def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [7, 8]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
results, rf = cross_val_cache.load()
job_samples = 50
tree_path_dependent_shap_interact_cache = SimpleCache(
f"tree_path_dependent_shap_interact_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap_interaction"),
)
@tree_path_dependent_shap_interact_cache
def get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=True)
get_interact_shap_values(
rf, X_train[index * job_samples : (index + 1) * job_samples]
)
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
5,
76,
82,
89,
258,
259,
263,
317,
318,
329,
349,
352,
425,
434,
451,
452,
453,
457,
461,
462,
472,
473,
589,
590,
600,
626,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
rf = get_model()
job_samples = 2000
tree_path_dependent_shap_cache = SimpleCache(
f"tree_path_dependent_shap_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap"),
)
@tree_path_dependent_shap_cache
def cached_get_shap_values(model, X):
return get_shap_values(model, X, interaction=False)
cached_get_shap_values(rf, X_train[index * job_samples : (index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
54,
55,
56,
57,
58,
65,
66,
72,
73,
82,
83,
84,
85,
92,
93,
94,
112,
113,
114,
115,
116,
118,
119,
128,
131,
132,
133,
134,
135,
136,
137,
138,
139,
143,
144,
147,
148,
164,
165,
166,
167,
172,
173,
174,
196,
197,
198,
199,
201,
203,
204,
212,
215,
216,
217,
218,
220,
221,
222,
223,
224,
230,
231,
236,
237,
247,
248,
249,
250,
251,
254,
255,
256,
259,
293,
294,
295,
296,
298,
299,
300,
305,
307,
308,
309,
310,
311,
312,
313,
314,
315,
325,
326,
328,
329,
352,
353,
354,
355,
356,
360,
361,
362,
370,
419,
420,
421,
422,
425,
426,
427,
428,
431,
432,
433,
434,
435,
436,
437,
438,
439,
446,
447,
455,
456,
489,
490,
491,
492,
493,
495,
496,
497,
504,
532,
533,
534,
535,
538,
539,
540,
546,
550,
551,
552,
556,
557,
558,
559,
560,
561,
577,
578,
587,
588,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
rf = get_model()
job_samples = 2000
tree_path_dependent_shap_cache = SimpleCache(
f"tree_path_dependent_shap_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap"),
)
@tree_path_dependent_shap_cache
def cached_get_shap_values(model, X):
return get_shap_values(model, X, interaction=False)
cached_get_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
115,
989,
1102,
1163,
1236,
1275,
1276,
1277,
1377,
1378,
1514,
1515,
1516,
1716,
1771,
1772,
1773,
1774,
1867,
1940,
1955,
2095,
2174,
2301,
2827,
2908,
2947,
2958,
2960,
3138,
3168,
3169,
3782,
3783,
3784,
3785,
3786,
3787,
4108,
4128,
4129,
4130,
4131,
4132,
4224,
4281,
4302,
4357,
4435,
4436,
4579,
4673,
4865,
4904,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
results, rf = cross_val_cache.load()
job_samples = 50
tree_path_dependent_shap_interact_cache = SimpleCache(
f"tree_path_dependent_shap_interact_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap_interaction"),
)
@tree_path_dependent_shap_interact_cache
def get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=True)
get_interact_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
5,
6,
7,
8,
9,
10,
11,
12,
13,
17,
22,
23,
24,
26,
27,
28,
32,
35,
36,
42,
46,
48,
58,
59,
60,
61,
62,
64,
75,
76,
77,
78,
79,
80,
81,
82,
83,
