text stringlengths 0 1.16k |
|---|
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 5') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Is there a black pair of sneakers sitting on a shoe box in the image?') |
ANSWER1=RESULT(var=ANSWER0) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Does the left image show an overlapping, upright row of at least three color versions of a pencil case style?'], 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: 1, images per sample: 1.0, dynamic token length: 338 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 |
tensor([9.9994e-01, 5.8289e-05, 4.1584e-07, 3.4167e-10, 4.2704e-11, 2.2567e-09, |
9.8169e-10, 1.3026e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.9994e-01, 5.8289e-05, 4.1584e-07, 3.4167e-10, 4.2704e-11, 2.2567e-09, |
9.8169e-10, 1.3026e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(5.8289e-05, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.9999, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(4.7684e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Is the dog in the image lying down?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
question: ['How many wolves are in the image?'], responses:['four'] |
question: ['How many animals are in the image?'], responses:['5'] |
[('7 eleven', 0.12650899275575006), ('4', 0.125210025275264), ('first', 0.12483048280083887), ('3', 0.12473532336671392), ('5', 0.1247268629491862), ('dark', 0.12470563072493092), ('forward', 0.12466964370422237), ('bag', 0.12461303842309367)] |
[['7 eleven', '4', 'first', '3', '5', 'dark', 'forward', 'bag']] |
[('5', 0.12793059870235002), ('8', 0.12539646467821697), ('4', 0.12509737486793587), ('6', 0.12470234839853608), ('3', 0.12467331676337925), ('7', 0.12441254825093238), ('11', 0.12401867309944531), ('9', 0.12376867523920407)] |
[['5', '8', '4', '6', '3', '7', '11', '9']] |
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 black pair of sneakers sitting on a shoe box 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([13, 3, 448, 448]) knan debug pixel values shape |
question: ['Is the dog in the image lying 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([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
tensor([1.0488e-01, 7.5854e-05, 1.2740e-07, 1.9507e-01, 9.0884e-12, 6.9995e-01, |
1.8172e-06, 1.4023e-05], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
7 ************* |
['5', '8', '4', '6', '3', '7', '11', '9'] tensor([1.0488e-01, 7.5854e-05, 1.2740e-07, 1.9507e-01, 9.0884e-12, 6.9995e-01, |
1.8172e-06, 1.4023e-05], device='cuda:2', grad_fn=<SelectBackward0>) |
tensor([3.9747e-14, 9.8153e-01, 4.8146e-08, 1.8456e-02, 1.2592e-05, 2.6284e-08, |
7.0123e-08, 3.6053e-08], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
4 ************* |
['7 eleven', '4', 'first', '3', '5', 'dark', 'forward', 'bag'] tensor([3.9747e-14, 9.8153e-01, 4.8146e-08, 1.8456e-02, 1.2592e-05, 2.6284e-08, |
7.0123e-08, 3.6053e-08], device='cuda:3', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.1049, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.8951, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Is there a child in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(1.7881e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the parrot in the image flying?') |
ANSWER1=RESULT(var=ANSWER0) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
question: ['Is there a child in the image?'], responses:['yes'] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
question: ['Is the parrot in the image flying?'], responses:['no'] |
[('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']] |
[('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: 13, images per sample: 13.0, dynamic token length: 3397 |
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: 3398 |
tensor([1.0000e+00, 7.8609e-09, 9.3436e-11, 7.1802e-09, 2.2539e-11, 2.9864e-11, |
3.2184e-11, 3.4138e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 7.8609e-09, 9.3436e-11, 7.1802e-09, 2.2539e-11, 2.9864e-11, |
3.2184e-11, 3.4138e-09], device='cuda:1', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1., device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(9.3436e-11, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-9.3436e-11, device='cuda:1', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many towels are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 4') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
tensor([1.0000e+00, 1.7177e-08, 4.6977e-11, 9.4519e-08, 2.5193e-09, 2.2991e-09, |
1.4882e-10, 4.6900e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.7177e-08, 4.6977e-11, 9.4519e-08, 2.5193e-09, 2.2991e-09, |
1.4882e-10, 4.6900e-09], device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(4.6977e-11, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1916e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
tensor([1.0000e+00, 2.7895e-10, 3.2048e-07, 4.4136e-11, 6.8620e-11, 1.7207e-08, |
8.3810e-10, 9.4597e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.