text stringlengths 0 1.16k |
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torch.Size([13, 3, 448, 448]) |
question: ['Is there a mostly black dog leaping through the air in the image?'], 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([3, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 |
question: ['Does the right image show a "Whataburger" cup sitting on a surface?'], responses:['no'] |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 |
[('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: 3, images per sample: 3.0, dynamic token length: 844 |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 |
question: ['Are books hanging on the wall in rectangular boxes?'], responses:['yes'] |
tensor([1.0000e+00, 2.9990e-09, 5.7025e-07, 9.6749e-13, 5.3339e-12, 2.7975e-09, |
1.7634e-10, 1.0087e-06], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 2.9990e-09, 5.7025e-07, 9.6749e-13, 5.3339e-12, 2.7975e-09, |
1.7634e-10, 1.0087e-06], device='cuda:0', grad_fn=<SelectBackward0>) |
question: ['Is there a person standing near the entrance of the store?'], responses:['yes'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.9990e-09, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.6689e-06, device='cuda:0', grad_fn=<DivBackward0>)} |
[('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']] |
ANSWER0=VQA(image=RIGHT,question='How many steeples are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('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]) |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 3.8127e-10, 1.4882e-06, 7.4910e-12, 7.8482e-11, 7.1057e-09, |
1.1604e-09, 1.0010e-06], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 3.8127e-10, 1.4882e-06, 7.4910e-12, 7.8482e-11, 7.1057e-09, |
1.1604e-09, 1.0010e-06], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(3.8127e-10, device='cuda:3', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(2.3842e-06, device='cuda:3', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many water buffalo are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['How many steeples 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']] |
question: ['How many water buffalo are in the image?'], responses:['30'] |
[('30', 0.12740713819081037), ('29', 0.12530514884086683), ('40', 0.1249276424885007), ('28', 0.12486301766888525), ('31', 0.12483184010065636), ('32', 0.12430090544871905), ('26', 0.12425497754646514), ('35', 0.12410932971509633)] |
[['30', '29', '40', '28', '31', '32', '26', '35']] |
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 |
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: 3397 |
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: 3397 |
tensor([1.0000e+00, 1.5943e-09, 5.2114e-10, 3.2903e-09, 2.0517e-11, 1.3673e-11, |
1.0856e-12, 2.7830e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.5943e-09, 5.2114e-10, 3.2903e-09, 2.0517e-11, 1.3673e-11, |
1.0856e-12, 2.7830e-09], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(5.2114e-10, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-5.2114e-10, device='cuda:2', grad_fn=<DivBackward0>)} |
tensor([1.0000e+00, 2.9194e-08, 1.9474e-10, 8.8464e-09, 1.7343e-09, 8.4590e-10, |
7.1723e-11, 2.1999e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.9194e-08, 1.9474e-10, 8.8464e-09, 1.7343e-09, 8.4590e-10, |
7.1723e-11, 2.1999e-09], device='cuda:1', grad_fn=<SelectBackward0>) |
ANSWER0=VQA(image=RIGHT,question='How many balconies are on the building?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.9474e-10, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.9474e-10, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many birds are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
tensor([0.5825, 0.0332, 0.2306, 0.0180, 0.0079, 0.0028, 0.0185, 0.1065], |
device='cuda:3', grad_fn=<SoftmaxBackward0>) |
30 ************* |
['30', '29', '40', '28', '31', '32', '26', '35'] tensor([0.5825, 0.0332, 0.2306, 0.0180, 0.0079, 0.0028, 0.0185, 0.1065], |
device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
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: 3397 |
question: ['How many balconies are on the building?'], 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 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
tensor([1.0000e+00, 2.5110e-08, 3.6744e-09, 9.5852e-10, 2.3356e-09, 1.1861e-08, |
1.0677e-06, 5.9274e-11], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 2.5110e-08, 3.6744e-09, 9.5852e-10, 2.3356e-09, 1.1861e-08, |
1.0677e-06, 5.9274e-11], device='cuda:0', grad_fn=<SelectBackward0>) |
question: ['How many birds are in the image?'], responses:['1'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0677e-06, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
[('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']] |
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