text
stringlengths 0
1.16k
|
|---|
ANSWER0=VQA(image=RIGHT,question='How many pencil cases are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} == 3')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} == 2')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([7, 3, 448, 448])
|
torch.Size([1, 3, 448, 448])
|
torch.Size([13, 3, 448, 448])
|
question: ['How many umbrellas are in the image?'], responses:['3']
|
question: ['How many dogs are in the image?'], responses:['2']
|
[('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([1, 3, 448, 448]) knan debug pixel values shape
|
[('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([1, 3, 448, 448]) knan debug pixel values shape
|
tensor([9.9772e-01, 2.1825e-03, 2.6405e-09, 1.9290e-06, 3.0992e-09, 9.5892e-05,
|
1.8512e-07, 9.7344e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>)
|
3 *************
|
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([9.9772e-01, 2.1825e-03, 2.6405e-09, 1.9290e-06, 3.0992e-09, 9.5892e-05,
|
1.8512e-07, 9.7344e-09], device='cuda:1', grad_fn=<SelectBackward0>)
|
tensor([1.0000e+00, 3.5133e-08, 1.7491e-09, 3.6320e-07, 2.1722e-10, 1.5926e-09,
|
1.0860e-09, 1.0347e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>)
|
2 *************
|
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 3.5133e-08, 1.7491e-09, 3.6320e-07, 2.1722e-10, 1.5926e-09,
|
1.0860e-09, 1.0347e-09], device='cuda:3', grad_fn=<SelectBackward0>)
|
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(9.5895e-05, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9999, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)}
|
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(4.0402e-07, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:3', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=RIGHT,question='Does the car in the image have a top?')
|
ANSWER1=EVAL(expr='{ANSWER0}')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
question: ['Is the animal in the image wearing an article of clothing?'], responses:['no']
|
ANSWER0=VQA(image=RIGHT,question='How many jellyfish are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} < 4')
|
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']]
|
torch.Size([13, 3, 448, 448])
|
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864
|
question: ['How many pencil cases are in the image?'], responses:['3']
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865
|
[('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']]
|
question: ['Does the car in the image have a top?'], 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']]
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864
|
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: 1864
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865
|
question: ['How many jellyfish 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']]
|
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: 1865
|
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
|
tensor([1.0000e+00, 4.8956e-10, 5.9563e-07, 1.0302e-10, 2.5942e-10, 8.6435e-08,
|
6.6092e-10, 4.5927e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>)
|
no *************
|
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 4.8956e-10, 5.9563e-07, 1.0302e-10, 2.5942e-10, 8.6435e-08,
|
6.6092e-10, 4.5927e-07], device='cuda:0', grad_fn=<SelectBackward0>)
|
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(4.8956e-10, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-06, device='cuda:0', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=RIGHT,question='How many pandas are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} == 2')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([13, 3, 448, 448])
|
tensor([1.0000e+00, 7.1232e-10, 1.4831e-07, 1.1997e-10, 6.3754e-11, 9.4362e-09,
|
1.8532e-09, 1.4825e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>)
|
no *************
|
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 7.1232e-10, 1.4831e-07, 1.1997e-10, 6.3754e-11, 9.4362e-09,
|
1.8532e-09, 1.4825e-07], device='cuda:1', grad_fn=<SelectBackward0>)
|
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(7.1232e-10, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.3842e-07, device='cuda:1', grad_fn=<DivBackward0>)}
|
question: ['How many pandas 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([13, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396
|
tensor([9.9951e-01, 4.8931e-04, 2.0542e-06, 5.9787e-09, 5.8620e-11, 2.5587e-06,
|
7.0337e-11, 1.0330e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>)
|
3 *************
|
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([9.9951e-01, 4.8931e-04, 2.0542e-06, 5.9787e-09, 5.8620e-11, 2.5587e-06,
|
7.0337e-11, 1.0330e-08], device='cuda:2', grad_fn=<SelectBackward0>)
|
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.9995, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.0005, 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: 3396
|
ANSWER0=VQA(image=LEFT,question='Is the dog outside?')
|
ANSWER1=EVAL(expr='{ANSWER0}')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([1, 3, 448, 448])
|
question: ['Is the dog outside?'], 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: 3396
|
tensor([1.0000e+00, 1.2626e-08, 9.5477e-08, 8.0377e-12, 1.4530e-12, 2.4490e-09,
|
1.6636e-10, 3.5680e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>)
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.