text stringlengths 0 1.16k |
|---|
4.0819e-09, 1.1794e-06], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(7.8241e-10, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.2650e-06, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the dog outside?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) |
question: ['Is there a black pair of sneakers sitting on a shoe box in the image?'], responses:['no'] |
question: ['Does the image contain an outside view of a storefront?'], responses:['yes'] |
[('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']] |
[('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 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 |
tensor([1.0000e+00, 9.2776e-07, 8.8524e-07, 2.8743e-07, 6.8116e-09, 5.5396e-08, |
2.9242e-08, 6.9729e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 9.2776e-07, 8.8524e-07, 2.8743e-07, 6.8116e-09, 5.5396e-08, |
2.9242e-08, 6.9729e-09], device='cuda:2', grad_fn=<SelectBackward0>) |
question: ['Is the dog outside?'], responses:['no'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(2.1989e-06, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 |
ANSWER0=VQA(image=RIGHT,question='How many warthogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 5') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
[('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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 |
tensor([1.0000e+00, 1.3730e-09, 8.1863e-07, 8.0692e-12, 2.4968e-11, 8.7125e-09, |
3.2240e-09, 7.0986e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.3730e-09, 8.1863e-07, 8.0692e-12, 2.4968e-11, 8.7125e-09, |
3.2240e-09, 7.0986e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 2.1177e-09, 5.0513e-10, 1.8056e-08, 2.4195e-10, 1.0423e-10, |
4.7947e-11, 4.0289e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.1177e-09, 5.0513e-10, 1.8056e-08, 2.4195e-10, 1.0423e-10, |
4.7947e-11, 4.0289e-09], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.3730e-09, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(1.5497e-06, device='cuda:0', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Does the image contain a flower?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(5.0513e-10, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-5.0513e-10, device='cuda:1', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is a eating utensil visible in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many warthogs are in the image?'], responses:['3'] |
[('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']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
question: ['Is a eating utensil 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 |
question: ['Does the image contain a flower?'], 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([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
tensor([9.8308e-01, 1.6915e-02, 9.4250e-08, 5.7069e-07, 1.8267e-10, 3.0481e-08, |
4.3821e-10, 2.0189e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([9.8308e-01, 1.6915e-02, 9.4250e-08, 5.7069e-07, 1.8267e-10, 3.0481e-08, |
4.3821e-10, 2.0189e-08], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(5.7069e-07, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
tensor([1.0000e+00, 3.4328e-08, 1.9858e-10, 3.1602e-08, 6.5471e-09, 3.6534e-08, |
3.5984e-10, 8.8924e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 3.4328e-08, 1.9858e-10, 3.1602e-08, 6.5471e-09, 3.6534e-08, |
3.5984e-10, 8.8924e-09], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.9858e-10, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1901e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([1.0000e+00, 7.5826e-10, 2.0392e-07, 1.5253e-11, 3.5953e-12, 4.5461e-09, |
1.7295e-10, 1.0020e-06], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 7.5826e-10, 2.0392e-07, 1.5253e-11, 3.5953e-12, 4.5461e-09, |
1.7295e-10, 1.0020e-06], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(7.5826e-10, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-06, device='cuda:3', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
tensor([1.0000e+00, 1.8086e-08, 1.8726e-10, 1.3830e-07, 2.0260e-10, 2.6307e-10, |
8.5174e-11, 1.0485e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.8086e-08, 1.8726e-10, 1.3830e-07, 2.0260e-10, 2.6307e-10, |
8.5174e-11, 1.0485e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(1.8726e-10, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(2.3823e-07, device='cuda:0', grad_fn=<SubBackward0>)} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.