File size: 30,084 Bytes
3020b27
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
<?xml version="1.0"?>
<net name="tokenizer" version="11">
	<layers>
		<layer id="0" name="Parameter_306401" type="Parameter" version="opset1">
			<data shape="?" element_type="string" />
			<output>
				<port id="0" precision="STRING" names="Parameter_306401">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="1" name="Constant_306500" type="Const" version="opset1">
			<data element_type="i32" shape="" offset="0" size="4" />
			<output>
				<port id="0" precision="I32" />
			</output>
		</layer>
		<layer id="2" name="Constant_306501" type="Const" version="opset1">
			<data element_type="i32" shape="" offset="4" size="4" />
			<output>
				<port id="0" precision="I32" />
			</output>
		</layer>
		<layer id="3" name="Constant_306502" type="Const" version="opset1">
			<data element_type="i32" shape="1" offset="8" size="4" />
			<output>
				<port id="0" precision="I32">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="4" name="Constant_306503" type="Const" version="opset1">
			<data element_type="i32" shape="" offset="0" size="4" />
			<output>
				<port id="0" precision="I32" />
			</output>
		</layer>
		<layer id="5" name="Constant_306504" type="Const" version="opset1">
			<data element_type="i32" shape="" offset="4" size="4" />
			<output>
				<port id="0" precision="I32" />
			</output>
		</layer>
		<layer id="6" name="Constant_306505" type="Const" version="opset1">
			<data element_type="i32" shape="1" offset="12" size="4" />
			<output>
				<port id="0" precision="I32">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="7" name="Constant_306407" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="16" size="8" />
			<output>
				<port id="0" precision="I64" />
			</output>
		</layer>
		<layer id="8" name="StringTensorUnpack_306402" type="StringTensorUnpack" version="extension">
			<data mode="begins_ends" />
			<input>
				<port id="0" precision="STRING">
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="9" name="ShapeOf_306403" type="ShapeOf" version="opset3">
			<data output_type="i64" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="10" name="Constant_306404" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="16" size="8" />
			<output>
				<port id="0" precision="I64" />
			</output>
		</layer>
		<layer id="11" name="Constant_306405" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="16" size="8" />
			<output>
				<port id="0" precision="I64" />
			</output>
		</layer>
		<layer id="12" name="Gather_306406" type="Gather" version="opset8">
			<data batch_dims="0" />
			<input>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
				<port id="1" precision="I64" />
				<port id="2" precision="I64" />
			</input>
			<output>
				<port id="3" precision="I64" />
			</output>
		</layer>
		<layer id="13" name="Constant_306408" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="24" size="8" />
			<output>
				<port id="0" precision="I64" />
			</output>
		</layer>
		<layer id="14" name="Range_306409" type="Range" version="opset4">
			<data output_type="i32" />
			<input>
				<port id="0" precision="I64" />
				<port id="1" precision="I64" />
				<port id="2" precision="I64" />
			</input>
			<output>
				<port id="3" precision="I32">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="15" name="Constant_306410" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="24" size="8" />
			<output>
				<port id="0" precision="I64" />
			</output>
		</layer>
		<layer id="16" name="Constant_306411" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="24" size="8" />
			<output>
				<port id="0" precision="I64" />
			</output>
		</layer>
		<layer id="17" name="Add_306412" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="I64" />
				<port id="1" precision="I64" />
			</input>
			<output>
				<port id="2" precision="I64" />
			</output>
		</layer>
		<layer id="18" name="Constant_306413" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="24" size="8" />
			<output>
				<port id="0" precision="I64" />
