<uint8_t>(SparseTensorIndexCOO::VT_ISCANONICAL, static_cast<uint8_t>(isCanonical), 0);
}
explicit SparseTensorIndexCOOBuilder(flatbuffers::FlatBufferBuilder &_fbb)
: fbb_(_fbb) {
start_ = fbb_.StartTable();
}
flatbuffers::Offset<SparseTensorIndexCOO> Finish() {
const auto end = fbb_.EndTable(start_);
auto o = flatbuffers::Offset<SparseTensorIndexCOO>(end);
fbb_.Required(o, SparseTensorIndexCOO::VT_INDICESTYPE);
fbb_.Required(o, SparseTensorIndexCOO::VT_INDICESBUFFER);
return o;
}
};
inline flatbuffers::Offset<SparseTensorIndexCOO> CreateSparseTensorIndexCOO(
flatbuffers::FlatBufferBuilder &_fbb,
flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indicesType = 0,
flatbuffers::Offset<flatbuffers::Vector<int64_t>> indicesStrides = 0,
const org::apache::arrow::flatbuf::Buffer *indicesBuffer = 0,
bool isCanonical = false) {
SparseTensorIndexCOOBuilder builder_(_fbb);
builder_.add_indicesBuffer(indicesBuffer);
builder_.add_indicesStrides(indicesStrides);
builder_.add_indicesType(indicesType);
builder_.add_isCanonical(isCanonical);
return builder_.Finish();
}
inline flatbuffers::Offset<SparseTensorIndexCOO> CreateSparseTensorIndexCOODirect(
flatbuffers::FlatBufferBuilder &_fbb,
flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indicesType = 0,
const std::vector<int64_t> *indicesStrides = nullptr,
const org::apache::arrow::flatbuf::Buffer *indicesBuffer = 0,
bool isCanonical = false) {
auto indicesStrides__ = indicesStrides ? _fbb.CreateVector<int64_t>(*indicesStrides) : 0;
return org::apache::arrow::flatbuf::CreateSparseTensorIndexCOO(
_fbb,
indicesType,
indicesStrides__,
indicesBuffer,
isCanonical);
}
/// Compressed Sparse format, that is matrix-specific.
struct SparseMatrixIndexCSX FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
typedef SparseMatrixIndexCSXBuilder Builder;
enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
VT_COMPRESSEDAXIS = 4,
VT_INDPTRTYPE = 6,
VT_INDPTRBUFFER = 8,
VT_INDICESTYPE = 10,
VT_INDICESBUFFER = 12
};
/// Which axis, row or column, is compressed
org::apache::arrow::flatbuf::SparseMatrixCompressedAxis compressedAxis() const {
return static_cast<org::apache::arrow::flatbuf::SparseMatrixCompressedAxis>(GetField<int16_t>(VT_COMPRESSEDAXIS, 0));
}
/// The type of values in indptrBuffer
const org::apache::arrow::flatbuf::Int *indptrType() const {
return GetPointer<const org::apache::arrow::flatbuf::Int *>(VT_INDPTRTYPE);
}
/// indptrBuffer stores the location and size of indptr array that
/// represents the range of the rows.
/// The i-th row spans from `indptr[i]` to `indptr[i+1]` in the data.
/// The length of this array is 1 + (the number of rows), and the type
/// of index value is long.
///
/// For example, let X be the following 6x4 matrix:
/// ```text
/// X := [[0, 1, 2, 0],
/// [0, 0, 3, 0],
/// [0, 4, 0, 5],
/// [0, 0, 0, 0],
/// [6, 0, 7, 8],
/// [0, 9, 0, 0]].
/// ```
/// The array of non-zero values in X is:
/// ```text
/// values(X) = [1, 2, 3, 4, 5, 6, 7, 8, 9].
/// ```
/// And the indptr of X is:
/// ```text
/// indptr(X) = [0, 2, 3, 5, 5, 8, 10].
/// ```
const org::apache::arrow::flatbuf::Buffer *indptrBuffer() const {
return GetStruct<const org::apache::arrow::flatbuf::Buffer *>(VT_INDPTRBUFFER);
}
/// The type of values in indicesBuffer
const org::apache::arrow::flatbuf::Int *indicesType() const {
return GetPointer<const org::apache::arrow::flatbuf::Int *>(VT_INDICESTYPE);
}
/// indicesBuffer stores the location and size of the array that
/// contains the column indices of the corresponding non-zero values.
/// The type of index value is long.
///
/// For example, the indices of the above X is:
/// ```text
/// indices(X) = [1, 2, 2, 1, 3, 0, 2, 3, 1].