89,
90,
91,
92,
93,
94,
95,
96,
97,
98,
99,
100,
101,
102,
110,
113,
114,
115,
116,
117,
118,
119,
120,
121,
137,
138,
139,
140,
141,
142,
145,
146,
147,
148,
149,
150,
151,
152,
153,
154,
155,
156,
182,
183,
213,
214,
215,
216,
217,
218,
219,
220,
221,
222,
223,
224,
225,
226,
227,
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,
332,
338,
339,
340,
344,
345,
346,
348,
351,
352,
353,
354,
355,
356,
357,
358,
359,
360,
361,
362,
363,
364,
365,
366,
367,
368,
369,
375,
390,
391,
392,
393,
394,
395,
396,
399,
400,
401,
402,
403,
404,
406,
407,
408,
409,
410,
411,
412,
413,
414,
415,
416,
417,
418,
419,
420,
421,
426,
444,
445,
446,
447,
448,
449,
450,
451,
452,
453,
454,
455,
456,
484,
487,
488,
527,
529,
530,
531,
533,
534,
535,
536,
537,
538,
539,
540,
572,
574,
575,
577,
578,
579,
580,
581,
584,
585,
586,
587,
588,
603,
617,
618,
619,
620,
621,
622,
623,
624,
628,
629,
630,
631,
632,
633,
634,
635,
636,
637,
638,
639,
640,
641,
643,
644,
647,
648,
649,
650,
651,
652,
666,
679,
685,
686,
695,
696,
697,
698,
699,
700,
701,
702,
704,
705,
706,
707,
708,
709,
710,
711,
712,
713,
714,
715,
717,
718,
719,
720,
721,
722,
724,
725,
727,
728,
729,
730,
731,
732,
733,
734,
745,
746,
769,
770,
771,
782,
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,
818,
834,
843,
845,
846,
847,
849,
850,
851,
852,
856,
857,
868,
869,
892,
893,
894,
895,
941,
942,
963,
965,
972,
973,
974,
988,
989,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
results, rf = cross_val_cache.load()
job_samples = 2000
tree_path_dependent_shap_cache = SimpleCache(
f"tree_path_dependent_shap_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap"),
)
@tree_path_dependent_shap_cache
def get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=False)
get_interact_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
8,
50,
51,
58,
60,
61,
62,
63,
64,
68,
94,
219,
265,
266,
268,
314,
315,
317,
319,
320,
321,
322,
347,
348,
379,
383,
384,
392,
419,
420,
421,
422,
453,
456,
458,
472,
473,
474,
475,
476,
489,
537,
538,
540,
542,
571,
572,
573,
574,
654,
655,
664,
665,
666,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
rf = get_model()
job_samples = 2000
tree_path_dependent_shap_cache = SimpleCache(
f"tree_path_dependent_shap_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap"),
)
@tree_path_dependent_shap_cache
def cached_get_shap_values(model, X):
return get_shap_values(model, X, interaction=False)
cached_get_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
3,
4,
6,
7,
41,
42,
43,
44,
45,
46,
47,
48,
58,
59,
60,
61,
62,
63,
65,
66,
69,
71,
72,
73,
74,
75,
76,
77,
78,
87,
88,
112,
113,
114,
115,
116,
117,
121,
122,
123,
124,
125,
127,
128,
129,
130,
131,
133,
134,
136,
137,
142,
143,
144,
147,
150,
151,
153,
154,
179,
180,
182,
183,
185,
186,
187,
188,
196,
197,
198,
199,
200,
201,
205,
209,
210,
211,
222,
223,
241,
242,
243,
244,
245,
246,
247,
248,
249,
250,
251,
252,
253,
256,
257,
258,
259,
260,
261,
262,
263,
264,
270,
272,
273,
274,
278,
279,
280,
283,
284,
303,
304,
305,
306,
307,
308,
309,
310,
313,
314,
316,
325,
326,
327,
328,
329,
330,
334,
337,
338,
339,
351,
352,
361,
362,
363,
364,
365,
366,
367,
368,
369,
370,
371,
372,
374,
375,
376,
377,
378,
379,
380,
382,
383,
389,
390,
391,
394,
398,
400,
