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ANSWER0=VQA(image=RIGHT,question='Does the sea creature in the photo have white tentacles with pink tips?') |
ANSWER1=RESULT(var=ANSWER0) |
torch.Size([7, 3, 448, 448]) |
torch.Size([3, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Does a bird fly right above the water in the image?'], 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([1, 3, 448, 448]) knan debug pixel values shape |
question: ['Does the sea creature in the photo have white tentacles with pink tips?'], 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([3, 3, 448, 448]) knan debug pixel values shape |
tensor([7.2324e-01, 2.2815e-02, 2.4994e-01, 2.3530e-03, 1.0695e-04, 6.0694e-04, |
8.7571e-05, 8.4673e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([7.2324e-01, 2.2815e-02, 2.4994e-01, 2.3530e-03, 1.0695e-04, 6.0694e-04, |
8.7571e-05, 8.4673e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7232, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.2499, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0268, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['Is there a stack of three books on the front-most corner of the shelf under the couch?'], responses:['yes'] |
torch.Size([7, 3, 448, 448]) |
[('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 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 |
tensor([8.3087e-01, 2.1437e-02, 1.4438e-01, 1.6377e-03, 7.9750e-05, 3.3563e-04, |
4.3033e-05, 1.2149e-03], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.3087e-01, 2.1437e-02, 1.4438e-01, 1.6377e-03, 7.9750e-05, 3.3563e-04, |
4.3033e-05, 1.2149e-03], device='cuda:2', grad_fn=<SelectBackward0>) |
question: ['Does the image on the left have a man'], responses:['No'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8309, device='cuda:2', grad_fn=<UnbindBackward0>), False: tensor(0.1444, device='cuda:2', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0247, device='cuda:2', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Are there sea mammals in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 |
[('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([13, 3, 448, 448]) |
question: ['How many animals 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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 |
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: 7, images per sample: 7.0, dynamic token length: 1872 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 |
tensor([6.4920e-01, 2.2728e-02, 3.2253e-01, 1.8493e-03, 2.0513e-04, 8.0482e-04, |
1.2651e-04, 2.5600e-03], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.4920e-01, 2.2728e-02, 3.2253e-01, 1.8493e-03, 2.0513e-04, 8.0482e-04, |
1.2651e-04, 2.5600e-03], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6492, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.3225, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many laptops are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['Are there sea mammals in the image?'], responses:['yes'] |
torch.Size([3, 3, 448, 448]) |
[('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']] |
question: ['How many laptops are in the image?'], responses:['3'] |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
[('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([3, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
tensor([9.6103e-01, 6.4750e-03, 2.5357e-03, 8.2273e-04, 1.1251e-03, 6.9996e-04, |
2.7262e-02, 4.4730e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.6103e-01, 6.4750e-03, 2.5357e-03, 8.2273e-04, 1.1251e-03, 6.9996e-04, |
2.7262e-02, 4.4730e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9610, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0390, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.7881e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
tensor([0.7275, 0.1264, 0.0282, 0.0177, 0.0015, 0.0926, 0.0046, 0.0014], |
device='cuda:0', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([0.7275, 0.1264, 0.0282, 0.0177, 0.0015, 0.0926, 0.0046, 0.0014], |
device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7275, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.2725, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)} |
tensor([0.5927, 0.3948, 0.0007, 0.0008, 0.0074, 0.0016, 0.0007, 0.0012], |
device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([0.5927, 0.3948, 0.0007, 0.0008, 0.0074, 0.0016, 0.0007, 0.0012], |
device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.3948, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.5927, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0125, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is there a body of water in the image?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([7, 3, 448, 448]) |
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