			</output>
		</layer>
		<layer id="19" name="Range_306414" type="Range" version="opset4">
			<data output_type="i32" />
			<input>
				<port id="0" precision="I64" />
				<port id="1" precision="I64" />
				<port id="2" precision="I64" />
			</input>
			<output>
				<port id="3" precision="I32">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="20" name="Constant_306476" type="Const" version="opset1">
			<data element_type="u8" shape="244" offset="32" size="244" />
			<output>
				<port id="0" precision="U8">
					<dim>244</dim>
				</port>
			</output>
		</layer>
		<layer id="21" name="SpecialTokensSplit_306477" type="SpecialTokensSplit" version="extension">
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="4" precision="U8">
					<dim>-1</dim>
				</port>
				<port id="5" precision="U8">
					<dim>244</dim>
				</port>
			</input>
			<output>
				<port id="6" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="7" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="8" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="9" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="10" precision="U8">
					<dim>-1</dim>
				</port>
				<port id="11" precision="BOOL">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="22" name="NormalizeUnicode_306478" type="NormalizeUnicode" version="extension">
			<data normalization_form="NFC" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="U8">
					<dim>-1</dim>
				</port>
				<port id="3" precision="BOOL">
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="4" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="5" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="6" precision="U8">
					<dim>-1</dim>
				</port>
				<port id="7" precision="BOOL">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="23" name="Constant_306480" type="Const" version="opset1">
			<data element_type="u8" shape="115" offset="276" size="115" />
			<output>
				<port id="0" precision="U8">
					<dim>115</dim>
				</port>
			</output>
		</layer>
		<layer id="24" name="RegexSplit_306481" type="RegexSplit" version="extension">
			<data behaviour="contiguous" invert="false" max_splits="-1" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="4" precision="U8">
					<dim>-1</dim>
				</port>
				<port id="5" precision="BOOL">
					<dim>-1</dim>
				</port>
				<port id="6" precision="U8">
					<dim>115</dim>
				</port>
			</input>
			<output>
				<port id="7" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="8" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="9" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="10" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="11" precision="U8">
					<dim>-1</dim>
				</port>
				<port id="12" precision="BOOL">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="25" name="Constant_306483" type="Const" version="opset1">
			<data element_type="u8" shape="1623592" offset="391" size="1623592" />
			<output>
				<port id="0" precision="U8">
					<dim>1623592</dim>
				</port>
			</output>
		</layer>
		<layer id="26" name="StringTensorUnpack_306484" type="StringTensorUnpack" version="extension">
			<data mode="begins_ends" />
			<input>
				<port id="0" precision="U8">
					<dim>1623592</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="27" name="Constant_306489" type="Const" version="opset1">
			<data element_type="u8" shape="1100616" offset="1623983" size="1100616" />
			<output>
				<port id="0" precision="U8">
					<dim>1100616</dim>
				</port>
			</output>
		</layer>
		<layer id="28" name="StringTensorUnpack_306490" type="StringTensorUnpack" version="extension">
			<data mode="begins_ends" />
			<input>
				<port id="0" precision="U8">
					<dim>1100616</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="29" name="Constant_306492" type="Const" version="opset1">
			<data element_type="u8" shape="1106903" offset="2724599" size="1106903" />
			<output>
				<port id="0" precision="U8">
					<dim>1106903</dim>
				</port>
			</output>
		</layer>