401,
402,
403,
422,
423,
425,
426,
429,
431,
432,
433,
442,
443,
444,
445,
446,
447,
450,
454,
455,
456,
464,
465,
479,
480,
481,
482,
483,
484,
485,
486,
487,
488,
489,
490,
493,
494,
495,
496,
497,
498,
499,
501,
502,
515,
521,
522,
523,
529,
530,
531,
534,
535,
539,
540,
552,
553,
554,
555,
557,
558,
559,
560,
564,
565,
566,
568,
569,
570,
573,
575,
576,
577,
578,
591,
593,
594,
595,
596,
597,
598,
599,
600,
601,
602,
603,
605,
606,
607,
608,
609,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
rf = get_model()
job_samples = 2000
tree_path_dependent_shap_cache = SimpleCache(
f"tree_path_dependent_shap_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap"),
)
@tree_path_dependent_shap_cache
def cached_get_shap_values(model, X):
return get_shap_values(model, X, interaction=False)
cached_get_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
108,
148,
153,
454,
515,
532,
551,
581,
603,
607,
608,
618,
646,
647,
648,
669,
850,
852,
867,
944,
945,
983,
984,
985,
987,
989,
991,
1006,
1009,
1010,
1020,
1072,
1182,
1205,
1211,
1215,
1237,
1262,
1263,
1271,
1295,
1296,
1310,
1314,
1315,
1324,
1339,
1345,
1390,
1405,
1521,
1546,
1555,
1582,
1671,
1835,
2182,
2399,
2826,
2918,
2971,
2972,
3006,
3061,
3092,
3093,
3211,
3227,
3233,
3297,
3308,
3396,
3397,
4125,
4148,
4177,
4203,
4312,
4339,
4340,
4365,
4366,
4371,
4406,
4407,
4408,
4430,
4431,
4483,
4484,
4486,
4546,
4559,
4713,
4994,
4996,
5940,
5965,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
rf = get_model()
job_samples = 50
tree_path_dependent_shap_interact_cache = SimpleCache(
f"tree_path_dependent_shap_interact_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap_interaction"),
)
@tree_path_dependent_shap_interact_cache
def cached_get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=True)
cached_get_interact_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
14,
43,
45,
59,
62,
73,
79,
94,
104,
110,
122,
140,
142,
150,
157,
161,
187,
196,
232,
236,
247,
264,
298,
306,
311,
312,
398,
402,
408,
410,
446,
454,
456,
459,
460,
461,
462,
464,
467,
469,
470,
471,
482,
483,
484,
492,
493,
494,
495,
496,
497,
516,
517,
518,
523,
535,
537,
543,
554,
557,
565,
572,
573,
644,
645,
646,
647,
648,
671,
673,
674,
676,
677,
678,
679,
700,
701,
715,
750,
751,
752,
753,
803,
804,
805,
814,
816,
817,
820,
822,
827,
829,
830,
831,
952,
953,
954,
989,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
results, rf = cross_val_cache.load()
job_samples = 2000
tree_path_dependent_shap_cache = SimpleCache(
f"tree_path_dependent_shap_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap"),
)
@tree_path_dependent_shap_cache
def get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=False)
get_interact_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
2,
3,
6,
7,
14,
15,
16,
17,
19,
21,
22,
28,
29,
35,
36,
52,
53,
54,
55,
59,
60,
61,
62,
68,
69,
70,
71,
72,
73,
76,
81,
82,
83,
84,
94,
98,
99,
100,
101,
102,
103,
104,
105,
106,
107,
108,
109,
111,
112,
113,
114,
115,
116,
117,
118,
119,
123,
124,
125,
129,
130,
132,
133,
134,
135,
141,
142,
155,
156,
170,
171,
172,
173,
175,
176,
177,
178,
183,
184,
185,
186,
188,
189,
196,
201,
202,
203,
204,
220,
221,
222,
223,
224,
225,
226,
227,
228,
229,
230,
231,
232,
235,
236,
237,
238,
239,
