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torch.Size([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Does the laptop on the right image have a black background?'], 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([1, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 5.9641e-09, 8.1646e-07, 2.4952e-11, 2.0033e-10, 1.3960e-08, |
3.8378e-10, 6.3575e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 5.9641e-09, 8.1646e-07, 2.4952e-11, 2.0033e-10, 1.3960e-08, |
3.8378e-10, 6.3575e-07], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(5.9641e-09, device='cuda:3', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(1.5497e-06, device='cuda:3', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many vehicles are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} > 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['Is there a barber pole in the image?'], 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 |
question: ['Is there a silver lid resting against a container in the image?'], responses:['yes'] |
question: ['Is there a ladder leaning against the bookcase in the image?'], responses:['no'] |
question: ['How many vehicles are in the image?'], responses:['200'] |
[('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']] |
[('200', 0.1321606270186138), ('400', 0.12559688033658498), ('150', 0.12485068989614088), ('500', 0.12470360679460982), ('300', 0.12446878919489603), ('600', 0.12292388257579578), ('700', 0.12273847440460704), ('1000', 0.12255704977875165)] |
[['200', '400', '150', '500', '300', '600', '700', '1000']] |
torch.Size([7, 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: 3401 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3404 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
tensor([1.0000e+00, 1.6052e-09, 8.9404e-07, 7.5825e-10, 1.1460e-08, 1.7469e-07, |
1.0754e-08, 3.4481e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.6052e-09, 8.9404e-07, 7.5825e-10, 1.1460e-08, 1.7469e-07, |
1.0754e-08, 3.4481e-07], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.6052e-09, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.4305e-06, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3402 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
tensor([8.4984e-01, 1.9279e-02, 7.1985e-02, 3.5819e-03, 4.3563e-02, 5.1476e-04, |
6.3051e-04, 1.0608e-02], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
200 ************* |
['200', '400', '150', '500', '300', '600', '700', '1000'] tensor([8.4984e-01, 1.9279e-02, 7.1985e-02, 3.5819e-03, 4.3563e-02, 5.1476e-04, |
6.3051e-04, 1.0608e-02], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
question: ['How many dogs 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']] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3402 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3402 |
tensor([1.0000e+00, 2.6910e-09, 1.1033e-09, 1.8116e-09, 1.8349e-12, 7.2049e-12, |
1.4830e-11, 9.9786e-10], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.6910e-09, 1.1033e-09, 1.8116e-09, 1.8349e-12, 7.2049e-12, |
1.4830e-11, 9.9786e-10], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(1.1033e-09, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-1.1033e-09, device='cuda:0', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Are there stairs in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
tensor([1.0000e+00, 2.9067e-09, 4.0103e-07, 2.4000e-10, 1.9825e-09, 6.9864e-08, |
7.3251e-09, 3.2736e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 2.9067e-09, 4.0103e-07, 2.4000e-10, 1.9825e-09, 6.9864e-08, |
7.3251e-09, 3.2736e-07], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.9067e-09, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(7.1526e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many chow dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
tensor([1.0000e+00, 2.8147e-07, 1.5961e-08, 7.7388e-10, 2.4841e-11, 1.3982e-06, |
5.1060e-11, 6.2896e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([1.0000e+00, 2.8147e-07, 1.5961e-08, 7.7388e-10, 2.4841e-11, 1.3982e-06, |
5.1060e-11, 6.2896e-10], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.5961e-08, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
question: ['Are there stairs in the image?'], 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']] |
question: ['How many chow dogs 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([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 |
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 |
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