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question: ['How many dogs are in the image?'], responses:['5'] |
[('5', 0.12793059870235002), ('8', 0.12539646467821697), ('4', 0.12509737486793587), ('6', 0.12470234839853608), ('3', 0.12467331676337925), ('7', 0.12441254825093238), ('11', 0.12401867309944531), ('9', 0.12376867523920407)] |
[['5', '8', '4', '6', '3', '7', '11', '9']] |
question: ['Is the panda on the left image with its mouth open?'], responses:['yes'] |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
question: ['Is the dog in the image on the right standing up on all four?'], responses:['no'] |
[('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']] |
[('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 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
tensor([9.4743e-01, 4.9446e-02, 3.0051e-05, 3.0950e-03, 1.1493e-08, 1.3225e-10, |
1.2816e-10, 3.4549e-08], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.4743e-01, 4.9446e-02, 3.0051e-05, 3.0950e-03, 1.1493e-08, 1.3225e-10, |
1.2816e-10, 3.4549e-08], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9969, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0031, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many seals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
tensor([9.9471e-01, 3.3423e-07, 1.3036e-04, 2.9797e-03, 9.8573e-10, 2.1802e-03, |
1.4345e-07, 3.1240e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
5 ************* |
['5', '8', '4', '6', '3', '7', '11', '9'] tensor([9.9471e-01, 3.3423e-07, 1.3036e-04, 2.9797e-03, 9.8573e-10, 2.1802e-03, |
1.4345e-07, 3.1240e-07], device='cuda:3', grad_fn=<SelectBackward0>) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many penguins are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 |
tensor([1.0000e+00, 1.6558e-08, 1.0754e-10, 1.8324e-08, 8.1107e-11, 1.0364e-09, |
3.9937e-11, 1.7167e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.6558e-08, 1.0754e-10, 1.8324e-08, 8.1107e-11, 1.0364e-09, |
3.9937e-11, 1.7167e-08], device='cuda:2', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 7.1941e-09, 1.2681e-07, 8.2929e-12, 2.9531e-12, 8.3899e-10, |
1.4551e-10, 1.0528e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 7.1941e-09, 1.2681e-07, 8.2929e-12, 2.9531e-12, 8.3899e-10, |
1.4551e-10, 1.0528e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: question: ['How many seals are in the image?'], responses:['2'] |
{True: tensor(1., device='cuda:2', grad_fn=<UnbindBackward0>), False: tensor(1.0754e-10, device='cuda:2', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-1.0754e-10, device='cuda:2', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many elephants are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(7.1941e-09, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.3842e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is someone holding the dog?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('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']] |
torch.Size([13, 3, 448, 448]) |
question: ['How many penguins are in the image?'], responses:['1'] |
question: ['How many elephants are in the image?'], responses:['2'] |
[('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']] |
[('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']] |
torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 3.6899e-07, 1.7806e-08, 3.7694e-08, 4.1906e-10, 6.6131e-10, |
1.0404e-09, 1.5006e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 3.6899e-07, 1.7806e-08, 3.7694e-08, 4.1906e-10, 6.6131e-10, |
1.0404e-09, 1.5006e-10], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(4.2676e-07, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
question: ['Is someone holding the dog?'], responses:['yes'] |
[('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([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3394 |
tensor([1.0000e+00, 2.7249e-10, 4.4136e-11, 1.6017e-10, 1.1089e-10, 1.3633e-08, |
2.8394e-09, 2.8917e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 2.7249e-10, 4.4136e-11, 1.6017e-10, 1.1089e-10, 1.3633e-08, |
2.8394e-09, 2.8917e-10], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.8394e-09, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3394 |
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: 3394 |
tensor([1.0000e+00, 4.8883e-07, 1.6468e-08, 5.2633e-09, 8.2308e-10, 6.4162e-10, |
1.8046e-09, 4.3196e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 4.8883e-07, 1.6468e-08, 5.2633e-09, 8.2308e-10, 6.4162e-10, |
1.8046e-09, 4.3196e-10], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(5.1426e-07, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3394 |
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