		<layer id="30" name="StringTensorUnpack_306493" type="StringTensorUnpack" version="extension">
			<data mode="begins_ends" />
			<input>
				<port id="0" precision="U8">
					<dim>1106903</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="31" name="Constant_306486" type="Const" version="opset1">
			<data element_type="u8" shape="14600" offset="3831502" size="14600" />
			<output>
				<port id="0" precision="U8">
					<dim>14600</dim>
				</port>
			</output>
		</layer>
		<layer id="32" name="StringTensorUnpack_306487" type="StringTensorUnpack" version="extension">
			<data mode="begins_ends" />
			<input>
				<port id="0" precision="U8">
					<dim>14600</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="U8">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="33" name="Constant_306494" type="Const" version="opset1">
			<data element_type="i32" shape="1072" offset="3846102" size="4288" />
			<output>
				<port id="0" precision="I32">
					<dim>1072</dim>
				</port>
			</output>
		</layer>
		<layer id="34" name="BPETokenizer_306495" type="BPETokenizer" version="extension">
			<data unk_token="" fuse_unk="false" suffix_indicator="" end_suffix="" byte_fallback="false" cache_capacity="30268" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="4" precision="U8">
					<dim>-1</dim>
				</port>
				<port id="5" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="6" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="7" precision="U8">
					<dim>-1</dim>
				</port>
				<port id="8" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="9" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="10" precision="U8">
					<dim>-1</dim>
				</port>
				<port id="11" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="12" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="13" precision="U8">
					<dim>-1</dim>
				</port>
				<port id="14" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="15" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="16" precision="U8">
					<dim>-1</dim>
				</port>
				<port id="17" precision="I32">
					<dim>1072</dim>
				</port>
			</input>
			<output>
				<port id="18" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="19" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="20" precision="I32">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="35" name="Subtract_306496" type="Subtract" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="36" name="Constant_306497" type="Const" version="opset1">
			<data element_type="i32" shape="" offset="3850390" size="4" />
			<output>
				<port id="0" precision="I32" />
			</output>
		</layer>
		<layer id="37" name="Minimum_306498" type="Minimum" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32" />
			</input>
			<output>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="38" name="Add_306499" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="39" name="Constant_306506" type="Const" version="opset1">
			<data element_type="i32" shape="3" offset="3850394" size="12" />
			<output>
				<port id="0" precision="I32">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="40" name="CombineSegments_306507" type="CombineSegments" version="extension">
			<input>
				<port id="0" precision="I32" />
				<port id="1" precision="I32" />
				<port id="2" precision="I32">
					<dim>1</dim>
				</port>
				<port id="3" precision="I32" />
				<port id="4" precision="I32" />
				<port id="5" precision="I32">
					<dim>1</dim>
				</port>
				<port id="6" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="7" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="8" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="9" precision="I32">
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="10" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="11" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="12" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="13" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="14" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="15" precision="I32">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="41" name="Subtract_306508" type="Subtract" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="42" name="Constant_306509" type="Const" version="opset1">
