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[['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: 1350 |
question: ['How many laptop computers 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: 5, images per sample: 5.0, dynamic token length: 1350 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 |
tensor([1.0000e+00, 2.9694e-10, 1.3709e-06, 2.3532e-11, 1.8466e-10, 3.5456e-08, |
1.1762e-09, 1.0433e-06], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 2.9694e-10, 1.3709e-06, 2.3532e-11, 1.8466e-10, 3.5456e-08, |
1.1762e-09, 1.0433e-06], device='cuda:3', grad_fn=<SelectBackward0>) |
question: ['Does the image have a solid black background?'], responses:['yes'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.9694e-10, device='cuda:3', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(2.5034e-06, device='cuda:3', grad_fn=<SubBackward0>)} |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 |
ANSWER0=VQA(image=RIGHT,question='Is the dog on grass?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 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']] |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 |
question: ['Is the dog on grass?'], 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']] |
tensor([1.0000e+00, 4.5278e-10, 8.7770e-11, 1.4240e-10, 2.1687e-10, 3.2698e-08, |
1.0632e-08, 4.2098e-10], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 4.5278e-10, 8.7770e-11, 1.4240e-10, 2.1687e-10, 3.2698e-08, |
1.0632e-08, 4.2098e-10], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:0', grad_fn=<DivBackward0>), False: tensor(4.4651e-08, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many pizzas are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
question: ['How many pizzas 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']] |
torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
tensor([1.0000e+00, 3.4663e-07, 8.2332e-08, 5.8382e-08, 2.4286e-09, 3.0462e-09, |
2.3910e-09, 1.5758e-10], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 3.4663e-07, 8.2332e-08, 5.8382e-08, 2.4286e-09, 3.0462e-09, |
2.3910e-09, 1.5758e-10], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(4.9537e-07, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
tensor([9.9981e-01, 1.9110e-04, 3.1070e-07, 6.0825e-07, 4.5011e-09, 1.6431e-09, |
4.5720e-09, 5.1005e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9981e-01, 1.9110e-04, 3.1070e-07, 6.0825e-07, 4.5011e-09, 1.6431e-09, |
4.5720e-09, 5.1005e-09], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(6.0825e-07, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many trains are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
tensor([1.0000e+00, 4.8427e-09, 3.4072e-11, 1.8301e-08, 1.8434e-10, 2.0408e-10, |
3.4425e-11, 1.1456e-08], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 4.8427e-09, 3.4072e-11, 1.8301e-08, 1.8434e-10, 2.0408e-10, |
3.4425e-11, 1.1456e-08], device='cuda:3', grad_fn=<SelectBackward0>) |
question: ['How many trains are in the image?'], responses:['1'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), False: tensor(3.4072e-11, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-3.4072e-11, device='cuda:3', 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']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 8.9946e-09, 3.1126e-10, 1.0975e-08, 4.4865e-09, 5.8576e-10, |
2.3978e-11, 1.5821e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 8.9946e-09, 3.1126e-10, 1.0975e-08, 4.4865e-09, 5.8576e-10, |
2.3978e-11, 1.5821e-08], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<UnbindBackward0>), False: tensor(3.1126e-10, device='cuda:2', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-3.1126e-10, device='cuda:2', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 5') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
tensor([1.0000e+00, 4.1226e-10, 6.6515e-11, 5.2208e-11, 1.0924e-10, 1.4845e-09, |
1.0145e-08, 1.2743e-11], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 4.1226e-10, 6.6515e-11, 5.2208e-11, 1.0924e-10, 1.4845e-09, |
1.0145e-08, 1.2743e-11], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0145e-08, 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>)} |
question: ['How many dogs are in the image?'], responses:['4'] |
[('4', 0.12804651361935848), ('5', 0.12521071898947128), ('3', 0.12515925906184908), ('8', 0.12489091845155219), ('6', 0.1245383468146311), ('1', 0.12441141527606933), ('2', 0.12403713327181662), ('11', 0.12370569451525179)] |
[['4', '5', '3', '8', '6', '1', '2', '11']] |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
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