240,
241,
245,
246,
252,
254,
255,
257,
258,
261,
262,
263,
264,
266,
267,
276,
277,
311,
312,
313,
314,
316,
319,
320,
321,
327,
328,
329,
330,
331,
332,
338,
341,
342,
343,
344,
369,
372,
373,
374,
375,
376,
377,
378,
379,
380,
381,
382,
383,
384,
385,
386,
387,
388,
393,
395,
396,
401,
402,
409,
410,
411,
412,
413,
414,
422,
423,
437,
438,
439,
440,
441,
444,
445,
447,
453,
454,
455,
456,
457,
459,
462,
470,
471,
472,
473,
508,
509,
510,
511,
512,
513,
514,
515,
516,
519,
520,
521,
522,
523,
524,
525,
526,
527,
528,
535,
536,
537,
539,
540,
543,
544,
545,
546,
548,
549,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
rf = get_model()
job_samples = 50
tree_path_dependent_shap_interact_cache = SimpleCache(
f"tree_path_dependent_shap_interact_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap_interaction"),
)
@tree_path_dependent_shap_interact_cache
def cached_get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=True)
cached_get_interact_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
0,
1,
2,
3,
4,
7,
8,
9,
15,
61,
62,
63,
64,
65,
66,
68,
69,
73,
75,
76,
77,
78,
79,
80,
81,
82,
83,
92,
93,
102,
103,
119,
120,
121,
122,
123,
128,
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5966,
5967,
5968,
5969,
5970,
5972,
5973,
5974,
5975,
5976,
5978,
5979,
5982,
5983,
5990,
5994,
5995,
5997,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
rf = get_model()
job_samples = 50
tree_path_dependent_shap_interact_cache = SimpleCache(
f"tree_path_dependent_shap_interact_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap_interaction"),
)
@tree_path_dependent_shap_interact_cache
def cached_get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=True)
cached_get_interact_shap_values(
rf, X_train[index * job_samples : (index + 1) * job_samples]
)
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
2,
3,
49,
87,
88,
99,
108,
148,
152,
153,
170,
238,
239,
275,
276,
296,
297,
302,
303,
348,
349,
350,
373,
440,
441,
442,
454,
515,
532,
551,
552,
579,
581,
603,
607,
608,
618,
620,
625,
646,
647,
648,
669,
686,
701,
743,
750,
752,
850,
852,
867,
894,
896,
944,
945,
980,
983,
984,
985,
987,
989,
990,
991,
1006,
1009,
1010,
1020,
1021,
1072,
1099,
1182,
1205,
1211,
1215,
1237,
1262,
1263,
1264,
1271,
1295,
1296,
1297,
1310,
1311,
1314,
1315,
1316,
1324,
1339,
1345,
1390,
1405,
1521,
1545,
1546,
1555,
1582,
1671,
1835,
1875,
1876,
2182,
2399,
2551,
2605,
2663,
2726,
2807,
2826,
2918,
2971,
2972,
3006,
3054,
3055,
3061,
3068,
3088,
3092,
3093,
3094,
3105,
3108,
3126,
3175,
3211,
3215,
3226,
3227,
3233,
3235,
3247,
3251,
3284,
3290,
3291,
3292,
3297,
3308,
3352,
3375,
3376,
3392,
3396,
3397,
3400,
3444,
3477,
3478,
3502,
3515,
3530,
3650,
3651,
3675,
3731,
3757,
3758,
3768,
3812,
3813,
3841,
3852,
3886,
3919,
3922,
3925,
3961,
3963,
4020,
4021,
4090,
4125,
4148,
4177,
4203,
4212,
4246,
4247,
4276,
4310,
4312,
4339,
4340,
4365,
4366,
4371,
4396,
4406,
4407,
4408,
4409,
4428,
4430,
4431,
4462,
4483,
4484,
4486,
4508,
4546,
4559,
4595,
4605,
4656,
4684,
4698,
4713,
4746,
4806,
4826,
4874,
4887,
4909,
4993,
4994,
4995,
4996,
4997,
5001,
5002,
5006,
5008,
5021,
5055,
5068,
5084,
5086,
5137,
5148,
5187,
5271,
5272,
5273,
5274,
5290,
5291,
5303,
5304,
5412,
5413,
5416,
5432,
5485,
5507,
5509,
