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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 |
tensor([0.1736, 0.1705, 0.1087, 0.1063, 0.1050, 0.1345, 0.0881, 0.1133], |
device='cuda:0', grad_fn=<SoftmaxBackward0>) |
8 ************* |
['8', '9', '12', '7', '5', '6', '11', '10'] tensor([0.1736, 0.1705, 0.1087, 0.1063, 0.1050, 0.1345, 0.0881, 0.1133], |
device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), False: tensor(1., device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is there a body of water in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['How many mountain goats are in the image?'], responses:['2'] |
question: ['Is the vehicle driving in front of a house?'], responses:['yes'] |
question: ['Are all of the sails on the boat red?'], responses:['yes'] |
[('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']] |
[('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']] |
[('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([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 |
question: ['Is there a body of water 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([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
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: 1862 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
tensor([6.4647e-01, 2.4702e-02, 3.2506e-01, 1.5868e-03, 1.4298e-04, 6.4658e-04, |
1.4713e-04, 1.2428e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.4647e-01, 2.4702e-02, 3.2506e-01, 1.5868e-03, 1.4298e-04, 6.4658e-04, |
1.4713e-04, 1.2428e-03], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([6.0324e-01, 2.7181e-02, 3.6588e-01, 1.4306e-03, 2.2020e-04, 8.3527e-04, |
1.1959e-04, 1.0871e-03], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.0324e-01, 2.7181e-02, 3.6588e-01, 1.4306e-03, 2.2020e-04, 8.3527e-04, |
1.1959e-04, 1.0871e-03], device='cuda:2', grad_fn=<SelectBackward0>) |
tensor([6.6152e-01, 9.5173e-02, 3.0939e-02, 1.8949e-01, 1.3728e-02, 4.3187e-03, |
4.5691e-03, 2.5537e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([6.6152e-01, 9.5173e-02, 3.0939e-02, 1.8949e-01, 1.3728e-02, 4.3187e-03, |
4.5691e-03, 2.5537e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6032, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.3659, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0309, device='cuda:2', grad_fn=<DivBackward0>)} |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6465, device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(0.3251, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0285, device='cuda:1', grad_fn=<SubBackward0>)} |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6615, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.3385, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Is baby gorilla visible in the image?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
torch.Size([13, 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 |
question: ['How many dogs 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']] |
torch.Size([3, 3, 448, 448]) knan debug pixel values shape |
tensor([8.9386e-01, 1.5861e-02, 8.8504e-02, 1.1394e-03, 6.9995e-05, 2.2583e-04, |
1.8781e-05, 3.2524e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.9386e-01, 1.5861e-02, 8.8504e-02, 1.1394e-03, 6.9995e-05, 2.2583e-04, |
1.8781e-05, 3.2524e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8939, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0885, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)} |
question: ['Is baby gorilla 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([7, 3, 448, 448]) knan debug pixel values shape |
tensor([0.1956, 0.1495, 0.0651, 0.1430, 0.1294, 0.0924, 0.1836, 0.0414], |
device='cuda:1', grad_fn=<SoftmaxBackward0>) |
7 ************* |
['7', '8', '11', '5', '9', '10', '6', '12'] tensor([0.1956, 0.1495, 0.0651, 0.1430, 0.1294, 0.0924, 0.1836, 0.0414], |
device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
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([13, 3, 448, 448]) knan debug pixel values shape |
tensor([8.4857e-01, 1.9254e-02, 1.3013e-01, 1.1645e-03, 6.1566e-05, 2.6597e-04, |
7.4622e-05, 4.7901e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.4857e-01, 1.9254e-02, 1.3013e-01, 1.1645e-03, 6.1566e-05, 2.6597e-04, |
7.4622e-05, 4.7901e-04], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8486, device='cuda:2', grad_fn=<UnbindBackward0>), False: tensor(0.1301, device='cuda:2', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0213, device='cuda:2', grad_fn=<SubBackward0>)} |
tensor([9.1554e-01, 2.7647e-02, 7.4390e-03, 4.5581e-02, 2.0015e-03, 9.7163e-04, |
7.3437e-04, 8.3425e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.1554e-01, 2.7647e-02, 7.4390e-03, 4.5581e-02, 2.0015e-03, 9.7163e-04, |
7.3437e-04, 8.3425e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
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