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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 |
question: ['Is the dog wearing a collar?'], responses:['yes'] |
question: ['What is the material of the jewelry in the image?'], responses:['metal'] |
[('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']] |
[('metal', 0.1263430186656571), ('glass', 0.12522357438951787), ('steel', 0.12503695230689602), ('iron', 0.12479778246180684), ('rust', 0.12469877097234755), ('fur', 0.12466446134913117), ('stone', 0.12462037078361551), ('wine', 0.12461506907102783)] |
[['metal', 'glass', 'steel', 'iron', 'rust', 'fur', 'stone', 'wine']] |
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 |
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: 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 |
tensor([7.4412e-01, 6.5021e-02, 9.3671e-03, 1.7672e-01, 2.8580e-03, 8.1806e-04, |
1.0184e-03, 7.3525e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([7.4412e-01, 6.5021e-02, 9.3671e-03, 1.7672e-01, 2.8580e-03, 8.1806e-04, |
1.0184e-03, 7.3525e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8233, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.1767, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
tensor([7.4876e-01, 3.0888e-02, 1.2150e-02, 2.1025e-03, 2.9656e-03, 1.6354e-03, |
2.0142e-01, 8.5029e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([7.4876e-01, 3.0888e-02, 1.2150e-02, 2.1025e-03, 2.9656e-03, 1.6354e-03, |
2.0142e-01, 8.5029e-05], device='cuda:0', grad_fn=<SelectBackward0>) |
ANSWER0=VQA(image=LEFT,question='How many insects are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.2512, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.7488, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is there at least one person standing on a curb by the open door of a parked yellow bus with a non-flat front?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
question: ['How many insects are in the image?'], responses:['1'] |
question: ['Is there at least one person standing on a curb by the open door of a parked yellow bus with a non-flat front?'], 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']] |
[('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([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: 1878 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 |
tensor([8.5108e-01, 1.5961e-02, 1.3052e-01, 9.4055e-04, 5.6897e-05, 2.0205e-04, |
5.9719e-05, 1.1808e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.5108e-01, 1.5961e-02, 1.3052e-01, 9.4055e-04, 5.6897e-05, 2.0205e-04, |
5.9719e-05, 1.1808e-03], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8511, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.1305, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0184, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many rodents are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
tensor([0.8047, 0.0581, 0.0701, 0.0342, 0.0058, 0.0120, 0.0095, 0.0056], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
metal ************* |
['metal', 'glass', 'steel', 'iron', 'rust', 'fur', 'stone', 'wine'] tensor([0.8047, 0.0581, 0.0701, 0.0342, 0.0058, 0.0120, 0.0095, 0.0056], |
device='cuda:2', grad_fn=<SelectBackward0>) |
torch.Size([1, 3, 448, 448]) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many chimps are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['How many rodents 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([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 |
tensor([9.2999e-01, 1.3265e-02, 5.5295e-03, 2.2997e-03, 3.3527e-03, 1.8876e-03, |
4.3496e-02, 1.7527e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.2999e-01, 1.3265e-02, 5.5295e-03, 2.2997e-03, 3.3527e-03, 1.8876e-03, |
4.3496e-02, 1.7527e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0700, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9300, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.7881e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([4.3387e-01, 1.1298e-01, 3.4456e-02, 6.9997e-03, 1.3078e-02, 3.9775e-03, |
3.9433e-01, 3.0306e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([4.3387e-01, 1.1298e-01, 3.4456e-02, 6.9997e-03, 1.3078e-02, 3.9775e-03, |
3.9433e-01, 3.0306e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.4339, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.5661, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
tensor([7.7625e-01, 2.2240e-01, 9.6654e-05, 1.6778e-04, 5.6044e-04, 6.5308e-05, |
2.8533e-04, 1.8126e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([7.7625e-01, 2.2240e-01, 9.6654e-05, 1.6778e-04, 5.6044e-04, 6.5308e-05, |
2.8533e-04, 1.8126e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.2224, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(0.7762, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0014, device='cuda:0', grad_fn=<SubBackward0>)} |
question: ['How many chimps 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([7, 3, 448, 448]) knan debug pixel values shape |
tensor([9.1766e-01, 1.4837e-02, 7.2286e-03, 2.7272e-03, 3.3046e-03, 2.2901e-03, |
5.1774e-02, 1.8380e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
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