text stringlengths 0 1.16k |
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question: ['Is there a dog sitting upright inside?'], responses:['no'] |
torch.Size([11, 3, 448, 448]) knan debug pixel values shape |
[('3', 0.12809209985493852), ('4', 0.12520382509374006), ('1', 0.1251059160028928), ('5', 0.12483070991268265), ('8', 0.12458076282181878), ('2', 0.12413212281858195), ('6', 0.1241125313968017), ('12', 0.12394203209854344)] |
[['3', '4', '1', '5', '8', '2', '6', '12']] |
[('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([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: 3401 |
tensor([9.9998e-01, 2.4300e-05, 1.4562e-07, 1.4930e-10, 2.1106e-11, 1.9314e-09, |
3.7142e-10, 5.8666e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.9998e-01, 2.4300e-05, 1.4562e-07, 1.4930e-10, 2.1106e-11, 1.9314e-09, |
3.7142e-10, 5.8666e-08], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(2.4300e-05, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Is the dog in the left image laying down?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
question: ['Is the dog in the left image laying down?'], 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 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
tensor([1.0000e+00, 3.1609e-10, 1.3759e-06, 2.6048e-11, 2.8282e-11, 1.7531e-08, |
6.1580e-10, 1.9521e-06], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 3.1609e-10, 1.3759e-06, 2.6048e-11, 2.8282e-11, 1.7531e-08, |
6.1580e-10, 1.9521e-06], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(3.1609e-10, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(3.4571e-06, device='cuda:2', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
tensor([1.0000e+00, 1.5624e-07, 8.8514e-07, 4.1811e-07, 1.1966e-08, 2.9471e-08, |
2.8122e-08, 1.2467e-08], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 1.5624e-07, 8.8514e-07, 4.1811e-07, 1.1966e-08, 2.9471e-08, |
2.8122e-08, 1.2467e-08], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(9.6716e-07, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is there water in the image?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
tensor([9.9999e-01, 3.7267e-06, 3.1742e-08, 3.2427e-09, 1.3888e-11, 2.7265e-06, |
1.1096e-10, 2.1555e-10], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([9.9999e-01, 3.7267e-06, 3.1742e-08, 3.2427e-09, 1.3888e-11, 2.7265e-06, |
1.1096e-10, 2.1555e-10], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(6.4885e-06, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the carriage covered?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
tensor([1.0000e+00, 2.1056e-10, 3.6471e-07, 4.9519e-12, 2.6405e-12, 1.6073e-08, |
1.0925e-10, 7.2907e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 2.1056e-10, 3.6471e-07, 4.9519e-12, 2.6405e-12, 1.6073e-08, |
1.0925e-10, 7.2907e-07], device='cuda:3', grad_fn=<SelectBackward0>) |
torch.Size([7, 3, 448, 448]) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.1056e-10, device='cuda:3', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(1.0729e-06, device='cuda:3', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Does the dog in the image have food in its mouth?') |
ANSWER1=RESULT(var=ANSWER0) |
torch.Size([13, 3, 448, 448]) |
question: ['Is there 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']] |
question: ['Is the carriage covered?'], 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([7, 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: 1857 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 |
question: ['Does the dog in the image have food in its mouth?'], 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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 |
tensor([1.0000e+00, 1.9751e-07, 8.4943e-08, 7.5507e-12, 2.4365e-11, 5.5395e-10, |
3.3895e-11, 7.8954e-08], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.9751e-07, 8.4943e-08, 7.5507e-12, 2.4365e-11, 5.5395e-10, |
3.3895e-11, 7.8954e-08], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.9751e-07, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(1.7881e-07, device='cuda:0', grad_fn=<SubBackward0>)} |
tensor([1.0000e+00, 3.3892e-09, 1.9172e-10, 8.7572e-09, 1.6919e-10, 3.5263e-10, |
1.6577e-11, 8.5929e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 3.3892e-09, 1.9172e-10, 8.7572e-09, 1.6919e-10, 3.5263e-10, |
1.6577e-11, 8.5929e-10], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(1.9172e-10, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-1.9172e-10, device='cuda:1', grad_fn=<SubBackward0>)} |
tensor([1.0000e+00, 1.2617e-08, 6.8896e-11, 2.5858e-08, 2.1935e-10, 4.6715e-10, |
7.6589e-11, 2.2424e-08], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.2617e-08, 6.8896e-11, 2.5858e-08, 2.1935e-10, 4.6715e-10, |
7.6589e-11, 2.2424e-08], device='cuda:3', grad_fn=<SelectBackward0>) |
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