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Registering VQA_lavis step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='Is the dog being held by a human?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=LEFT,question='How many wine bottles are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 5') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
ANSWER0=VQA(image=RIGHT,question='How many stingrays are visible in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
question: ['Is the dog being held by a human?'], 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([5, 3, 448, 448]) knan debug pixel values shape |
question: ['How many dogs are standing in the snow?'], responses:['2'] |
question: ['How many wine bottles are in the image?'], responses:['ε'] |
[('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']] |
question: ['How many stingrays are visible in the image?'], responses:['2'] |
[('geese', 0.12791273653846358), ('cushion', 0.12632164867635856), ('biking', 0.12559214056053666), ('bulldog', 0.12532071672327474), ('striped', 0.12486304389654934), ('goose', 0.12402122964730407), ('vegetable', 0.12318440383239601), ('dodgers', 0.12278408012511692)] |
[['geese', 'cushion', 'biking', 'bulldog', 'striped', 'goose', 'vegetable', 'dodgers']] |
[('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 |
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: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
tensor([1.0000e+00, 9.6395e-09, 3.7384e-11, 1.2513e-07, 2.0528e-10, 8.0716e-10, |
9.6591e-11, 1.2710e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 9.6395e-09, 3.7384e-11, 1.2513e-07, 2.0528e-10, 8.0716e-10, |
9.6591e-11, 1.2710e-08], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(3.7384e-11, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1917e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Does the building have a chimney?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 3, 448, 448]) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
question: ['Does the building have a chimney?'], 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']] |
tensor([9.9998e-01, 1.1861e-08, 1.4730e-09, 2.2828e-05, 1.5166e-10, 8.1977e-10, |
7.7620e-10, 9.1087e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9998e-01, 1.1861e-08, 1.4730e-09, 2.2828e-05, 1.5166e-10, 8.1977e-10, |
7.7620e-10, 9.1087e-10], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(2.2844e-05, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([5.4020e-04, 1.8119e-02, 1.8068e-06, 1.5003e-01, 1.1859e-01, 2.0356e-03, |
7.0737e-01, 3.3181e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
vegetable ************* |
['geese', 'cushion', 'biking', 'bulldog', 'striped', 'goose', 'vegetable', 'dodgers'] tensor([5.4020e-04, 1.8119e-02, 1.8068e-06, 1.5003e-01, 1.1859e-01, 2.0356e-03, |
7.0737e-01, 3.3181e-03], device='cuda:3', grad_fn=<SelectBackward0>) |
ANSWER0=VQA(image=RIGHT,question='How many legs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
tensor([9.9999e-01, 3.4321e-08, 9.5851e-10, 1.1479e-05, 8.9851e-11, 4.2042e-11, |
1.1355e-10, 2.2776e-11], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9999e-01, 3.4321e-08, 9.5851e-10, 1.1479e-05, 8.9851e-11, 4.2042e-11, |
1.1355e-10, 2.2776e-11], device='cuda:0', grad_fn=<SelectBackward0>) |
torch.Size([1, 3, 448, 448]) |
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>)} |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.1479e-05, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many dogs are wearing a collar?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='How many acorns are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many legs 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([1, 3, 448, 448]) knan debug pixel values shape |
tensor([9.9998e-01, 3.1800e-08, 1.9276e-05, 8.3634e-07, 2.3861e-09, 1.4243e-06, |
2.2638e-08, 7.0495e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9998e-01, 3.1800e-08, 1.9276e-05, 8.3634e-07, 2.3861e-09, 1.4243e-06, |
2.2638e-08, 7.0495e-07], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(2.2298e-05, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
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