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['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.2375e-01, 2.4621e-02, 5.1608e-03, 4.3206e-02, 1.7829e-03, 7.8809e-04,
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6.3465e-04, 5.6315e-05], device='cuda:1', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9237, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0763, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='How many boars are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} >= 3')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([3, 3, 448, 448])
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question: ['What color is the dog in the image?'], responses:['tan']
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question: ['How many windows are on the rusted out bus?'], responses:['6']
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[('tan', 0.12670198546574601), ('pear', 0.12488736917128618), ('pan', 0.12483632219296452), ('broom', 0.12479636744714646), ('chimney', 0.12479439652246849), ('doll', 0.12468410687193951), ('hood', 0.12466784352901412), ('sauce', 0.12463160879943475)]
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[['tan', 'pear', 'pan', 'broom', 'chimney', 'doll', 'hood', 'sauce']]
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[('6', 0.12794147189263105), ('8', 0.12539492259598553), ('12', 0.12539359088927945), ('5', 0.12471292164321114), ('4', 0.12443617393590153), ('1', 0.12417386497855347), ('11', 0.12398049124372558), ('3', 0.12396656282071232)]
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[['6', '8', '12', '5', '4', '1', '11', '3']]
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question: ['Is the dog running in the image?'], responses:['yes']
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[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)]
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[['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate']]
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question: ['How many boars are in the image?'], responses:['4']
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torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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[('4', 0.12804651361935848), ('5', 0.12521071898947128), ('3', 0.12515925906184908), ('8', 0.12489091845155219), ('6', 0.1245383468146311), ('1', 0.12441141527606933), ('2', 0.12403713327181662), ('11', 0.12370569451525179)]
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[['4', '5', '3', '8', '6', '1', '2', '11']]
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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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torch.Size([3, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
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tensor([0.2305, 0.2172, 0.1897, 0.0730, 0.1370, 0.0353, 0.0896, 0.0276],
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device='cuda:1', grad_fn=<SoftmaxBackward0>)
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4 *************
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['4', '5', '3', '8', '6', '1', '2', '11'] tensor([0.2305, 0.2172, 0.1897, 0.0730, 0.1370, 0.0353, 0.0896, 0.0276],
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device='cuda:1', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8751, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.1249, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)}
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
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tensor([8.8948e-01, 2.0285e-02, 8.8020e-02, 1.0149e-03, 8.6437e-05, 3.3712e-04,
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1.7915e-05, 7.5412e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.8948e-01, 2.0285e-02, 8.8020e-02, 1.0149e-03, 8.6437e-05, 3.3712e-04,
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1.7915e-05, 7.5412e-04], device='cuda:3', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0880, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.8895, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0225, device='cuda:3', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=LEFT,question='Is there a bird in the image?')
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ANSWER1=EVAL(expr='{ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([7, 3, 448, 448])
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
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question: ['Is there a bird in the image?'], responses:['yes']
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[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)]
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[['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate']]
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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
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tensor([9.4078e-01, 9.4381e-04, 2.3036e-03, 2.6643e-03, 3.1279e-02, 2.9316e-03,
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1.5024e-04, 1.8946e-02], device='cuda:2', grad_fn=<SoftmaxBackward0>)
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tan *************
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['tan', 'pear', 'pan', 'broom', 'chimney', 'doll', 'hood', 'sauce'] tensor([9.4078e-01, 9.4381e-04, 2.3036e-03, 2.6643e-03, 3.1279e-02, 2.9316e-03,
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1.5024e-04, 1.8946e-02], device='cuda:2', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:2', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=LEFT,question='How many children are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} >= 2')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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tensor([0.1803, 0.1696, 0.1356, 0.1215, 0.1378, 0.0458, 0.1239, 0.0855],
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device='cuda:0', grad_fn=<SoftmaxBackward0>)
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6 *************
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['6', '8', '12', '5', '4', '1', '11', '3'] tensor([0.1803, 0.1696, 0.1356, 0.1215, 0.1378, 0.0458, 0.1239, 0.0855],
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device='cuda:0', grad_fn=<SelectBackward0>)
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torch.Size([13, 3, 448, 448])
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.1356, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.8644, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=LEFT,question='How many sled dogs are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} == 4')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([7, 3, 448, 448])
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question: ['How many sled dogs are in the image?'], responses:['5']
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[('5', 0.12793059870235002), ('8', 0.12539646467821697), ('4', 0.12509737486793587), ('6', 0.12470234839853608), ('3', 0.12467331676337925), ('7', 0.12441254825093238), ('11', 0.12401867309944531), ('9', 0.12376867523920407)]
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[['5', '8', '4', '6', '3', '7', '11', '9']]
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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
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question: ['How many children are in the image?'], responses:['0']
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[('0', 0.13077743594303964), ('circles', 0.12449813349255197), ('maroon', 0.12428926693968681), ('large', 0.1242263466991631), ('rooster', 0.12409315512763705), ('nuts', 0.12408018414184876), ('beige', 0.1240288472550799), ('bottle', 0.12400663040099273)]
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[['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle']]
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tensor([9.0677e-01, 2.1249e-02, 6.9950e-02, 1.4237e-03, 5.5222e-05, 1.9592e-04,
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3.8701e-05, 3.1259e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.0677e-01, 2.1249e-02, 6.9950e-02, 1.4237e-03, 5.5222e-05, 1.9592e-04,
|
3.8701e-05, 3.1259e-04], device='cuda:3', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9068, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0700, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0233, device='cuda:3', grad_fn=<DivBackward0>)}
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
|
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
|
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
|
tensor([0.2962, 0.0798, 0.1440, 0.2622, 0.0354, 0.1245, 0.0138, 0.0442],
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device='cuda:0', grad_fn=<SoftmaxBackward0>)
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5 *************
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['5', '8', '4', '6', '3', '7', '11', '9'] tensor([0.2962, 0.0798, 0.1440, 0.2622, 0.0354, 0.1245, 0.0138, 0.0442],
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device='cuda:0', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.1440, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.8560, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='How many Canadian geese are in the image?')
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