5511,
5512,
5513,
5514,
5515,
5516,
5517,
5518,
5519,
5520,
5584,
5586,
5607,
5654,
5655,
5656,
5658,
5714,
5715,
5719,
5720,
5721,
5722,
5727,
5728,
5729,
5735,
5736,
5739,
5741,
5827,
5828,
5887,
5888,
5889,
5890,
5891,
5892,
5893,
5934,
5935,
5936,
5937,
5938,
5939,
5940,
5965,
5966,
5967,
5968,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
rf = get_model()
job_samples = 50
tree_path_dependent_shap_interact_cache = SimpleCache(
f"tree_path_dependent_shap_interact_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap_interaction"),
)
@tree_path_dependent_shap_interact_cache
def cached_get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=True)
cached_get_interact_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
2,
11,
12,
13,
121,
122,
123,
124,
125,
126,
127,
128,
129,
130,
131,
132,
133,
134,
135,
202,
203,
205,
206,
209,
210,
211,
212,
220,
221,
222,
223,
224,
225,
226,
227,
228,
229,
230,
231,
232,
235,
236,
237,
238,
242,
243,
250,
251,
254,
256,
265,
277,
307,
387,
388,
414,
415,
427,
428,
429,
432,
433,
447,
488,
489,
494,
550,
557,
573,
574,
585,
633,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
rf = get_model()
job_samples = 2000
tree_path_dependent_shap_cache = SimpleCache(
f"tree_path_dependent_shap_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap"),
)
@tree_path_dependent_shap_cache
def cached_get_shap_values(model, X):
return get_shap_values(model, X, interaction=False)
cached_get_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
3,
4,
154,
155,
211,
240,
251,
289,
293,
294,
330,
331,
334,
345,
380,
381,
392,
410,
421,
422,
423,
439,
460,
461,
467,
468,
483,
503,
516,
522,
523,
528,
536,
539,
540,
541,
542,
543,
558,
560,
564,
567,
568,
580,
585,
586,
590,
591,
617,
618,
619,
620,
625,
626,
633,
658,
659,
660,
661,
662,
663,
668,
687,
688,
689,
691,
692,
693,
694,
695,
696,
697,
698,
700,
702,
703,
721,
746,
754,
755,
762,
763,
790,
791,
792,
793,
794,
798,
806,
814,
818,
827,
828,
829,
832,
844,
845,
861,
862,
863,
864,
866,
884,
888,
889,
890,
891,
892,
897,
900,
902,
903,
904,
905,
906,
910,
911,
912,
913,
927,
928,
929,
930,
937,
938,
948,
949,
950,
952,
953,
956,
960,
962,
974,
975,
976,
977,
978,
980,
982,
983,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
results, rf = cross_val_cache.load()
job_samples = 2000
tree_path_dependent_shap_cache = SimpleCache(
f"tree_path_dependent_shap_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap"),
)
@tree_path_dependent_shap_cache
def get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=False)
get_interact_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
1017,
1088,
1089,
1136,
1174,
1202,
1277,
1303,
1364,
1480,
1529,
1589,
1687,
1805,
1845,
1889,
1896,
1931,
1932,
1941,
1966,
1967,
1970,
1984,
2014,
2035,
2043,
2047,
2051,
2061,
2062,
2067,
2069,
2075,
2081,
2094,
2095,
2103,
2122,
2123,
2126,
2127,
2128,
2130,
2131,
2137,
2138,
2152,
2154,
2155,
2156,
2157,
2159,
2160,
2161,
2173,
2174,
2175,
2176,
2179,
2180,
2188,
2189,
2191,
2193,
2194,
2195,
2196,
2198,
2199,
2202,
2203,
2205,
2206,
2207,
2210,
2224,
2225,
2227,
2232,
2233,
2236,
2238,
2248,
2249,
2250,
2251,
2252,
2253,
2254,
2258,
2259,
2261,
2262,
2263,
2264,
2272,
2273,
2274,
2276,
2279,
2280,
2281,
2282,
2283,
2285,