/// ```
/// Note that the indices are sorted in lexicographical order for each row.
const org::apache::arrow::flatbuf::Buffer *indicesBuffer() const {
return GetStruct<const org::apache::arrow::flatbuf::Buffer *>(VT_INDICESBUFFER);
}
bool Verify(flatbuffers::Verifier &verifier) const {
return VerifyTableStart(verifier) &&
VerifyField<int16_t>(verifier, VT_COMPRESSEDAXIS) &&
VerifyOffsetRequired(verifier, VT_INDPTRTYPE) &&
verifier.VerifyTable(indptrType()) &&
VerifyFieldRequired<org::apache::arrow::flatbuf::Buffer>(verifier, VT_INDPTRBUFFER) &&
VerifyOffsetRequired(verifier, VT_INDICESTYPE) &&
verifier.VerifyTable(indicesType()) &&
VerifyFieldRequired<org::apache::arrow::flatbuf::Buffer>(verifier, VT_INDICESBUFFER) &&
verifier.EndTable();
}
};
struct SparseMatrixIndexCSXBuilder {
typedef SparseMatrixIndexCSX Table;
flatbuffers::FlatBufferBuilder &fbb_;
flatbuffers::uoffset_t start_;
void add_compressedAxis(org::apache::arrow::flatbuf::SparseMatrixCompressedAxis compressedAxis) {
fbb_.AddElement<int16_t>(SparseMatrixIndexCSX::VT_COMPRESSEDAXIS, static_cast<int16_t>(compressedAxis), 0);
}
void add_indptrType(flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indptrType) {
fbb_.AddOffset(SparseMatrixIndexCSX::VT_INDPTRTYPE, indptrType);
}
void add_indptrBuffer(const org::apache::arrow::flatbuf::Buffer *indptrBuffer) {
fbb_.AddStruct(SparseMatrixIndexCSX::VT_INDPTRBUFFER, indptrBuffer);
}
void add_indicesType(flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indicesType) {
fbb_.AddOffset(SparseMatrixIndexCSX::VT_INDICESTYPE, indicesType);
}
void add_indicesBuffer(const org::apache::arrow::flatbuf::Buffer *indicesBuffer) {
fbb_.AddStruct(SparseMatrixIndexCSX::VT_INDICESBUFFER, indicesBuffer);
}
explicit SparseMatrixIndexCSXBuilder(flatbuffers::FlatBufferBuilder &_fbb)
: fbb_(_fbb) {
start_ = fbb_.StartTable();
}
flatbuffers::Offset<SparseMatrixIndexCSX> Finish() {
const auto end = fbb_.EndTable(start_);
auto o = flatbuffers::Offset<SparseMatrixIndexCSX>(end);
fbb_.Required(o, SparseMatrixIndexCSX::VT_INDPTRTYPE);
fbb_.Required(o, SparseMatrixIndexCSX::VT_INDPTRBUFFER);
fbb_.Required(o, SparseMatrixIndexCSX::VT_INDICESTYPE);
fbb_.Required(o, SparseMatrixIndexCSX::VT_INDICESBUFFER);
return o;
}
};
inline flatbuffers::Offset<SparseMatrixIndexCSX> CreateSparseMatrixIndexCSX(
flatbuffers::FlatBufferBuilder &_fbb,
org::apache::arrow::flatbuf::SparseMatrixCompressedAxis compressedAxis = org::apache::arrow::flatbuf::SparseMatrixCompressedAxis::Row,
flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indptrType = 0,
const org::apache::arrow::flatbuf::Buffer *indptrBuffer = 0,
flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indicesType = 0,
const org::apache::arrow::flatbuf::Buffer *indicesBuffer = 0) {
SparseMatrixIndexCSXBuilder builder_(_fbb);
builder_.add_indicesBuffer(indicesBuffer);
builder_.add_indicesType(indicesType);
builder_.add_indptrBuffer(indptrBuffer);
builder_.add_indptrType(indptrType);
builder_.add_compressedAxis(compressedAxis);
return builder_.Finish();
}
/// Compressed Sparse Fiber (CSF) sparse tensor index.
struct SparseTensorIndexCSF FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
typedef SparseTensorIndexCSFBuilder Builder;
enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
VT_INDPTRTYPE = 4,
VT_INDPTRBUFFERS = 6,
VT_INDICESTYPE = 8,
VT_INDICESBUFFERS = 10,
VT_AXISORDER = 12
};
/// 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
const org::apache::arrow::flatbuf::Int *indptrType() const {
return GetPointer<const org::apache::arrow::flatbuf::Int *>(VT_INDPTRTYPE);
}
/// 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]
/// ].
