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Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='Is there a child inside a long boat made out of joined cardboard boxes?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 4') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many 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([9.4201e-01, 2.6721e-02, 5.9626e-03, 2.2153e-02, 1.6555e-03, 8.5703e-04, |
6.0858e-04, 3.3824e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.4201e-01, 2.6721e-02, 5.9626e-03, 2.2153e-02, 1.6555e-03, 8.5703e-04, |
6.0858e-04, 3.3824e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0060, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9940, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Are straws visible in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
question: ['How many pencil cases are in the image?'], responses:['1'] |
question: ['Is there a child inside a long boat made out of joined cardboard boxes?'], responses:['yes'] |
question: ['How many monkeys 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']] |
[('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']] |
[('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: ['Are straws visible 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 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
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: 3403 |
tensor([6.4204e-01, 1.1378e-02, 3.4366e-01, 9.2941e-04, 7.4752e-05, 2.2406e-04, |
7.4282e-05, 1.6196e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.4204e-01, 1.1378e-02, 3.4366e-01, 9.2941e-04, 7.4752e-05, 2.2406e-04, |
7.4282e-05, 1.6196e-03], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6420, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.3437, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0143, device='cuda:1', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3406 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
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: 3403 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
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 |
tensor([8.2150e-01, 2.3108e-02, 1.5196e-01, 1.6194e-03, 9.5159e-05, 3.1608e-04, |
4.8281e-05, 1.3550e-03], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.2150e-01, 2.3108e-02, 1.5196e-01, 1.6194e-03, 9.5159e-05, 3.1608e-04, |
4.8281e-05, 1.3550e-03], device='cuda:0', grad_fn=<SelectBackward0>) |
tensor([8.5612e-01, 2.4286e-02, 8.6592e-03, 2.7237e-03, 3.9644e-03, 1.8658e-03, |
1.0225e-01, 1.3269e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([8.5612e-01, 2.4286e-02, 8.6592e-03, 2.7237e-03, 3.9644e-03, 1.8658e-03, |
1.0225e-01, 1.3269e-04], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8215, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.1520, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)} |
tensor([7.8065e-01, 5.3232e-02, 1.9533e-02, 5.0635e-03, 9.2279e-03, 4.2646e-03, |
1.2765e-01, 3.6969e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([7.8065e-01, 5.3232e-02, 1.9533e-02, 5.0635e-03, 9.2279e-03, 4.2646e-03, |
1.2765e-01, 3.6969e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.1439, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.8561, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many fish are in the picture?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7807, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.2193, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many birds are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([3, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many birds 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([3, 3, 448, 448]) knan debug pixel values shape |
question: ['How many fish are in the picture?'], 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([7, 3, 448, 448]) knan debug pixel values shape |
tensor([9.8061e-01, 3.8840e-03, 1.5691e-03, 7.1698e-04, 9.2156e-04, 6.4424e-04, |
1.1596e-02, 5.5164e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.8061e-01, 3.8840e-03, 1.5691e-03, 7.1698e-04, 9.2156e-04, 6.4424e-04, |
1.1596e-02, 5.5164e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9806, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0194, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
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