2287,
2288,
2289,
2291,
2292,
2294,
2302,
2308,
2310,
2314,
2315,
2316,
2320,
2321,
2323,
2327,
2328,
2332,
2340,
2341,
2355,
2356,
2361,
2366,
2367,
2368,
2369,
2371,
2372,
2373,
2377,
2381,
2394,
2395,
2397,
2402,
2403,
2407,
2412,
2418,
2425,
2438,
2441,
2442,
2444,
2456,
2473,
2475,
2476,
2477,
2478,
2494,
2507,
2515,
2516,
2517,
2531,
2534,
2565,
2567,
2571,
2572,
2573,
2574,
2575,
2582,
2587,
2588,
2594,
2595,
2611,
2624,
2625,
2626,
2627,
2628,
2629,
2630,
2632,
2633,
2634,
2637,
2638,
2639,
2640,
2641,
2642,
2650,
2651,
2654,
2655,
2671,
2672,
2673,
2674,
2675,
2676,
2677,
2679,
2680,
2682,
2683,
2686,
2687,
2688,
2689,
2690,
2692,
2697,
2707,
2708,
2710,
2711,
2712,
2714,
2715,
2716,
2717,
2718,
2719,
2721,
2722,
2723,
2724,
2725,
2727,
2730,
2736,
2737,
2757,
2758,
2759,
2762,
2763,
2764,
2765,
2766,
2767,
2768,
2769,
2771,
2772,
2773,
2775,
2776,
2777,
2779,
2780,
2781,
2782,
2783,
2784,
2800,
2801,
2802,
2803,
2804,
2805,
2806,
2807,
2808,
2809,
2810,
2811,
2812,
2813,
2815,
2816,
2817,
2818,
2819,
2820,
2821,
2823,
2824,
2825,
2826,
2831,
2832,
2833,
2834,
2835,
2852,
2854,
2855,
2856,
2857,
2858,
2859,
2861,
2862,
2863,
2864,
2865,
2866,
2867,
2868,
2870,
2871,
2872,
2873,
2874,
2876,
2879,
2880,
2881,
2885,
2900,
2910,
2911,
2912,
2913,
2914,
2915,
2918,
2919,
2920,
2921,
2924,
2925,
2930,
2931,
2932,
2933,
2935,
2936,
2937,
2938,
2943,
2945,
2957,
2961,
2962,
2964,
2965,
2966,
2970,
2971,
2972,
2975,
2976,
2978,
2979,
2980,
2981,
2982,
2985,
2986,
2997,
3005,
3014,
3017,
3023,
3024,
3027,
3028,
3043,
3054,
3061,
3062,
3103,
3141,
3873,
3881,
3884,
3886,
3887,
3890,
3891,
3894,
3895,
3896,
3897,
3898,
3899,
3900,
3903,
3909,
3910,
3911,
3912,
3916,
3925,
3926,
3927,
3928,
3929,
3932,
3933,
3934,
3935,
3936,
3938,
3941,
3942,
3943,
3944,
3947,
3948,
3951,
3952,
3953,
3954,
3955,
3956,
3957,
3958,
3959,
3960,
3961,
3962,
3963,
3964,
3965,
3966,
3967,
3968,
3969,
3970,
3971,
3973,
3974,
3975,
3976,
3978,
3979,
3980,
3981,
3982,
3983,
3984,
3985,
3986,
3987,
3988,
3989,
3990,
3991,
3992,
3993,
3994,
3995,
3996,
3997,
3998,
3999,
4000,
4001,
4002,
4003,
4004,
4005,
4006,
4007,
4015,
4016,
4250,
4284,
4285,
4373,
4374,
4418,
4419,
4420,
4421,
4445,
4446,
4493,
4494,
4495,
4496,
4514,
4515,
4537,
4544,
4545,
4546,
4547,
4570,
4571,
4594,
4600,
4601,
4602,
4603,
4613,
4614,
4625,
4626,
4627,
4631,
4632,
4656,
4657,
4675,
4676,
4693,
4694,
4708,
4709,
4726,
4727,
4743,
4744,
4749,
4750,
4771,
4772,
4788,
4789,
4791,
4792,
4793,
4802,
4803,
4804,
4805,
4815,
4816,
4828,
4829,
4830,
4831,
4832,
4862,
4863,
4873,
4874,
4876,
4877,
4878,
4887,
4888,
4889,
4890,
4897,
4904,
4905,
4925,
4927,
4928,
4929,
4935,
4936,
4937,
4941,
4949,
4950,
4961,
4977,
4985,
4986,
4999,
5007,
5008,
5009,
5025,
5026,
5028,
5029,
5048,
5049,
5057,
5058,
5066,
5067,
5078,
5082,
5083,
5084,
5085,
5104,
5105,
5112,
5113,
5128,
5129,
5133,
5134,
5135,
5136,
5137,
5145,
5146,
5153,
5154,
5168,
5172,
5173,
5174,
5175,
5176,
5178,
5187,
5199,
5200,
5214,
5217,
5221,
5222,
5223,
5224,
5225,
5226,
5227,
5228,
5233,
5242,
5243,
5261,
5266,
5268,
5269,
5270,
5271,
5273,
5279,
5286,
5287,
5293,
5294,
5295,
5296,
5297,
5298,
5299,
5300,
5301,
5302,
5311,
5312,
5320,
5321,
5328,
5329,
5331,
5332,
5333,
5334,
5335,
5336,
5337,