/// ```
const flatbuffers::Vector<const org::apache::arrow::flatbuf::Buffer *> *indptrBuffers() const {
return GetPointer<const flatbuffers::Vector<const org::apache::arrow::flatbuf::Buffer *> *>(VT_INDPTRBUFFERS);
}
/// The type of values in indicesBuffers
const org::apache::arrow::flatbuf::Int *indicesType() const {
return GetPointer<const org::apache::arrow::flatbuf::Int *>(VT_INDICESTYPE);
}
/// 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]
/// ].
/// ```
const flatbuffers::Vector<const org::apache::arrow::flatbuf::Buffer *> *indicesBuffers() const {
return GetPointer<const flatbuffers::Vector<const org::apache::arrow::flatbuf::Buffer *> *>(VT_INDICESBUFFERS);
}
/// 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].
/// ```
const flatbuffers::Vector<int32_t> *axisOrder() const {
return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_AXISORDER);
}
bool Verify(flatbuffers::Verifier &verifier) const {
return VerifyTableStart(verifier) &&
VerifyOffsetRequired(verifier, VT_INDPTRTYPE) &&
verifier.VerifyTable(indptrType()) &&
VerifyOffsetRequired(verifier, VT_INDPTRBUFFERS) &&
verifier.VerifyVector(indptrBuffers()) &&
VerifyOffsetRequired(verifier, VT_INDICESTYPE) &&
verifier.VerifyTable(indicesType()) &&
VerifyOffsetRequired(verifier, VT_INDICESBUFFERS) &&
verifier.VerifyVector(indicesBuffers()) &&
VerifyOffsetRequired(verifier, VT_AXISORDER) &&
verifier.VerifyVector(axisOrder()) &&
verifier.EndTable();
}
};
struct SparseTensorIndexCSFBuilder {
typedef SparseTensorIndexCSF Table;
flatbuffers::FlatBufferBuilder &fbb_;
flatbuffers::uoffset_t start_;
void add_indptrType(flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indptrType) {
fbb_.AddOffset(SparseTensorIndexCSF::VT_INDPTRTYPE, indptrType);
}
void add_indptrBuffers(flatbuffers::Offset<flatbuffers::Vector<const org::apache::arrow::flatbuf::Buffer *>> indptrBuffers) {
fbb_.AddOffset(SparseTensorIndexCSF::VT_INDPTRBUFFERS, indptrBuffers);
}
void add_indicesType(flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indicesType) {
fbb_.AddOffset(SparseTensorIndexCSF::VT_INDICESTYPE, indicesType);
}
void add_indicesBuffers(flatbuffers::Offset<flatbuffers::Vector<const org::apache::arrow::flatbuf::Buffer *>> indicesBuffers) {
fbb_.AddOffset(SparseTensorIndexCSF::VT_INDICESBUFFERS, indicesBuffers);
}
void add_axisOrder(flatbuffers::Offset<flatbuffers::Vector<int32_t>> axisOrder) {
fbb_.AddOffset(SparseTensorIndexCSF::VT_AXISORDER, axisOrder);
}
explicit SparseTensorIndexCSFBuilder(flatbuffers::FlatBufferBuilder &_fbb)
: fbb_(_fbb) {
start_ = fbb_.StartTable();
}
flatbuffers::Offset<SparseTensorIndexCSF> Finish() {
const auto end = fbb_.EndTable(start_);
auto o = flatbuffers::Offset<SparseTensorIndexCSF>(end);
fbb_.Required(o, SparseTensorIndexCSF::VT_INDPTRTYPE);
fbb_.Required(o, SparseTensorIndexCSF::VT_INDPTRBUFFERS);
fbb_.Required(o, SparseTensorIndexCSF::VT_INDICESTYPE);
fbb_.Required(o, SparseTensorIndexCSF::VT_INDICESBUFFERS);
fbb_.Required(o, SparseTensorIndexCSF::VT_AXISORDER);
return o;
}
};
inline flatbuffers::Offset<SparseTensorIndexCSF> CreateSparseTensorIndexCSF(
flatbuffers::FlatBufferBuilder &_fbb,
flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indptrType = 0,
flatbuffers::Offset<flatbuffers::Vector<const org::apache::arrow::flatbuf::Buffer *>> indptrBuffers = 0,
flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indicesType = 0,
flatbuffers::Offset<flatbuffers::Vector<const org::apache::arrow::flatbuf::Buffer *>> indicesBuffers = 0,
flatbuffers::Offset<flatbuffers::Vector<int32_t>> axisOrder = 0) {
SparseTensorIndexCSFBuilder builder_(_fbb);
builder_.add_axisOrder(axisOrder);
builder_.add_indicesBuffers(indicesBuffers);
builder_.add_indicesType(indicesType);
builder_.add_indptrBuffers(indptrBuffers);