			<data element_type="i32" shape="" offset="0" size="4" />
			<output>
				<port id="0" precision="I32" />
			</output>
		</layer>
		<layer id="43" name="ReduceMax_306510" type="ReduceMax" version="opset1">
			<data keep_dims="false" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32" />
			</input>
			<output>
				<port id="2" precision="I32" />
			</output>
		</layer>
		<layer id="44" name="Constant_306511" type="Const" version="opset1">
			<data element_type="i32" shape="" offset="3850406" size="4" />
			<output>
				<port id="0" precision="I32" />
			</output>
		</layer>
		<layer id="45" name="RaggedToDense_306512" type="RaggedToDense" version="extension">
			<data pad_right="false" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="I32" />
				<port id="4" precision="I32" />
			</input>
			<output>
				<port id="5" precision="I32">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="6" precision="BOOL">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="46" name="Convert_306513" type="Convert" version="opset1">
			<data destination_type="i32" />
			<input>
				<port id="0" precision="BOOL">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I32">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="47" name="Convert_306513" type="Convert" version="opset1">
			<data destination_type="i64" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64" names="attention_mask">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="49" name="Constant_306514" type="Const" version="opset1">
			<data element_type="i32" shape="" offset="3850406" size="4" />
			<output>
				<port id="0" precision="I32" />
			</output>
		</layer>
		<layer id="50" name="RaggedToDense_306515" type="RaggedToDense" version="extension">
			<data pad_right="false" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="2" precision="I32">
					<dim>-1</dim>
				</port>
				<port id="3" precision="I32" />
				<port id="4" precision="I32" />
			</input>
			<output>
				<port id="5" precision="I32">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="6" precision="BOOL">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="51" name="RaggedToDense_306515.0" type="Convert" version="opset1">
			<data destination_type="i64" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64" names="token_type_ids">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="53" name="RaggedToDense_306512.0" type="Convert" version="opset1">
			<data destination_type="i64" />
			<input>
				<port id="0" precision="I32">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64" names="input_ids">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="54" name="Result_306516" type="Result" version="opset1">
			<input>
				<port id="0" precision="I64">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
		</layer>
		<layer id="52" name="Result_306517" type="Result" version="opset1">
			<input>
				<port id="0" precision="I64">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
		</layer>
		<layer id="48" name="Result_306518" type="Result" version="opset1">
			<input>
				<port id="0" precision="I64">
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
		</layer>
	</layers>
	<edges>
		<edge from-layer="0" from-port="0" to-layer="8" to-port="0" />
		<edge from-layer="1" from-port="0" to-layer="40" to-port="0" />
		<edge from-layer="2" from-port="0" to-layer="40" to-port="1" />
		<edge from-layer="3" from-port="0" to-layer="40" to-port="2" />
		<edge from-layer="4" from-port="0" to-layer="40" to-port="3" />
		<edge from-layer="5" from-port="0" to-layer="40" to-port="4" />
		<edge from-layer="6" from-port="0" to-layer="40" to-port="5" />
		<edge from-layer="7" from-port="0" to-layer="14" to-port="0" />
		<edge from-layer="8" from-port="1" to-layer="9" to-port="0" />
		<edge from-layer="8" from-port="3" to-layer="21" to-port="4" />
		<edge from-layer="8" from-port="2" to-layer="21" to-port="3" />