5338,
5343,
5344,
5351,
5352,
5363,
5364,
5368,
5369,
5370,
5371,
5372,
5373,
5374,
5375,
5383,
5384,
5393,
5394,
5402,
5405,
5406,
5407,
5408,
5409,
5410,
5411,
5412,
5413,
5419,
5420,
5430,
5431,
5442,
5446,
5447,
5448,
5449,
5450,
5451,
5452,
5453,
5454,
5456,
5457,
5464,
5465,
5476,
5485,
5486,
5487,
5488,
5489,
5490,
5491,
5492,
5493,
5494,
5499,
5507,
5508,
5524,
5525,
5526,
5527,
5528,
5529,
5530,
5531,
5532,
5542,
5543,
5550,
5551,
5565,
5566,
5572,
5573,
5574,
5575,
5576,
5577,
5578,
5579,
5580,
5581,
5591,
5594,
5595,
5608,
5609,
5612,
5613,
5614,
5620,
5621,
5622,
5623,
5626,
5627,
5628,
5629,
5630,
5640,
5641,
5644,
5645,
5656,
5657,
5658,
5659,
5660,
5662,
5663,
5667,
5668,
5669,
5670,
5671,
5672,
5673,
5674,
5675,
5676,
5681,
5685,
5686,
5713,
5714,
5715,
5716,
5719,
5720,
5729,
5730,
5731,
5732,
5733,
5734,
5735,
5736,
5737,
5738,
5749,
5750,
5756,
5757,
5785,
5786,
5787,
5788,
5791,
5792,
5796,
5799,
5800,
5801,
5802,
5803,
5804,
5805,
5806,
5807,
5823,
5824,
5831,
5832,
5864,
5868,
5869,
5883,
5884,
5901,
5902,
5903,
5904,
5907,
5908,
5911,
5912,
5913,
5914,
5915,
5916,
5917,
5918,
5919,
5920,
5923,
5924,
5932,
5933,
5942,
5943,
5944,
5945,
5946,
5948,
5949,
5950,
5977,
5978,
5979,
5980,
5981,
5983,
5984,
5991,
5995,
5996,
5997,
5999,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
rf = get_model()
job_samples = 50
tree_path_dependent_shap_interact_cache = SimpleCache(
f"tree_path_dependent_shap_interact_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap_interaction"),
)
@tree_path_dependent_shap_interact_cache
def cached_get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=True)
cached_get_interact_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
4,
5,
6,
7,
10,
11,
12,
13,
14,
15,
16,
18,
19,
21,
31,
32,
39,
49,
52,
66,
67,
72,
73,
75,
76,
81,
82,
86,
87,
89,
99,
101,
112,
126,
127,
142,
147,
148,
161,
162,
163,
164,
174,
175,
182,
185,
186,
188,
189,
190,
192,
196,
197,
198,
199,
204,
205,
206,
209,
216,
226,
227,
228,
236,
240,
241,
253,
254,
258,
259,
260,
262,
263,
264,
300,
303,
304,
316,
317,
318,
329,
330,
348,
349,
351,
352,
365,
425,
434,
451,
452,
453,
457,
459,
461,
462,
472,
473,
475,
480,
481,
486,
488,
491,
493,
495,
496,
499,
502,
509,
521,
523,
546,
547,
549,
550,
551,
561,
562,
570,
575,
586,
587,
589,
590,
598,
599,
600,
601,
602,
603,
604,
605,
608,
609,
611,
612,
613,
614,
616,
617,
626,
629,
630,
634,
635,
642,
648,
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,
925,
926,
927,
928,
929,
930,
931,
932,
933,
934,
935,
936,
937,
938,
939,
940,
941,
942,
943,
944,
945,
946,
947,
948,
949,
950,
951,
952,
953,
954,
955,
956,
957,
958,
959,
960,
961,
962,
963,
964,
965,
966,
967,
968,
969,
970,
971,
972,
973,
974,
975,
976,
977,
978,
979,
980,
981,
982,
983,
984,
985,
986,
987,
988,
989,
990,
991,
992,
993,
994,
995,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
rf = get_model()
job_samples = 2000
tree_path_dependent_shap_cache = SimpleCache(
f"tree_path_dependent_shap_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap"),
)
@tree_path_dependent_shap_cache
def cached_get_shap_values(model, X):
return get_shap_values(model, X, interaction=False)
cached_get_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])
def func():