builder_.add_indptrType(indptrType);
return builder_.Finish();
}
inline flatbuffers::Offset<SparseTensorIndexCSF> CreateSparseTensorIndexCSFDirect(
flatbuffers::FlatBufferBuilder &_fbb,
flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indptrType = 0,
const std::vector<org::apache::arrow::flatbuf::Buffer> *indptrBuffers = nullptr,
flatbuffers::Offset<org::apache::arrow::flatbuf::Int> indicesType = 0,
const std::vector<org::apache::arrow::flatbuf::Buffer> *indicesBuffers = nullptr,
const std::vector<int32_t> *axisOrder = nullptr) {
auto indptrBuffers__ = indptrBuffers ? _fbb.CreateVectorOfStructs<org::apache::arrow::flatbuf::Buffer>(*indptrBuffers) : 0;
auto indicesBuffers__ = indicesBuffers ? _fbb.CreateVectorOfStructs<org::apache::arrow::flatbuf::Buffer>(*indicesBuffers) : 0;
auto axisOrder__ = axisOrder ? _fbb.CreateVector<int32_t>(*axisOrder) : 0;
return org::apache::arrow::flatbuf::CreateSparseTensorIndexCSF(
_fbb,
indptrType,
indptrBuffers__,
indicesType,
indicesBuffers__,
axisOrder__);
}
struct SparseTensor FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
typedef SparseTensorBuilder Builder;
enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
VT_TYPE_TYPE = 4,
VT_TYPE = 6,
VT_SHAPE = 8,
VT_NON_ZERO_LENGTH = 10,
VT_SPARSEINDEX_TYPE = 12,
VT_SPARSEINDEX = 14,
VT_DATA = 16
};
org::apache::arrow::flatbuf::Type type_type() const {
return static_cast<org::apache::arrow::flatbuf::Type>(GetField<uint8_t>(VT_TYPE_TYPE, 0));
}
/// The type of data contained in a value cell.
/// Currently only fixed-width value types are supported,
/// no strings or nested types.
const void *type() const {
return GetPointer<const void *>(VT_TYPE);
}
template<typename T> const T *type_as() const;
const org::apache::arrow::flatbuf::Null *type_as_Null() const {
return type_type() == org::apache::arrow::flatbuf::Type::Null ? static_cast<const org::apache::arrow::flatbuf::Null *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Int *type_as_Int() const {
return type_type() == org::apache::arrow::flatbuf::Type::Int ? static_cast<const org::apache::arrow::flatbuf::Int *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::FloatingPoint *type_as_FloatingPoint() const {
return type_type() == org::apache::arrow::flatbuf::Type::FloatingPoint ? static_cast<const org::apache::arrow::flatbuf::FloatingPoint *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Binary *type_as_Binary() const {
return type_type() == org::apache::arrow::flatbuf::Type::Binary ? static_cast<const org::apache::arrow::flatbuf::Binary *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Utf8 *type_as_Utf8() const {
return type_type() == org::apache::arrow::flatbuf::Type::Utf8 ? static_cast<const org::apache::arrow::flatbuf::Utf8 *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Bool *type_as_Bool() const {
return type_type() == org::apache::arrow::flatbuf::Type::Bool ? static_cast<const org::apache::arrow::flatbuf::Bool *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Decimal *type_as_Decimal() const {
return type_type() == org::apache::arrow::flatbuf::Type::Decimal ? static_cast<const org::apache::arrow::flatbuf::Decimal *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Date *type_as_Date() const {
return type_type() == org::apache::arrow::flatbuf::Type::Date ? static_cast<const org::apache::arrow::flatbuf::Date *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Time *type_as_Time() const {
return type_type() == org::apache::arrow::flatbuf::Type::Time ? static_cast<const org::apache::arrow::flatbuf::Time *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Timestamp *type_as_Timestamp() const {
return type_type() == org::apache::arrow::flatbuf::Type::Timestamp ? static_cast<const org::apache::arrow::flatbuf::Timestamp *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Interval *type_as_Interval() const {
