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question: ['How many guinea pigs are in the image?'], responses:['2'] |
tensor([8.3588e-01, 7.4640e-03, 1.5496e-01, 1.1118e-03, 6.5076e-05, 1.5461e-04, |
2.3205e-05, 3.3421e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.3588e-01, 7.4640e-03, 1.5496e-01, 1.1118e-03, 6.5076e-05, 1.5461e-04, |
2.3205e-05, 3.3421e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8359, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.1550, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0092, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many balloon animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
[('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']] |
[('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']] |
question: ['How many balloon animals are in the image?'], responses:['3'] |
[('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']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
torch.Size([1, 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: 3396 |
tensor([0.6143, 0.0883, 0.0568, 0.0418, 0.0073, 0.1650, 0.0231, 0.0035], |
device='cuda:1', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([0.6143, 0.0883, 0.0568, 0.0418, 0.0073, 0.1650, 0.0231, 0.0035], |
device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0568, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9432, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many pandas are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
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 |
question: ['How many wolves are in the image?'], responses:['4'] |
[('4', 0.12804651361935848), ('5', 0.12521071898947128), ('3', 0.12515925906184908), ('8', 0.12489091845155219), ('6', 0.1245383468146311), ('1', 0.12441141527606933), ('2', 0.12403713327181662), ('11', 0.12370569451525179)] |
[['4', '5', '3', '8', '6', '1', '2', '11']] |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
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([9.8338e-01, 4.8476e-03, 1.3047e-03, 9.6405e-03, 4.1036e-04, 2.3187e-04, |
1.7000e-04, 1.6959e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.8338e-01, 4.8476e-03, 1.3047e-03, 9.6405e-03, 4.1036e-04, 2.3187e-04, |
1.7000e-04, 1.6959e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
question: ['How many pandas are in the image?'], responses:['2'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9834, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0166, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
[('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']] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
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([6.3620e-01, 2.6580e-02, 2.6263e-02, 4.6193e-03, 3.8648e-04, 3.0420e-01, |
1.5774e-03, 1.7895e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([6.3620e-01, 2.6580e-02, 2.6263e-02, 4.6193e-03, 3.8648e-04, 3.0420e-01, |
1.5774e-03, 1.7895e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9737, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many convertible vehicles are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
question: ['How many convertible vehicles are in the image?'], responses:['1'] |
[('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([3, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
tensor([0.5499, 0.1914, 0.2037, 0.0046, 0.0257, 0.0091, 0.0139, 0.0017], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
4 ************* |
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([0.5499, 0.1914, 0.2037, 0.0046, 0.0257, 0.0091, 0.0139, 0.0017], |
device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0091, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.9909, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
tensor([9.7390e-01, 2.9119e-03, 8.0860e-04, 1.9200e-04, 4.0652e-04, 2.4518e-04, |
2.1516e-02, 1.6629e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.7390e-01, 2.9119e-03, 8.0860e-04, 1.9200e-04, 4.0652e-04, 2.4518e-04, |
2.1516e-02, 1.6629e-05], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.9785, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the dog mostly black?') |
ANSWER1=RESULT(var=ANSWER0) |
torch.Size([7, 3, 448, 448]) |
tensor([9.4046e-01, 3.2177e-02, 3.8434e-03, 2.2114e-02, 8.3116e-04, 2.9606e-04, |
2.5337e-04, 2.3273e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.4046e-01, 3.2177e-02, 3.8434e-03, 2.2114e-02, 8.3116e-04, 2.9606e-04, |
2.5337e-04, 2.3273e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9405, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0595, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
question: ['Is the dog mostly black?'], responses:['no'] |
[('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']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
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