text
stringlengths 0
1.16k
|
|---|
torch.Size([7, 3, 448, 448])
|
question: ['Is the dog wearing something?'], responses:['yes']
|
question: ['What color is the cabinet in the image?'], responses:['green']
|
question: ['Is the panda hanging against the side of a tree trunk?'], 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']]
|
[('green', 0.1326115459908909), ('yellow', 0.12668030247077625), ('red', 0.12551779073733718), ('wild', 0.12324669870262604), ('orange and blue', 0.12319974118412196), ('bronze', 0.1230515752050065), ('pink', 0.12286305245049417), ('red white blue', 0.12282929325874692)]
|
[['green', 'yellow', 'red', 'wild', 'orange and blue', 'bronze', 'pink', 'red white blue']]
|
[('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
|
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
|
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
|
question: ['Is a toilet visible in the image?'], responses:['yes']
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866
|
[('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: 1865
|
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
|
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: 1866
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866
|
tensor([1.0000e+00, 4.9608e-08, 6.0919e-11, 1.4885e-07, 5.8800e-10, 1.0693e-09,
|
3.5699e-10, 4.0862e-08], device='cuda:1', grad_fn=<SoftmaxBackward0>)
|
yes *************
|
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 4.9608e-08, 6.0919e-11, 1.4885e-07, 5.8800e-10, 1.0693e-09,
|
3.5699e-10, 4.0862e-08], device='cuda:1', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(6.0919e-11, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(2.3836e-07, device='cuda:1', grad_fn=<SubBackward0>)}
|
tensor([9.9318e-01, 4.9812e-04, 2.3722e-04, 2.5867e-05, 2.7643e-04, 3.4838e-03,
|
1.9317e-03, 3.6501e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>)
|
green *************
|
['green', 'yellow', 'red', 'wild', 'orange and blue', 'bronze', 'pink', 'red white blue'] tensor([9.9318e-01, 4.9812e-04, 2.3722e-04, 2.5867e-05, 2.7643e-04, 3.4838e-03,
|
1.9317e-03, 3.6501e-04], device='cuda:3', grad_fn=<SelectBackward0>)
|
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} == 2')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
tensor([1.0000e+00, 1.1033e-09, 3.1515e-07, 4.7517e-13, 7.1624e-13, 1.2914e-09,
|
1.9680e-10, 1.7140e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>)
|
no *************
|
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.1033e-09, 3.1515e-07, 4.7517e-13, 7.1624e-13, 1.2914e-09,
|
1.9680e-10, 1.7140e-07], device='cuda:0', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:3', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=RIGHT,question='How many pairs of tinted lips are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} == 1')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([7, 3, 448, 448])
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.1033e-09, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(4.7684e-07, device='cuda:0', grad_fn=<DivBackward0>)}
|
torch.Size([3, 3, 448, 448])
|
ANSWER0=VQA(image=RIGHT,question='How many rodents are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} == 2')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([1, 3, 448, 448])
|
question: ['How many rodents 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([1, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
|
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
|
question: ['How many pairs of tinted lips are in the image?'], responses:['1']
|
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
|
[('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']]
|
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
|
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
|
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
|
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
|
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
|
tensor([1.0000e+00, 9.8895e-10, 2.8334e-10, 6.3352e-10, 6.0438e-10, 5.7427e-08,
|
7.8092e-09, 1.7533e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>)
|
1 *************
|
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 9.8895e-10, 2.8334e-10, 6.3352e-10, 6.0438e-10, 5.7427e-08,
|
7.8092e-09, 1.7533e-09], device='cuda:0', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(7.8092e-09, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)}
|
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([7, 3, 448, 448]) knan debug pixel values shape
|
tensor([1.0000e+00, 2.6414e-09, 5.0511e-10, 4.8676e-09, 2.2275e-09, 1.3094e-07,
|
2.4337e-08, 8.1976e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>)
|
1 *************
|
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 2.6414e-09, 5.0511e-10, 4.8676e-09, 2.2275e-09, 1.3094e-07,
|
2.4337e-08, 8.1976e-10], device='cuda:3', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.6634e-07, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)}
|
tensor([1.0000e+00, 7.0882e-09, 6.2862e-10, 1.9957e-08, 1.3128e-10, 9.4366e-10,
|
4.5304e-11, 2.2729e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>)
|
yes *************
|
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 7.0882e-09, 6.2862e-10, 1.9957e-08, 1.3128e-10, 9.4366e-10,
|
4.5304e-11, 2.2729e-09], device='cuda:2', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(6.2862e-10, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-6.2862e-10, device='cuda:2', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=LEFT,question='How many insects are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} == 2')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([7, 3, 448, 448])
|
tensor([1.0000e+00, 4.8957e-10, 6.7562e-11, 1.8800e-10, 1.1269e-10, 4.9423e-09,
|
6.5503e-09, 4.6812e-11], device='cuda:1', grad_fn=<SoftmaxBackward0>)
|
1 *************
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.