return type_type() == org::apache::arrow::flatbuf::Type::Interval ? static_cast<const org::apache::arrow::flatbuf::Interval *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::List *type_as_List() const {
return type_type() == org::apache::arrow::flatbuf::Type::List ? static_cast<const org::apache::arrow::flatbuf::List *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Struct_ *type_as_Struct_() const {
return type_type() == org::apache::arrow::flatbuf::Type::Struct_ ? static_cast<const org::apache::arrow::flatbuf::Struct_ *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Union *type_as_Union() const {
return type_type() == org::apache::arrow::flatbuf::Type::Union ? static_cast<const org::apache::arrow::flatbuf::Union *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::FixedSizeBinary *type_as_FixedSizeBinary() const {
return type_type() == org::apache::arrow::flatbuf::Type::FixedSizeBinary ? static_cast<const org::apache::arrow::flatbuf::FixedSizeBinary *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::FixedSizeList *type_as_FixedSizeList() const {
return type_type() == org::apache::arrow::flatbuf::Type::FixedSizeList ? static_cast<const org::apache::arrow::flatbuf::FixedSizeList *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Map *type_as_Map() const {
return type_type() == org::apache::arrow::flatbuf::Type::Map ? static_cast<const org::apache::arrow::flatbuf::Map *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::Duration *type_as_Duration() const {
return type_type() == org::apache::arrow::flatbuf::Type::Duration ? static_cast<const org::apache::arrow::flatbuf::Duration *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::LargeBinary *type_as_LargeBinary() const {
return type_type() == org::apache::arrow::flatbuf::Type::LargeBinary ? static_cast<const org::apache::arrow::flatbuf::LargeBinary *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::LargeUtf8 *type_as_LargeUtf8() const {
return type_type() == org::apache::arrow::flatbuf::Type::LargeUtf8 ? static_cast<const org::apache::arrow::flatbuf::LargeUtf8 *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::LargeList *type_as_LargeList() const {
return type_type() == org::apache::arrow::flatbuf::Type::LargeList ? static_cast<const org::apache::arrow::flatbuf::LargeList *>(type()) : nullptr;
}
const org::apache::arrow::flatbuf::RunEndEncoded *type_as_RunEndEncoded() const {
return type_type() == org::apache::arrow::flatbuf::Type::RunEndEncoded ? static_cast<const org::apache::arrow::flatbuf::RunEndEncoded *>(type()) : nullptr;
}
/// The dimensions of the tensor, optionally named.
const flatbuffers::Vector<flatbuffers::Offset<org::apache::arrow::flatbuf::TensorDim>> *shape() const {
return GetPointer<const flatbuffers::Vector<flatbuffers::Offset<org::apache::arrow::flatbuf::TensorDim>> *>(VT_SHAPE);
}
/// The number of non-zero values in a sparse tensor.
int64_t non_zero_length() const {
return GetField<int64_t>(VT_NON_ZERO_LENGTH, 0);
}
org::apache::arrow::flatbuf::SparseTensorIndex sparseIndex_type() const {
return static_cast<org::apache::arrow::flatbuf::SparseTensorIndex>(GetField<uint8_t>(VT_SPARSEINDEX_TYPE, 0));
}
/// Sparse tensor index
const void *sparseIndex() const {
return GetPointer<const void *>(VT_SPARSEINDEX);
}
template<typename T> const T *sparseIndex_as() const;
const org::apache::arrow::flatbuf::SparseTensorIndexCOO *sparseIndex_as_SparseTensorIndexCOO() const {
return sparseIndex_type() == org::apache::arrow::flatbuf::SparseTensorIndex::SparseTensorIndexCOO ? static_cast<const org::apache::arrow::flatbuf::SparseTensorIndexCOO *>(sparseIndex()) : nullptr;
}
