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question: ['Is clothing hanging in the wardrobe?'], responses:['no'] |
question: ['Is the mashed potato shaped like a bowl of gravy?'], responses:['no'] |
question: ['How many animals are in the image?'], responses:['2'] |
question: ['How many puppies are in the image?'], responses:['1'] |
[('no', 0.1313955057270409), ('yes', 0.12592208734904367), ('no smoking', 0.12472972590078177), ('gone', 0.12376514658020793), ('man', 0.12367833016285167), ('meow', 0.1235796378467502), ('kia', 0.12347643720898455), ('no clock', 0.12345312922433942)] |
[['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock']] |
[('no', 0.1313955057270409), ('yes', 0.12592208734904367), ('no smoking', 0.12472972590078177), ('gone', 0.12376514658020793), ('man', 0.12367833016285167), ('meow', 0.1235796378467502), ('kia', 0.12347643720898455), ('no clock', 0.12345312922433942)] |
[['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock']] |
[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)] |
[['2', '3', '4', '1', '5', '8', '7', '29']] |
[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)] |
[['1', '3', '4', '8', '6', '12', '2', '47']] |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
tensor([1.0000e+00, 3.3911e-10, 3.6495e-07, 8.0716e-10, 2.8828e-10, 8.2482e-08, |
1.6033e-08, 1.3499e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 3.3911e-10, 3.6495e-07, 8.0716e-10, 2.8828e-10, 8.2482e-08, |
1.6033e-08, 1.3499e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 1.2099e-06, 1.0369e-07, 2.7401e-12, 3.8709e-12, 1.1289e-09, |
3.8505e-10, 3.9040e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.2099e-06, 1.0369e-07, 2.7401e-12, 3.8709e-12, 1.1289e-09, |
3.8505e-10, 3.9040e-07], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 7.0423e-08, 9.6256e-08, 7.5394e-09, 5.2935e-10, 6.1051e-09, |
1.1063e-09, 8.4548e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 7.0423e-08, 9.6256e-08, 7.5394e-09, 5.2935e-10, 6.1051e-09, |
1.1063e-09, 8.4548e-10], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(3.3911e-10, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.8280e-07, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many Samoyed puppies are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.2099e-06, device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(4.7684e-07, device='cuda:1', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Can cliffs be seen behind the castle?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
tensor([1.0000e+00, 1.0947e-09, 2.4129e-10, 8.9339e-10, 6.6392e-10, 1.3432e-08, |
2.0817e-08, 6.3185e-11], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 1.0947e-09, 2.4129e-10, 8.9339e-10, 6.6392e-10, 1.3432e-08, |
2.0817e-08, 6.3185e-11], device='cuda:3', grad_fn=<SelectBackward0>) |
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.5294e-08, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
torch.Size([7, 3, 448, 448]) |
ANSWER0=VQA(image=RIGHT,question='How many pencil cases are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many pencil cases are in the image?'], responses:['11'] |
[('11', 0.12740768001087358), ('10', 0.12548679249075975), ('12', 0.12538137681693887), ('9', 0.12485855662563465), ('8', 0.12469919178932766), ('13', 0.12431757055023795), ('7', 0.12396146028399917), ('14', 0.1238873714322284)] |
[['11', '10', '12', '9', '8', '13', '7', '14']] |
question: ['How many Samoyed puppies are in the image?'], responses:['2'] |
question: ['Can cliffs be seen behind the castle?'], responses:['yes'] |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)] |
[['2', '3', '4', '1', '5', '8', '7', '29']] |
[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)] |
[['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 |
question: ['How many dogs are in the image?'], responses:['3'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
[('3', 0.12809209985493852), ('4', 0.12520382509374006), ('1', 0.1251059160028928), ('5', 0.12483070991268265), ('8', 0.12458076282181878), ('2', 0.12413212281858195), ('6', 0.1241125313968017), ('12', 0.12394203209854344)] |
[['3', '4', '1', '5', '8', '2', '6', '12']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
tensor([9.8015e-01, 1.3004e-03, 1.2338e-02, 1.3004e-03, 5.3145e-06, 4.0056e-03, |
4.7841e-04, 4.2219e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
11 ************* |
['11', '10', '12', '9', '8', '13', '7', '14'] tensor([9.8015e-01, 1.3004e-03, 1.2338e-02, 1.3004e-03, 5.3145e-06, 4.0056e-03, |
4.7841e-04, 4.2219e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-2.3842e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
tensor([1.0000e+00, 5.5709e-08, 6.2994e-09, 1.6212e-08, 3.4715e-10, 8.2630e-10, |
8.4258e-10, 7.1118e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 5.5709e-08, 6.2994e-09, 1.6212e-08, 3.4715e-10, 8.2630e-10, |
8.4258e-10, 7.1118e-10], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(5.5709e-08, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
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