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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 |
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: ['Is there an animal sitting in a bowl in the image?'], responses:['yes'] |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
[('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, 6.7178e-10, 1.7870e-10, 2.6102e-10, 2.8535e-10, 1.1293e-08, |
6.1535e-09, 3.2869e-10], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 6.7178e-10, 1.7870e-10, 2.6102e-10, 2.8535e-10, 1.1293e-08, |
6.1535e-09, 3.2869e-10], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.9172e-08, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many pillows are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
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 pillows 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: 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 |
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 |
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, 2.8737e-07, 1.2825e-08, 2.3321e-06, 1.6131e-09, 7.4504e-10, |
1.8840e-09, 2.8809e-10], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 2.8737e-07, 1.2825e-08, 2.3321e-06, 1.6131e-09, 7.4504e-10, |
1.8840e-09, 2.8809e-10], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.3321e-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>)} |
question: ['Is someone holding up the dog?'], responses:['no'] |
question: ['How many hamsters are in the image?'], responses:['5'] |
[('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']] |
[('5', 0.12793059870235002), ('8', 0.12539646467821697), ('4', 0.12509737486793587), ('6', 0.12470234839853608), ('3', 0.12467331676337925), ('7', 0.12441254825093238), ('11', 0.12401867309944531), ('9', 0.12376867523920407)] |
[['5', '8', '4', '6', '3', '7', '11', '9']] |
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, 3.4943e-09, 3.8047e-11, 9.9926e-08, 2.0738e-10, 1.5404e-10, |
2.2566e-11, 6.0889e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 3.4943e-09, 3.8047e-11, 9.9926e-08, 2.0738e-10, 1.5404e-10, |
2.2566e-11, 6.0889e-09], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(3.8047e-11, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1917e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Does the dog have a hat with a brim?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([13, 3, 448, 448]) |
question: ['Does the dog have a hat with a brim?'], 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([13, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 4.7450e-10, 3.8054e-07, 3.0098e-11, 6.6680e-10, 1.7601e-08, |
5.4828e-10, 2.6985e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 4.7450e-10, 3.8054e-07, 3.0098e-11, 6.6680e-10, 1.7601e-08, |
5.4828e-10, 2.6985e-07], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(4.7450e-10, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='What color is the drum?') |
ANSWER1=EVAL(expr='{ANSWER0} == "white"') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
tensor([9.6314e-01, 3.0385e-06, 2.1549e-04, 3.6381e-02, 2.7664e-10, 2.4012e-04, |
9.0844e-06, 1.3348e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
5 ************* |
['5', '8', '4', '6', '3', '7', '11', '9'] tensor([9.6314e-01, 3.0385e-06, 2.1549e-04, 3.6381e-02, 2.7664e-10, 2.4012e-04, |
9.0844e-06, 1.3348e-05], 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>)} |
torch.Size([13, 3, 448, 448]) |
ANSWER0=VQA(image=RIGHT,question='Does the bookshelf frame an arch?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['Does the bookshelf frame an arch?'], 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([7, 3, 448, 448]) knan debug pixel values shape |
question: ['What color is the drum?'], responses:['white'] |
[('white', 0.12741698904857263), ('black', 0.12562195821587463), ('purple', 0.12482758531934457), ('orange', 0.12467593918870701), ('maroon', 0.12456097552653009), ('color', 0.12448461429606533), ('brown', 0.12421598902969112), ('dark', 0.12419594937521464)] |
[['white', 'black', 'purple', 'orange', 'maroon', 'color', 'brown', 'dark']] |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 2.3485e-08, 8.0546e-11, 5.9611e-08, 7.4918e-10, 5.3768e-10, |
1.2097e-10, 2.0568e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.3485e-08, 8.0546e-11, 5.9611e-08, 7.4918e-10, 5.3768e-10, |
1.2097e-10, 2.0568e-08], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<UnbindBackward0>), False: tensor(8.0546e-11, device='cuda:2', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(1.1913e-07, device='cuda:2', grad_fn=<SubBackward0>)} |
tensor([9.9962e-01, 9.6782e-10, 3.7998e-04, 1.6080e-09, 3.6213e-12, 5.2173e-13, |
1.8048e-11, 3.1261e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.9962e-01, 9.6782e-10, 3.7998e-04, 1.6080e-09, 3.6213e-12, 5.2173e-13, |
1.8048e-11, 3.1261e-09], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9996, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0004, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.4686e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
tensor([9.8849e-01, 1.9141e-04, 1.0389e-06, 7.0983e-06, 3.4077e-04, 7.7501e-08, |
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