# Used to re-compute specific failed jobs, `None` otherwise.
indices = [
32,
71,
277,
278,
279,
280,
281,
282,
283,
284,
339,
340,
341,
342,
343,
344,
379,
481,
483,
498,
500,
515,
516,
517,
518,
519,
520,
521,
522,
523,
524,
564,
565,
566,
589,
903,
904,
905,
906,
907,
908,
914,
915,
994,
995,
1016,
1023,
1024,
1025,
1026,
1085,
1103,
1107,
1123,
1126,
1127,
1128,
1243,
1271,
1272,
1324,
1378,
1385,
1386,
1387,
1388,
1389,
1390,
1391,
1403,
1404,
1416,
1418,
1438,
1440,
1455,
1456,
1457,
1589,
1592,
1626,
1627,
1629,
1675,
1676,
2008,
2009,
2010,
2153,
2160,
2164,
2167,
2169,
2205,
2208,
2248,
2249,
2250,
2277,
2297,
2298,
2299,
2328,
2337,
2342,
2343,
2379,
2381,
2382,
2383,
2604,
2919,
2920,
3036,
3048,
3049,
3050,
3051,
3052,
3059,
3065,
3066,
3067,
3068,
3075,
3076,
3077,
3078,
3079,
3080,
3081,
3082,
3083,
3085,
3091,
3092,
3093,
3094,
3095,
3102,
3103,
3104,
3105,
3106,
3107,
3108,
3109,
3110,
3111,
3112,
3113,
3114,
3115,
3124,
3126,
3170,
3171,
3299,
3301,
3307,
3343,
3716,
3733,
3734,
3735,
3736,
3751,
3753,
3757,
3817,
3818,
3828,
4046,
4047,
4048,
4049,
4050,
4051,
4052,
4053,
4054,
4055,
4056,
4057,
4058,
4059,
4060,
4061,
4062,
4063,
4064,
4065,
4066,
4067,
4074,
4075,
4080,
4081,
4082,
4083,
4084,
4085,
4086,
4087,
4088,
4089,
4090,
4091,
4092,
4093,
4094,
4095,
4096,
4097,
4098,
4099,
4100,
4101,
4102,
4336,
4346,
4347,
4384,
4385,
4386,
4387,
4388,
4389,
4404,
4420,
4422,
4475,
4483,
4508,
4512,
4527,
4528,
4607,
4608,
4609,
4610,
4611,
4612,
4613,
4614,
4615,
4616,
4694,
4695,
4696,
4697,
4729,
4730,
4740,
4761,
4837,
4838,
4880,
4881,
4882,
4991,
4992,
5032,
5061,
5087,
5096,
5186,
5187,
5188,
5189,
5190,
5191,
5192,
5193,
5199,
5407,
5408,
5451,
5452,
5511,
5598,
5599,
5600,
5601,
5602,
5603,
5604,
5605,
5606,
5607,
5608,
5620,
5662,
5667,
5699,
5700,
5757,
5763,
5852,
5853,
5854,
5855,
5856,
5857,
5941,
5991,
]
index = int(os.environ["PBS_ARRAY_INDEX"])
if indices is not None:
index = indices[index]
print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
results, rf = cross_val_cache.load()
job_samples = 50
tree_path_dependent_shap_interact_cache = SimpleCache(
f"tree_path_dependent_shap_interact_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap_interaction"),
)
@tree_path_dependent_shap_interact_cache
def get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=True)
get_interact_shap_values(
rf, X_train[index * job_samples:(index + 1) * job_samples])