		<edge from-layer="8" from-port="1" to-layer="21" to-port="2" />
		<edge from-layer="9" from-port="1" to-layer="12" to-port="0" />
		<edge from-layer="10" from-port="0" to-layer="12" to-port="1" />
		<edge from-layer="11" from-port="0" to-layer="12" to-port="2" />
		<edge from-layer="12" from-port="3" to-layer="14" to-port="1" />
		<edge from-layer="12" from-port="3" to-layer="17" to-port="0" />
		<edge from-layer="13" from-port="0" to-layer="14" to-port="2" />
		<edge from-layer="14" from-port="3" to-layer="21" to-port="0" />
		<edge from-layer="15" from-port="0" to-layer="19" to-port="0" />
		<edge from-layer="16" from-port="0" to-layer="17" to-port="1" />
		<edge from-layer="17" from-port="2" to-layer="19" to-port="1" />
		<edge from-layer="18" from-port="0" to-layer="19" to-port="2" />
		<edge from-layer="19" from-port="3" to-layer="21" to-port="1" />
		<edge from-layer="20" from-port="0" to-layer="21" to-port="5" />
		<edge from-layer="21" from-port="9" to-layer="22" to-port="1" />
		<edge from-layer="21" from-port="10" to-layer="22" to-port="2" />
		<edge from-layer="21" from-port="11" to-layer="22" to-port="3" />
		<edge from-layer="21" from-port="6" to-layer="24" to-port="0" />
		<edge from-layer="21" from-port="7" to-layer="24" to-port="1" />
		<edge from-layer="21" from-port="8" to-layer="22" to-port="0" />
		<edge from-layer="22" from-port="6" to-layer="24" to-port="4" />
		<edge from-layer="22" from-port="7" to-layer="24" to-port="5" />
		<edge from-layer="22" from-port="5" to-layer="24" to-port="3" />
		<edge from-layer="22" from-port="4" to-layer="24" to-port="2" />
		<edge from-layer="23" from-port="0" to-layer="24" to-port="6" />
		<edge from-layer="24" from-port="9" to-layer="34" to-port="2" />
		<edge from-layer="24" from-port="10" to-layer="34" to-port="3" />
		<edge from-layer="24" from-port="11" to-layer="34" to-port="4" />
		<edge from-layer="24" from-port="8" to-layer="34" to-port="1" />
		<edge from-layer="24" from-port="7" to-layer="34" to-port="0" />
		<edge from-layer="25" from-port="0" to-layer="26" to-port="0" />
		<edge from-layer="26" from-port="1" to-layer="34" to-port="5" />
		<edge from-layer="26" from-port="2" to-layer="34" to-port="6" />
		<edge from-layer="26" from-port="3" to-layer="34" to-port="7" />
		<edge from-layer="27" from-port="0" to-layer="28" to-port="0" />
		<edge from-layer="28" from-port="3" to-layer="34" to-port="10" />
		<edge from-layer="28" from-port="1" to-layer="34" to-port="8" />
		<edge from-layer="28" from-port="2" to-layer="34" to-port="9" />
		<edge from-layer="29" from-port="0" to-layer="30" to-port="0" />
		<edge from-layer="30" from-port="3" to-layer="34" to-port="13" />
		<edge from-layer="30" from-port="1" to-layer="34" to-port="11" />
		<edge from-layer="30" from-port="2" to-layer="34" to-port="12" />
		<edge from-layer="31" from-port="0" to-layer="32" to-port="0" />
		<edge from-layer="32" from-port="1" to-layer="34" to-port="14" />
		<edge from-layer="32" from-port="2" to-layer="34" to-port="15" />
		<edge from-layer="32" from-port="3" to-layer="34" to-port="16" />
		<edge from-layer="33" from-port="0" to-layer="34" to-port="17" />
		<edge from-layer="34" from-port="18" to-layer="38" to-port="0" />
		<edge from-layer="34" from-port="20" to-layer="40" to-port="8" />
		<edge from-layer="34" from-port="18" to-layer="40" to-port="6" />
		<edge from-layer="34" from-port="19" to-layer="35" to-port="0" />
		<edge from-layer="34" from-port="18" to-layer="35" to-port="1" />
		<edge from-layer="35" from-port="2" to-layer="37" to-port="0" />
		<edge from-layer="36" from-port="0" to-layer="37" to-port="1" />
		<edge from-layer="37" from-port="2" to-layer="38" to-port="1" />
		<edge from-layer="38" from-port="2" to-layer="40" to-port="7" />
		<edge from-layer="39" from-port="0" to-layer="40" to-port="9" />
		<edge from-layer="40" from-port="11" to-layer="41" to-port="0" />
		<edge from-layer="40" from-port="15" to-layer="50" to-port="2" />
		<edge from-layer="40" from-port="14" to-layer="50" to-port="1" />
