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FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} > 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Is the dog sitting on green grass?'], 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, 6.6916e-10, 3.0420e-07, 1.1049e-12, 2.7263e-12, 3.9866e-09, |
7.6025e-11, 2.8132e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 6.6916e-10, 3.0420e-07, 1.1049e-12, 2.7263e-12, 3.9866e-09, |
7.6025e-11, 2.8132e-07], device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(6.6916e-10, device='cuda:2', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(5.9605e-07, device='cuda:2', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many pins are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 4') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 3, 448, 448]) |
question: ['How many pins are in the image?'], responses:['7'] |
[('7', 0.12828776251745355), ('8', 0.1258361832781132), ('11', 0.12481772898325143), ('5', 0.124759881092759), ('9', 0.12447036165452931), ('10', 0.1239759375399529), ('6', 0.12393017600998846), ('12', 0.12392196892395223)] |
[['7', '8', '11', '5', '9', '10', '6', '12']] |
question: ['Does the image feature two tear-drop carved white sinks positioned side-by-side?'], responses:['yes'] |
question: ['How many seals are laying on the ground in the image?'], responses:['2'] |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
question: ['How many animals are in the image?'], responses:['5'] |
[('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']] |
[('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']] |
[('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']] |
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 |
torch.Size([13, 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: 3407 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3404 |
tensor([0.3651, 0.0015, 0.0241, 0.5317, 0.0424, 0.0017, 0.0280, 0.0055], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
5 ************* |
['7', '8', '11', '5', '9', '10', '6', '12'] tensor([0.3651, 0.0015, 0.0241, 0.5317, 0.0424, 0.0017, 0.0280, 0.0055], |
device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3405 |
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: 3404 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3405 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3405 |
tensor([1.0000e+00, 2.3937e-09, 8.3107e-11, 5.4871e-09, 1.4801e-10, 8.4422e-11, |
1.9845e-11, 1.3955e-08], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.3937e-09, 8.3107e-11, 5.4871e-09, 1.4801e-10, 8.4422e-11, |
1.9845e-11, 1.3955e-08], device='cuda:0', grad_fn=<SelectBackward0>) |
tensor([8.7862e-01, 1.1891e-01, 2.4616e-03, 1.8366e-07, 4.2127e-06, 1.6916e-08, |
6.4102e-07, 5.3501e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([8.7862e-01, 1.1891e-01, 2.4616e-03, 1.8366e-07, 4.2127e-06, 1.6916e-08, |
6.4102e-07, 5.3501e-10], device='cuda:1', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1., device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(8.3107e-11, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-8.3107e-11, device='cuda:0', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many insects are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.9975, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0025, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
torch.Size([7, 3, 448, 448]) |
tensor([9.9979e-01, 1.7620e-09, 1.0641e-04, 9.8312e-05, 5.5507e-10, 4.6057e-06, |
1.3831e-09, 2.7988e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
5 ************* |
['5', '8', '4', '6', '3', '7', '11', '9'] tensor([9.9979e-01, 1.7620e-09, 1.0641e-04, 9.8312e-05, 5.5507e-10, 4.6057e-06, |
1.3831e-09, 2.7988e-09], device='cuda:3', grad_fn=<SelectBackward0>) |
ANSWER0=VQA(image=RIGHT,question='Is the bird in flight?') |
ANSWER1=RESULT(var=ANSWER0) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(1.1921e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
torch.Size([7, 3, 448, 448]) |
ANSWER0=VQA(image=LEFT,question='How many spotted wild cats are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['How many insects are in the image?'], responses:['1'] |
question: ['Is the bird in flight?'], responses:['no'] |
[('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']] |
question: ['How many spotted wild cats 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([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
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: 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: 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: 1860 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
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