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question: ['Is there an angled row of lotion products in the image?'], responses:['no'] |
question: ['How many orange spoons are in the image?'], responses:['1'] |
[('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']] |
[('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([5, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 |
tensor([1.0000e+00, 1.5535e-06, 3.4862e-08, 1.7393e-08, 3.9691e-09, 1.4389e-09, |
6.1049e-09, 1.0772e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 1.5535e-06, 3.4862e-08, 1.7393e-08, 3.9691e-09, 1.4389e-09, |
6.1049e-09, 1.0772e-09], device='cuda:2', grad_fn=<SelectBackward0>) |
question: ['How many parrots are in the image?'], responses:['five'] |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.7393e-08, 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>)} |
ANSWER0=VQA(image=LEFT,question='How many primates are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('7 eleven', 0.1264466744091217), ('babies', 0.124977990347662), ('sunrise', 0.12490143984830117), ('eating', 0.1247676656843781), ('feet', 0.12475702323703439), ('candle', 0.12473210928138137), ('light', 0.12472650705175181), ('floating', 0.12469059014036947)] |
[['7 eleven', 'babies', 'sunrise', 'eating', 'feet', 'candle', 'light', 'floating']] |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 |
tensor([9.9998e-01, 1.8925e-05, 5.8882e-07, 7.3912e-11, 2.6623e-10, 4.1030e-09, |
3.4200e-09, 1.5996e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.9998e-01, 1.8925e-05, 5.8882e-07, 7.3912e-11, 2.6623e-10, 4.1030e-09, |
3.4200e-09, 1.5996e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 6.8905e-10, 1.3809e-10, 3.2602e-10, 4.5612e-10, 2.3567e-08, |
3.5968e-08, 8.8457e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 6.8905e-10, 1.3809e-10, 3.2602e-10, 4.5612e-10, 2.3567e-08, |
3.5968e-08, 8.8457e-10], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many women are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(7.1526e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many balloons are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
question: ['How many primates are in the image?'], responses:['2'] |
[('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([7, 3, 448, 448]) knan debug pixel values shape |
question: ['How many balloons 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 |
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 |
question: ['How many women are in the image?'], responses:['five'] |
[('7 eleven', 0.1264466744091217), ('babies', 0.124977990347662), ('sunrise', 0.12490143984830117), ('eating', 0.1247676656843781), ('feet', 0.12475702323703439), ('candle', 0.12473210928138137), ('light', 0.12472650705175181), ('floating', 0.12469059014036947)] |
[['7 eleven', 'babies', 'sunrise', 'eating', 'feet', 'candle', 'light', 'floating']] |
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 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
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, 1.5870e-07, 3.3587e-09, 3.6899e-07, 3.3386e-10, 3.4702e-10, |
1.5895e-09, 2.4149e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 1.5870e-07, 3.3587e-09, 3.6899e-07, 3.3386e-10, 3.4702e-10, |
1.5895e-09, 2.4149e-10], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(3.6899e-07, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
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([3.3530e-04, 1.9548e-08, 1.4902e-07, 1.2969e-08, 1.5429e-09, 9.9966e-01, |
1.5341e-08, 3.4371e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([3.3530e-04, 1.9548e-08, 1.4902e-07, 1.2969e-08, 1.5429e-09, 9.9966e-01, |
1.5341e-08, 3.4371e-09], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9997, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
tensor([8.3383e-09, 5.7687e-01, 5.2195e-02, 3.6748e-04, 3.6999e-01, 5.8613e-05, |
3.5742e-04, 1.5727e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
babies ************* |
['7 eleven', 'babies', 'sunrise', 'eating', 'feet', 'candle', 'light', 'floating'] tensor([8.3383e-09, 5.7687e-01, 5.2195e-02, 3.6748e-04, 3.6999e-01, 5.8613e-05, |
3.5742e-04, 1.5727e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many chow dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
question: ['How many chow dogs are in the image?'], responses:['2'] |
[('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([3, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 4.1808e-07, 3.7691e-08, 1.8588e-08, 1.4502e-09, 2.4470e-09, |
2.6573e-09, 2.7238e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 4.1808e-07, 3.7691e-08, 1.8588e-08, 1.4502e-09, 2.4470e-09, |
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