feat: modernize PSO and add convergence research

Migrate the package and examples to the tensor-native PyTorch implementation, add benchmark evidence, and add the guarded post-training convergence protocol with TensorBoard progress monitoring and hash-verified recovery.

Constraint: Preserve one-shot official-test sealing and auditable research artifacts

Rejected: Commit local .omc runs and downloaded datasets | multi-gigabyte runtime state is machine-local

Confidence: high

Scope-risk: broad

Not-tested: Production CUDA run on pieroot-server
This commit is contained in:
2026-09-07 22:03:25 +09:00
parent 9745bb7ad4
commit 813433000a
120 changed files with 198148 additions and 4745 deletions
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seed,epoch,train_loss,train_acc,train_mse,test_loss,test_acc,test_mse,fit_time_sec
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73,20,1.703110694885254,0.4322333335876465,0.07236693799495697,1.662993311882019,0.4422999918460846,0.07139508426189423,33.0256
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74,20,1.696816325187683,0.4334833323955536,0.07303200662136078,1.685478925704956,0.4397999942302704,0.07274489104747772,32.3565
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1 seed epoch train_loss train_acc train_mse test_loss test_acc test_mse fit_time_sec
2 71 20 1.6637481451034546 0.4778333306312561 0.06879015266895294 1.6244964599609375 0.4961000084877014 0.0671548843383789 33.649
3 71 40 1.165610432624817 0.6545166373252869 0.04875154793262482 1.0854827165603638 0.6718000173568726 0.046549420803785324 33.649
4 71 60 0.905483067035675 0.7269166707992554 0.0389271154999733 0.8291375041007996 0.7445999979972839 0.036550913006067276 33.649
5 71 80 0.7415720224380493 0.7783499956130981 0.03182263299822807 0.6753337979316711 0.7944999933242798 0.029618915170431137 33.649
6 71 100 0.6563442945480347 0.8064000010490417 0.02799912355840206 0.5993074178695679 0.8216999769210815 0.025761328637599945 33.649
7 71 120 0.588559091091156 0.8279500007629395 0.025105126202106476 0.5335480570793152 0.8414999842643738 0.022965701296925545 33.649
8 71 140 0.5534469485282898 0.8387500047683716 0.023768901824951172 0.5105180144309998 0.8489999771118164 0.022098202258348465 33.649
9 71 160 0.5169084668159485 0.8464000225067139 0.022431854158639908 0.4750884771347046 0.8555999994277954 0.02082662656903267 33.649
10 71 180 0.48863890767097473 0.8547000288963318 0.021347153931856155 0.4477296769618988 0.8686000108718872 0.01953563280403614 33.649
11 71 200 0.4686008393764496 0.8610333204269409 0.020526422187685966 0.43183833360671997 0.8719000220298767 0.018971838057041168 33.649
12 71 220 0.45222264528274536 0.8653833270072937 0.0198610108345747 0.4211212396621704 0.8756999969482422 0.01851881667971611 33.649
13 71 240 0.438436359167099 0.8698999881744385 0.019294776022434235 0.41157108545303345 0.878000020980835 0.018099937587976456 33.649
14 72 20 1.7392971515655518 0.4580833315849304 0.07111531496047974 1.7067090272903442 0.4602999985218048 0.07063549011945724 33.7062
15 72 40 1.2618558406829834 0.6182666420936584 0.05362313985824585 1.2296088933944702 0.6273000240325928 0.05239206552505493 33.7062
16 72 60 0.9506728053092957 0.7125833630561829 0.04073568433523178 0.90444415807724 0.725600004196167 0.03892349451780319 33.7062
17 72 80 0.7690414786338806 0.7677000164985657 0.0332583524286747 0.7225316762924194 0.7825000286102295 0.03151436522603035 33.7062
18 72 100 0.6607407331466675 0.7977833151817322 0.029053399339318275 0.6213417053222656 0.8091999888420105 0.02738099917769432 33.7062
19 72 120 0.5884125232696533 0.8225333094596863 0.02557925134897232 0.5514547824859619 0.8324999809265137 0.024056605994701385 33.7062
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21 72 160 0.5122449398040771 0.8464499711990356 0.022468935698270798 0.4830068349838257 0.8574000000953674 0.021029997617006302 33.7062
22 72 180 0.4828203022480011 0.8543833494186401 0.021225325763225555 0.45465460419654846 0.8646000027656555 0.01990104280412197 33.7062
23 72 200 0.46293872594833374 0.8621000051498413 0.020341966301202774 0.4369881749153137 0.8700000047683716 0.019186409190297127 33.7062
24 72 220 0.4459497630596161 0.8664166927337646 0.0197211392223835 0.41942450404167175 0.8730000257492065 0.0184775423258543 33.7062
25 72 240 0.4350419342517853 0.871566653251648 0.01916772872209549 0.41060513257980347 0.875 0.018150048330426216 33.7062
26 73 20 1.703110694885254 0.4322333335876465 0.07236693799495697 1.662993311882019 0.4422999918460846 0.07139508426189423 33.0256
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47 74 200 0.4600929617881775 0.8631166815757751 0.020222675055265427 0.43229734897613525 0.8694999814033508 0.01901264674961567 32.3565
48 74 220 0.44254931807518005 0.8678500056266785 0.019469955936074257 0.417081743478775 0.8754000067710876 0.018321329727768898 32.3565
49 74 240 0.43052077293395996 0.8725666403770447 0.018974633887410164 0.40485620498657227 0.8798999786376953 0.01778729446232319 32.3565
50 75 20 1.7082723379135132 0.42640000581741333 0.07211916148662567 1.6778934001922607 0.43220001459121704 0.07167963683605194 33.1184
51 75 40 1.2474853992462158 0.628333330154419 0.05103134736418724 1.1880637407302856 0.6402000188827515 0.04922466725111008 33.1184
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