const org::apache::arrow::flatbuf::SparseMatrixIndexCSX *sparseIndex_as_SparseMatrixIndexCSX() const {
return sparseIndex_type() == org::apache::arrow::flatbuf::SparseTensorIndex::SparseMatrixIndexCSX ? static_cast<const org::apache::arrow::flatbuf::SparseMatrixIndexCSX *>(sparseIndex()) : nullptr;
}
const org::apache::arrow::flatbuf::SparseTensorIndexCSF *sparseIndex_as_SparseTensorIndexCSF() const {
return sparseIndex_type() == org::apache::arrow::flatbuf::SparseTensorIndex::SparseTensorIndexCSF ? static_cast<const org::apache::arrow::flatbuf::SparseTensorIndexCSF *>(sparseIndex()) : nullptr;
}
/// The location and size of the tensor's data
const org::apache::arrow::flatbuf::Buffer *data() const {
return GetStruct<const org::apache::arrow::flatbuf::Buffer *>(VT_DATA);
}
bool Verify(flatbuffers::Verifier &verifier) const {
return VerifyTableStart(verifier) &&
VerifyField<uint8_t>(verifier, VT_TYPE_TYPE) &&
VerifyOffsetRequired(verifier, VT_TYPE) &&
VerifyType(verifier, type(), type_type()) &&
VerifyOffsetRequired(verifier, VT_SHAPE) &&
verifier.VerifyVector(shape()) &&
verifier.VerifyVectorOfTables(shape()) &&
VerifyField<int64_t>(verifier, VT_NON_ZERO_LENGTH) &&
VerifyField<uint8_t>(verifier, VT_SPARSEINDEX_TYPE) &&
VerifyOffsetRequired(verifier, VT_SPARSEINDEX) &&
VerifySparseTensorIndex(verifier, sparseIndex(), sparseIndex_type()) &&
VerifyFieldRequired<org::apache::arrow::flatbuf::Buffer>(verifier, VT_DATA) &&
verifier.EndTable();
}
};
template<> inline const org::apache::arrow::flatbuf::Null *SparseTensor::type_as<org::apache::arrow::flatbuf::Null>() const {
return type_as_Null();
}
template<> inline const org::apache::arrow::flatbuf::Int *SparseTensor::type_as<org::apache::arrow::flatbuf::Int>() const {
return type_as_Int();
}
template<> inline const org::apache::arrow::flatbuf::FloatingPoint *SparseTensor::type_as<org::apache::arrow::flatbuf::FloatingPoint>() const {
return type_as_FloatingPoint();
}
template<> inline const org::apache::arrow::flatbuf::Binary *SparseTensor::type_as<org::apache::arrow::flatbuf::Binary>() const {
return type_as_Binary();
}
template<> inline const org::apache::arrow::flatbuf::Utf8 *SparseTensor::type_as<org::apache::arrow::flatbuf::Utf8>() const {
return type_as_Utf8();
}
template<> inline const org::apache::arrow::flatbuf::Bool *SparseTensor::type_as<org::apache::arrow::flatbuf::Bool>() const {
return type_as_Bool();
}
template<> inline const org::apache::arrow::flatbuf::Decimal *SparseTensor::type_as<org::apache::arrow::flatbuf::Decimal>() const {
return type_as_Decimal();
}
template<> inline const org::apache::arrow::flatbuf::Date *SparseTensor::type_as<org::apache::arrow::flatbuf::Date>() const {
return type_as_Date();
}
template<> inline const org::apache::arrow::flatbuf::Time *SparseTensor::type_as<org::apache::arrow::flatbuf::Time>() const {
return type_as_Time();
}
template<> inline const org::apache::arrow::flatbuf::Timestamp *SparseTensor::type_as<org::apache::arrow::flatbuf::Timestamp>() const {
return type_as_Timestamp();
}
template<> inline const org::apache::arrow::flatbuf::Interval *SparseTensor::type_as<org::apache::arrow::flatbuf::Interval>() const {
return type_as_Interval();
}
template<> inline const org::apache::arrow::flatbuf::List *SparseTensor::type_as<org::apache::arrow::flatbuf::List>() const {
return type_as_List();
}
template<> inline const org::apache::arrow::flatbuf::Struct_ *SparseTensor::type_as<org::apache::arrow::flatbuf::Struct_>() const {
return type_as_Struct_();
}
template<> inline const org::apache::arrow::flatbuf::Union *SparseTensor::type_as<org::apache::arrow::flatbuf::Union>() const {
return type_as_Union();
}
template<> inline const org::apache::arrow::flatbuf::FixedSizeBinary *SparseTensor::type_as<org::apache::arrow::flatbuf::FixedSizeBinary>() const {