		<edge from-layer="40" from-port="13" to-layer="50" to-port="0" />
		<edge from-layer="40" from-port="12" to-layer="45" to-port="2" />
		<edge from-layer="40" from-port="11" to-layer="45" to-port="1" />
		<edge from-layer="40" from-port="10" to-layer="45" to-port="0" />
		<edge from-layer="40" from-port="10" to-layer="41" to-port="1" />
		<edge from-layer="41" from-port="2" to-layer="43" to-port="0" />
		<edge from-layer="42" from-port="0" to-layer="43" to-port="1" />
		<edge from-layer="43" from-port="2" to-layer="45" to-port="3" />
		<edge from-layer="43" from-port="2" to-layer="50" to-port="3" />
		<edge from-layer="44" from-port="0" to-layer="45" to-port="4" />
		<edge from-layer="45" from-port="6" to-layer="46" to-port="0" />
		<edge from-layer="45" from-port="5" to-layer="53" to-port="0" />
		<edge from-layer="46" from-port="1" to-layer="47" to-port="0" />
		<edge from-layer="47" from-port="1" to-layer="48" to-port="0" />
		<edge from-layer="49" from-port="0" to-layer="50" to-port="4" />
		<edge from-layer="50" from-port="5" to-layer="51" to-port="0" />
		<edge from-layer="51" from-port="1" to-layer="52" to-port="0" />
		<edge from-layer="53" from-port="1" to-layer="54" to-port="0" />
	</edges>
	<rt_info>
		<add_attention_mask value="True" />
		<add_prefix_space />
		<add_special_tokens value="True" />
		<chat_template value="[gMASK]&lt;sop>{% for item in messages %}{% if item['tools'] is defined %}&lt;|system|>&#10;你是一个名为 ChatGLM 的人工智能助手。你是基于智谱AI训练的语言模型 GLM-4 模型开发的,你的任务是针对用户的问题和要求提供适当的答复和支持。&#10;&#10;# 可用工具{% set tools = item['tools'] %}{% for tool in tools %}{% if tool['type'] == 'function' %}&#10;&#10;## {{ tool['function']['name'] }}&#10;&#10;{{ tool['function'] | tojson(indent=4) }}&#10;在调用上述函数时,请使用 Json 格式表示调用的参数。{% elif tool['type'] == 'python' %}&#10;&#10;## python&#10;&#10;当你向 `python` 发送包含 Python 代码的消息时,该代码将会在一个有状态的 Jupyter notebook 环境中执行。&#10;`python` 返回代码执行的输出,或在执行 60 秒后返回超时。&#10;`/mnt/data` 将会持久化存储你的文件。在此会话中,`python` 无法访问互联网。不要使用 `python` 进行任何网络请求或者在线 API 调用,这些在线内容的访问将不会成功。{% elif tool['type'] == 'simple_browser' %}&#10;&#10;## simple_browser&#10;&#10;你可以使用 `simple_browser` 工具。该工具支持以下函数:&#10;`search(query: str, recency_days: int)`:使用搜索引擎进行查询并显示结果,可以使用 `recency_days` 参数控制搜索内容的时效性。&#10;`mclick(ids: list[int])`:获取一系列指定 id 的页面内容。每次调用时,须选择3-10个页面。选择多个角度的页面,同时尽可能选择可信任的信息来源。考虑到部分页面是无法加载的,你也可以多打开一些可能有用的页面而不用担心内容过多。&#10;`open_url(url: str)`:打开指定的 URL。&#10;&#10;使用 `【{引用 id}†{引用文本}】` 来引用内容。&#10;&#10;操作步骤:1. 使用 `search` 来获得信息列表; 2. 使用 `mclick` 来获取指定 ID 页面的内容; 3. 根据获得的内容进行回复。在回复中应当引用信息来源。&#10; 如果用户提供了 URL,也可以用 `open_url` 直接打开页面。&#10;如果初次搜索结果没有找到合适的信息,也可以再次使用 `search` 进行搜索。{% elif tool['type'] == 'cogview' %}&#10;&#10;## cogview&#10;&#10;如果用户的请求中包含了对图像的描述,你可以使用 `cogview` 来生成图像并展示给用户。你需要向 `cogview` 发送图像描述,规则:&#10;- 发送给 `cogview` 的消息必须使用英语。用户的中文描述必须完全翻译为英语。&#10;- 应当尽可能详细地描述图像生成的需求,需求描述约 100 英文单词。&#10;- 保持用户原始描述的意图。不要虚构内容或者没见过的人物。&#10;- 如无特殊说明,所在地为中国,持有中国立场并遵循中国社会主义价值观。{% endif %}{% endfor %}{% endif %}{% if item['content'] %}&lt;|{{ item['role'] }}|>{{ item['metadata'] }}&#10;{{ item['content'] }}{% endif %}{% endfor %}{% if add_generation_prompt %}&lt;|assistant|>{% endif %}" />
		<clean_up_tokenization_spaces value="False" />
		<detokenizer_input_type value="i64" />
		<eos_token_id value="151329" />
		<handle_special_tokens_with_re />
		<number_of_inputs value="1" />
		<openvino_tokenizers_version value="2024.5.0.0.dev20241030" />
		<openvino_version value="2024.5.0.dev20241030" />
		<original_tokenizer_class value="&lt;class 'transformers_modules.THUDM.glm-4-9b-chat.eb55a443d66541f30869f6caac5ad0d2e95bcbaa.tokenization_chatglm.ChatGLM4Tokenizer'>" />
		<pad_token_id value="151329" />
		<sentencepiece_version value="0.2.0" />
		<skip_special_tokens value="True" />
		<streaming_detokenizer value="False" />
		<tiktoken_version value="0.8.0" />
		<tokenizer_output_type value="i64" />
		<tokenizers_version value="0.20.1" />
		<transformers_version value="4.45.2" />
		<use_max_padding value="False" />
		<use_sentencepiece_backend value="False" />
		<utf8_replace_mode />
		<with_detokenizer value="True" />
	</rt_info>
</net>