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[['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: 1860 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
tensor([1.0000e+00, 2.4862e-09, 1.3277e-07, 3.6229e-12, 8.8065e-12, 1.1078e-09, |
1.7195e-10, 1.7473e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 2.4862e-09, 1.3277e-07, 3.6229e-12, 8.8065e-12, 1.1078e-09, |
1.7195e-10, 1.7473e-07], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.4862e-09, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.3842e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
question: ['What part of the dog can be seen in the image?'], responses:['face'] |
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('face', 0.1269299868205098), ('bowl', 0.12492903238012228), ('doll', 0.12476595093051729), ('circle', 0.12474574009924336), ('eaten', 0.12468100267482014), ('oven', 0.1246598522858018), ('blending', 0.12465952693354158), ('dome', 0.12462890787544378)] |
[['face', 'bowl', 'doll', 'circle', 'eaten', 'oven', 'blending', 'dome']] |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
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([1.0000e+00, 3.3597e-07, 2.8841e-09, 1.3574e-07, 9.2541e-10, 2.2767e-10, |
1.2502e-09, 3.5114e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 3.3597e-07, 2.8841e-09, 1.3574e-07, 9.2541e-10, 2.2767e-10, |
1.2502e-09, 3.5114e-10], device='cuda:2', grad_fn=<SelectBackward0>) |
question: ['How many dogs are in the image?'], responses:['2'] |
tensor([1.0000e+00, 3.6563e-08, 3.5262e-10, 2.3033e-07, 8.9085e-10, 1.5713e-08, |
6.8269e-10, 2.3274e-08], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 3.6563e-08, 3.5262e-10, 2.3033e-07, 8.9085e-10, 1.5713e-08, |
6.8269e-10, 2.3274e-08], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.3574e-07, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many chimpanzees are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(3.5262e-10, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(3.5728e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many adult humans are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 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']] |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
question: ['How many chimpanzees 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([7, 3, 448, 448]) knan debug pixel values shape |
question: ['How many adult humans 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: 3397 |
tensor([9.8393e-01, 2.1099e-03, 2.6312e-03, 3.1658e-05, 1.2330e-03, 2.9293e-06, |
1.0568e-03, 9.0026e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
face ************* |
['face', 'bowl', 'doll', 'circle', 'eaten', 'oven', 'blending', 'dome'] tensor([9.8393e-01, 2.1099e-03, 2.6312e-03, 3.1658e-05, 1.2330e-03, 2.9293e-06, |
1.0568e-03, 9.0026e-03], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many binders are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
torch.Size([5, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
question: ['How many binders 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']] |
tensor([3.5393e-01, 6.4607e-01, 1.0870e-07, 1.2504e-09, 3.1693e-06, 6.3472e-09, |
2.3333e-10, 1.0730e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
5 ************* |
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([3.5393e-01, 6.4607e-01, 1.0870e-07, 1.2504e-09, 3.1693e-06, 6.3472e-09, |
2.3333e-10, 1.0730e-08], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.3333e-10, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
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: 3397 |
tensor([1.0000e+00, 1.5870e-07, 4.9937e-08, 4.0757e-08, 5.2114e-10, 2.5853e-09, |
1.3974e-09, 3.9031e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 1.5870e-07, 4.9937e-08, 4.0757e-08, 5.2114e-10, 2.5853e-09, |
1.3974e-09, 3.9031e-10], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(2.5429e-07, 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: 3397 |
tensor([9.9995e-01, 1.0571e-07, 4.5726e-09, 5.2519e-10, 6.6913e-10, 1.5214e-08, |
4.8325e-05, 8.4174e-11], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.9995e-01, 1.0571e-07, 4.5726e-09, 5.2519e-10, 6.6913e-10, 1.5214e-08, |
4.8325e-05, 8.4174e-11], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(4.8325e-05, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, 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: 3397 |
tensor([1.0000e+00, 2.2856e-10, 1.2256e-11, 7.8680e-11, 3.2286e-11, 3.5605e-09, |
6.6156e-08, 1.4024e-10], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
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