return type_as_FixedSizeBinary();
}
template<> inline const org::apache::arrow::flatbuf::FixedSizeList *SparseTensor::type_as<org::apache::arrow::flatbuf::FixedSizeList>() const {
return type_as_FixedSizeList();
}
template<> inline const org::apache::arrow::flatbuf::Map *SparseTensor::type_as<org::apache::arrow::flatbuf::Map>() const {
return type_as_Map();
}
template<> inline const org::apache::arrow::flatbuf::Duration *SparseTensor::type_as<org::apache::arrow::flatbuf::Duration>() const {
return type_as_Duration();
}
template<> inline const org::apache::arrow::flatbuf::LargeBinary *SparseTensor::type_as<org::apache::arrow::flatbuf::LargeBinary>() const {
return type_as_LargeBinary();
}
template<> inline const org::apache::arrow::flatbuf::LargeUtf8 *SparseTensor::type_as<org::apache::arrow::flatbuf::LargeUtf8>() const {
return type_as_LargeUtf8();
}
template<> inline const org::apache::arrow::flatbuf::LargeList *SparseTensor::type_as<org::apache::arrow::flatbuf::LargeList>() const {
return type_as_LargeList();
}
template<> inline const org::apache::arrow::flatbuf::RunEndEncoded *SparseTensor::type_as<org::apache::arrow::flatbuf::RunEndEncoded>() const {
return type_as_RunEndEncoded();
}
template<> inline const org::apache::arrow::flatbuf::SparseTensorIndexCOO *SparseTensor::sparseIndex_as<org::apache::arrow::flatbuf::SparseTensorIndexCOO>() const {
return sparseIndex_as_SparseTensorIndexCOO();
}
template<> inline const org::apache::arrow::flatbuf::SparseMatrixIndexCSX *SparseTensor::sparseIndex_as<org::apache::arrow::flatbuf::SparseMatrixIndexCSX>() const {
return sparseIndex_as_SparseMatrixIndexCSX();
}
template<> inline const org::apache::arrow::flatbuf::SparseTensorIndexCSF *SparseTensor::sparseIndex_as<org::apache::arrow::flatbuf::SparseTensorIndexCSF>() const {
return sparseIndex_as_SparseTensorIndexCSF();
}
struct SparseTensorBuilder {
typedef SparseTensor Table;
flatbuffers::FlatBufferBuilder &fbb_;
flatbuffers::uoffset_t start_;
void add_type_type(org::apache::arrow::flatbuf::Type type_type) {
fbb_.AddElement<uint8_t>(SparseTensor::VT_TYPE_TYPE, static_cast<uint8_t>(type_type), 0);
}
void add_type(flatbuffers::Offset<void> type) {
fbb_.AddOffset(SparseTensor::VT_TYPE, type);
}
void add_shape(flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<org::apache::arrow::flatbuf::TensorDim>>> shape) {
fbb_.AddOffset(SparseTensor::VT_SHAPE, shape);
}
void add_non_zero_length(int64_t non_zero_length) {
fbb_.AddElement<int64_t>(SparseTensor::VT_NON_ZERO_LENGTH, non_zero_length, 0);
}
void add_sparseIndex_type(org::apache::arrow::flatbuf::SparseTensorIndex sparseIndex_type) {
fbb_.AddElement<uint8_t>(SparseTensor::VT_SPARSEINDEX_TYPE, static_cast<uint8_t>(sparseIndex_type), 0);
}
void add_sparseIndex(flatbuffers::Offset<void> sparseIndex) {
fbb_.AddOffset(SparseTensor::VT_SPARSEINDEX, sparseIndex);
}
void add_data(const org::apache::arrow::flatbuf::Buffer *data) {
fbb_.AddStruct(SparseTensor::VT_DATA, data);
}
explicit SparseTensorBuilder(flatbuffers::FlatBufferBuilder &_fbb)
: fbb_(_fbb) {
start_ = fbb_.StartTable();
}
flatbuffers::Offset<SparseTensor> Finish() {
const auto end = fbb_.EndTable(start_);
auto o = flatbuffers::Offset<SparseTensor>(end);
fbb_.Required(o, SparseTensor::VT_TYPE);
fbb_.Required(o, SparseTensor::VT_SHAPE);
fbb_.Required(o, SparseTensor::VT_SPARSEINDEX);
fbb_.Required(o, SparseTensor::VT_DATA);
return o;
}
};
inline flatbuffers::Offset<SparseTensor> CreateSparseTensor(
flatbuffers::FlatBufferBuilder &_fbb,
org::apache::arrow::flatbuf::Type type_type = org::apache::arrow::flatbuf::Type::NONE,
flatbuffers::Offset<void> type = 0,
flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<org::apache::arrow::flatbuf::TensorDim>>> shape = 0,
int64_t non_zero_length = 0,
