text
stringlengths 0
1.16k
|
|---|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
|
tensor([0.5106, 0.2913, 0.0145, 0.0834, 0.0049, 0.0736, 0.0204, 0.0014],
|
device='cuda:1', grad_fn=<SoftmaxBackward0>)
|
3 *************
|
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([0.5106, 0.2913, 0.0145, 0.0834, 0.0049, 0.0736, 0.0204, 0.0014],
|
device='cuda:1', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9119, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0881, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=RIGHT,question='Is the panda nibbling something?')
|
FINAL_ANSWER=RESULT(var=ANSWER0)
|
torch.Size([7, 3, 448, 448])
|
tensor([0.6016, 0.0741, 0.0267, 0.0097, 0.0125, 0.0075, 0.2670, 0.0009],
|
device='cuda:2', grad_fn=<SoftmaxBackward0>)
|
1 *************
|
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([0.6016, 0.0741, 0.0267, 0.0097, 0.0125, 0.0075, 0.2670, 0.0009],
|
device='cuda:2', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6016, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.3984, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=RIGHT,question='Do prairie dogs pose together in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0}')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([3, 3, 448, 448])
|
tensor([5.2971e-01, 2.7289e-02, 4.3914e-01, 1.1774e-03, 1.8056e-04, 6.5751e-04,
|
3.0853e-04, 1.5332e-03], device='cuda:0', grad_fn=<SoftmaxBackward0>)
|
yes *************
|
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([5.2971e-01, 2.7289e-02, 4.3914e-01, 1.1774e-03, 1.8056e-04, 6.5751e-04,
|
3.0853e-04, 1.5332e-03], device='cuda:0', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.5297, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(0.4391, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0311, device='cuda:0', grad_fn=<SubBackward0>)}
|
tensor([8.6619e-01, 1.3265e-01, 5.3778e-05, 9.2722e-05, 2.0549e-04, 3.4468e-04,
|
2.8890e-04, 1.6598e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>)
|
no *************
|
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([8.6619e-01, 1.3265e-01, 5.3778e-05, 9.2722e-05, 2.0549e-04, 3.4468e-04,
|
2.8890e-04, 1.6598e-04], device='cuda:3', grad_fn=<SelectBackward0>)
|
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} <= 1')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([5, 3, 448, 448])
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.1327, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.8662, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0012, device='cuda:3', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=RIGHT,question='How many glass panels does the furniture piece have?')
|
ANSWER1=EVAL(expr='{ANSWER0} >= 3')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
question: ['Do prairie dogs pose together in the image?'], responses:['yes']
|
torch.Size([13, 3, 448, 448])
|
[('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([3, 3, 448, 448]) knan debug pixel values shape
|
question: ['Is the panda nibbling something?'], 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: ['How many dogs 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([5, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348
|
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348
|
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348
|
tensor([7.2832e-01, 3.1394e-02, 2.3645e-01, 2.1177e-03, 1.1554e-04, 4.8203e-04,
|
8.1221e-05, 1.0346e-03], device='cuda:2', grad_fn=<SoftmaxBackward0>)
|
yes *************
|
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([7.2832e-01, 3.1394e-02, 2.3645e-01, 2.1177e-03, 1.1554e-04, 4.8203e-04,
|
8.1221e-05, 1.0346e-03], device='cuda:2', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7283, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.2365, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0352, device='cuda:2', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=RIGHT,question='How many pug dogs are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} == 3')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([7, 3, 448, 448])
|
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348
|
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348
|
question: ['How many glass panels does the furniture piece have?'], responses:['2']
|
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348
|
[('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: 5, images per sample: 5.0, dynamic token length: 1348
|
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
|
question: ['How many pug dogs are in the image?'], responses:['3']
|
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348
|
[('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']]
|
tensor([9.7081e-01, 5.2555e-03, 2.4056e-03, 1.1682e-03, 1.4132e-03, 1.0845e-03,
|
1.7780e-02, 8.3168e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>)
|
1 *************
|
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.7081e-01, 5.2555e-03, 2.4056e-03, 1.1682e-03, 1.4132e-03, 1.0845e-03,
|
1.7780e-02, 8.3168e-05], device='cuda:0', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9708, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-07, device='cuda:0', grad_fn=<DivBackward0>)}
|
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
|
ANSWER0=VQA(image=LEFT,question='What color is the keyboard?')
|
ANSWER1=EVAL(expr='{ANSWER0} == "black"')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([13, 3, 448, 448])
|
tensor([8.9409e-01, 1.9740e-02, 8.3122e-02, 1.4554e-03, 7.2159e-05, 4.0846e-04,
|
4.3499e-05, 1.0731e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>)
|
yes *************
|
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.9409e-01, 1.9740e-02, 8.3122e-02, 1.4554e-03, 7.2159e-05, 4.0846e-04,
|
4.3499e-05, 1.0731e-03], device='cuda:1', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8941, device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(0.0831, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0228, device='cuda:1', grad_fn=<SubBackward0>)}
|
ANSWER0=VQA(image=LEFT,question='What color is the purse in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} == "blue"')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([1, 3, 448, 448])
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.