text
stringlengths 0
1.16k
|
|---|
[('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']]
|
[('11', 0.12740768001087358), ('10', 0.12548679249075975), ('12', 0.12538137681693887), ('9', 0.12485855662563465), ('8', 0.12469919178932766), ('13', 0.12431757055023795), ('7', 0.12396146028399917), ('14', 0.1238873714322284)]
|
[['11', '10', '12', '9', '8', '13', '7', '14']]
|
[('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']]
|
[('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: 7, images per sample: 7.0, dynamic token length: 1861
|
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: 1861
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
|
tensor([1.0000e+00, 1.0215e-08, 4.3113e-11, 1.0462e-07, 6.3231e-09, 2.4879e-09,
|
2.4484e-10, 4.5111e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>)
|
yes *************
|
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.0215e-08, 4.3113e-11, 1.0462e-07, 6.3231e-09, 2.4879e-09,
|
2.4484e-10, 4.5111e-09], device='cuda:2', grad_fn=<SelectBackward0>)
|
tensor([1.0000e+00, 2.9649e-07, 7.5235e-10, 1.7603e-06, 1.9398e-10, 4.0500e-11,
|
2.5497e-10, 5.7472e-11], device='cuda:1', grad_fn=<SoftmaxBackward0>)
|
2 *************
|
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 2.9649e-07, 7.5235e-10, 1.7603e-06, 1.9398e-10, 4.0500e-11,
|
2.5497e-10, 5.7472e-11], device='cuda:1', grad_fn=<SelectBackward0>)
|
tensor([8.1996e-01, 1.6963e-03, 4.9756e-02, 1.0399e-03, 4.9036e-06, 1.1206e-01,
|
2.0540e-03, 1.3430e-02], device='cuda:0', grad_fn=<SoftmaxBackward0>)
|
11 *************
|
['11', '10', '12', '9', '8', '13', '7', '14'] tensor([8.1996e-01, 1.6963e-03, 4.9756e-02, 1.0399e-03, 4.9036e-06, 1.1206e-01,
|
2.0540e-03, 1.3430e-02], device='cuda:0', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(4.3113e-11, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1917e-07, device='cuda:2', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=LEFT,question='How many hyenas are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} >= 2')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.9398e-10, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=LEFT,question='Does the drum set on the left include cymbals?')
|
ANSWER1=EVAL(expr='{ANSWER0}')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), False: tensor(1., device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)}
|
torch.Size([3, 3, 448, 448])
|
ANSWER0=VQA(image=RIGHT,question='Is there a clown fish in the image?')
|
FINAL_ANSWER=RESULT(var=ANSWER0)
|
tensor([1.0000e+00, 6.2862e-10, 3.5368e-07, 6.5740e-11, 6.1024e-12, 4.2509e-08,
|
8.3325e-10, 4.6857e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>)
|
no *************
|
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 6.2862e-10, 3.5368e-07, 6.5740e-11, 6.1024e-12, 4.2509e-08,
|
8.3325e-10, 4.6857e-07], device='cuda:3', grad_fn=<SelectBackward0>)
|
torch.Size([3, 3, 448, 448])
|
torch.Size([7, 3, 448, 448])
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(6.2862e-10, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(8.3447e-07, device='cuda:3', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=LEFT,question='How many hyenas are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} == 3')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([7, 3, 448, 448])
|
question: ['How many hyenas are in the image?'], responses:['1']
|
question: ['Is there a clown fish in the image?'], responses:['no']
|
[('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']]
|
[('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([3, 3, 448, 448]) knan debug pixel values shape
|
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838
|
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838
|
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839
|
question: ['Does the drum set on the left include cymbals?'], 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']]
|
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838
|
question: ['How many hyenas are in the image?'], responses:['0']
|
[('0', 0.13077743594303964), ('circles', 0.12449813349255197), ('maroon', 0.12428926693968681), ('large', 0.1242263466991631), ('rooster', 0.12409315512763705), ('nuts', 0.12408018414184876), ('beige', 0.1240288472550799), ('bottle', 0.12400663040099273)]
|
[['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle']]
|
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838
|
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839
|
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839
|
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839
|
tensor([1.0000e+00, 3.8127e-10, 1.2378e-10, 4.1874e-10, 1.6142e-10, 2.8871e-08,
|
2.4286e-09, 7.5733e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>)
|
1 *************
|
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 3.8127e-10, 1.2378e-10, 4.1874e-10, 1.6142e-10, 2.8871e-08,
|
2.4286e-09, 7.5733e-10], device='cuda:2', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(3.3143e-08, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)}
|
tensor([1.0000e+00, 8.5921e-10, 4.1801e-07, 7.6696e-12, 1.4021e-11, 1.3790e-08,
|
1.2926e-09, 2.7682e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>)
|
no *************
|
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 8.5921e-10, 4.1801e-07, 7.6696e-12, 1.4021e-11, 1.3790e-08,
|
1.2926e-09, 2.7682e-07], device='cuda:0', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(8.5921e-10, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(7.1526e-07, device='cuda:0', grad_fn=<SubBackward0>)}
|
tensor([1.0000e+00, 2.5049e-09, 1.1862e-08, 8.0478e-09, 4.9984e-11, 6.2238e-11,
|
7.2873e-11, 3.1056e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>)
|
yes *************
|
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.5049e-09, 1.1862e-08, 8.0478e-09, 4.9984e-11, 6.2238e-11,
|
7.2873e-11, 3.1056e-09], device='cuda:1', grad_fn=<SelectBackward0>)
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.