org::apache::arrow::flatbuf::SparseTensorIndex sparseIndex_type = org::apache::arrow::flatbuf::SparseTensorIndex::NONE,
flatbuffers::Offset<void> sparseIndex = 0,
const org::apache::arrow::flatbuf::Buffer *data = 0) {
SparseTensorBuilder builder_(_fbb);
builder_.add_non_zero_length(non_zero_length);
builder_.add_data(data);
builder_.add_sparseIndex(sparseIndex);
builder_.add_shape(shape);
builder_.add_type(type);
builder_.add_sparseIndex_type(sparseIndex_type);
builder_.add_type_type(type_type);
return builder_.Finish();
}
inline flatbuffers::Offset<SparseTensor> CreateSparseTensorDirect(
flatbuffers::FlatBufferBuilder &_fbb,
org::apache::arrow::flatbuf::Type type_type = org::apache::arrow::flatbuf::Type::NONE,
flatbuffers::Offset<void> type = 0,
const std::vector<flatbuffers::Offset<org::apache::arrow::flatbuf::TensorDim>> *shape = nullptr,
int64_t non_zero_length = 0,
org::apache::arrow::flatbuf::SparseTensorIndex sparseIndex_type = org::apache::arrow::flatbuf::SparseTensorIndex::NONE,
flatbuffers::Offset<void> sparseIndex = 0,
const org::apache::arrow::flatbuf::Buffer *data = 0) {
auto shape__ = shape ? _fbb.CreateVector<flatbuffers::Offset<org::apache::arrow::flatbuf::TensorDim>>(*shape) : 0;
return org::apache::arrow::flatbuf::CreateSparseTensor(
_fbb,
type_type,
type,
shape__,
non_zero_length,
sparseIndex_type,
sparseIndex,
data);
}
inline bool VerifySparseTensorIndex(flatbuffers::Verifier &verifier, const void *obj, SparseTensorIndex type) {
switch (type) {
case SparseTensorIndex::NONE: {
return true;
}
case SparseTensorIndex::SparseTensorIndexCOO: {
auto ptr = reinterpret_cast<const org::apache::arrow::flatbuf::SparseTensorIndexCOO *>(obj);
return verifier.VerifyTable(ptr);
}
case SparseTensorIndex::SparseMatrixIndexCSX: {
auto ptr = reinterpret_cast<const org::apache::arrow::flatbuf::SparseMatrixIndexCSX *>(obj);
return verifier.VerifyTable(ptr);
}
case SparseTensorIndex::SparseTensorIndexCSF: {
auto ptr = reinterpret_cast<const org::apache::arrow::flatbuf::SparseTensorIndexCSF *>(obj);
return verifier.VerifyTable(ptr);
}
default: return true;
}
}
inline bool VerifySparseTensorIndexVector(flatbuffers::Verifier &verifier, const flatbuffers::Vector<flatbuffers::Offset<void>> *values, const flatbuffers::Vector<uint8_t> *types) {
if (!values || !types) return !values && !types;
if (values->size() != types->size()) return false;
for (flatbuffers::uoffset_t i = 0; i < values->size(); ++i) {
if (!VerifySparseTensorIndex(
verifier, values->Get(i), types->GetEnum<SparseTensorIndex>(i))) {
return false;
}
}
return true;
}
inline const org::apache::arrow::flatbuf::SparseTensor *GetSparseTensor(const void *buf) {
return flatbuffers::GetRoot<org::apache::arrow::flatbuf::SparseTensor>(buf);
}
inline const org::apache::arrow::flatbuf::SparseTensor *GetSizePrefixedSparseTensor(const void *buf) {
return flatbuffers::GetSizePrefixedRoot<org::apache::arrow::flatbuf::SparseTensor>(buf);
}
inline bool VerifySparseTensorBuffer(
flatbuffers::Verifier &verifier) {
return verifier.VerifyBuffer<org::apache::arrow::flatbuf::SparseTensor>(nullptr);
}
inline bool VerifySizePrefixedSparseTensorBuffer(
flatbuffers::Verifier &verifier) {
return verifier.VerifySizePrefixedBuffer<org::apache::arrow::flatbuf::SparseTensor>(nullptr);
}
inline void FinishSparseTensorBuffer(
flatbuffers::FlatBufferBuilder &fbb,
flatbuffers::Offset<org::apache::arrow::flatbuf::SparseTensor> root) {
fbb.Finish(root);
}
inline void FinishSizePrefixedSparseTensorBuffer(
flatbuffers::FlatBufferBuilder &fbb,
flatbuffers::Offset<org::apache::arrow::flatbuf::SparseTensor> root) {
fbb.FinishSizePrefixed(root);
}
} // namespace flatbuf
} // namespace arrow
} // namespace apache
} // namespace org
#endif // FLATBUFFERS_GENERATED_SPARSETENSOR_ORG_APACHE_ARROW_FLATBUF_H_