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ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.7886e-10, 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>)} |
ANSWER0=VQA(image=LEFT,question='Are the mittens in the image made of a solid color?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
question: ['Is there a swoop design visible on the shoe on the right?'], responses:['no'] |
question: ['Is someone touching a vending machine in the image?'], responses:['yes'] |
question: ['How many people are in the image?'], responses:['0'] |
[('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']] |
[('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']] |
[('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']] |
question: ['Are the mittens in the image made of a solid color?'], 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([1, 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: 1866 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 |
tensor([1.0000e+00, 4.4301e-09, 1.2238e-08, 3.0986e-09, 3.3340e-09, 1.0754e-10, |
1.2155e-11, 6.6431e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 4.4301e-09, 1.2238e-08, 3.0986e-09, 3.3340e-09, 1.0754e-10, |
1.2155e-11, 6.6431e-09], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.2238e-08, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.2238e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
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: 1867 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
tensor([1.0000e+00, 8.9268e-07, 1.6140e-07, 1.0161e-10, 1.9613e-06, 3.4327e-08, |
4.2753e-07, 1.2378e-06], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
0 ************* |
['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle'] tensor([1.0000e+00, 8.9268e-07, 1.6140e-07, 1.0161e-10, 1.9613e-06, 3.4327e-08, |
4.2753e-07, 1.2378e-06], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 1.3574e-07, 1.7792e-07, 1.4472e-10, 7.3415e-11, 1.2547e-08, |
9.4449e-10, 1.0765e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.3574e-07, 1.7792e-07, 1.4472e-10, 7.3415e-11, 1.2547e-08, |
9.4449e-10, 1.0765e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 2.0665e-08, 4.3282e-11, 5.6872e-08, 1.3062e-10, 8.8649e-10, |
5.2509e-11, 4.2933e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.0665e-08, 4.3282e-11, 5.6872e-08, 1.3062e-10, 8.8649e-10, |
5.2509e-11, 4.2933e-09], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(4.6492e-06, device='cuda:1', grad_fn=<DivBackward0>)} |
{True: tensor(1.3574e-07, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(3.5763e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many seals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(4.3282e-11, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1917e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many animals are standing in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
ANSWER0=VQA(image=RIGHT,question='How many machines are lined up in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 4') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many seals 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([3, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
tensor([1.0000e+00, 1.4960e-08, 1.3527e-08, 1.2225e-08, 1.3178e-10, 2.3374e-09, |
6.7961e-10, 1.4331e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 1.4960e-08, 1.3527e-08, 1.2225e-08, 1.3178e-10, 2.3374e-09, |
6.7961e-10, 1.4331e-09], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:0', grad_fn=<DivBackward0>), False: tensor(4.5294e-08, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
question: ['How many animals are standing in the image?'], responses:['2'] |
question: ['How many machines are lined up 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']] |
[('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([13, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([9.9999e-01, 6.9623e-06, 2.3588e-08, 8.6777e-09, 2.7953e-09, 4.9873e-10, |
3.0941e-09, 2.6617e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9999e-01, 6.9623e-06, 2.3588e-08, 8.6777e-09, 2.7953e-09, 4.9873e-10, |
3.0941e-09, 2.6617e-10], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(8.6777e-09, 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>)} |
tensor([9.9988e-01, 8.4808e-05, 3.3211e-05, 6.1049e-09, 9.6245e-08, 9.1838e-08, |
1.5868e-07, 2.0893e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
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