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question: ['Is a window shade partially pulled up in the image?'], responses:['yes']
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question: ['Where are the humans in relation to the cows?'], responses:['leading']
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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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[('charging', 0.12510895783242473), ('cutting', 0.12507799144117152), ('setting', 0.12503575193465818), ('scarf', 0.12500572727492312), ('bending', 0.12499361047143344), ('circle', 0.12496316186509192), ('blending', 0.12491269364537502), ('decorative', 0.124902105534922)]
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[['charging', 'cutting', 'setting', 'scarf', 'bending', 'circle', 'blending', 'decorative']]
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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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tensor([1.0000e+00, 4.5991e-10, 4.6852e-07, 5.2114e-10, 8.5631e-09, 8.7472e-08,
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1.3466e-08, 3.7538e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>)
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no *************
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['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 4.5991e-10, 4.6852e-07, 5.2114e-10, 8.5631e-09, 8.7472e-08,
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1.3466e-08, 3.7538e-07], device='cuda:1', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(4.5991e-10, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(9.5367e-07, device='cuda:1', grad_fn=<DivBackward0>)}
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question: ['Is the fragrance bottle a different color than its box?'], responses:['no']
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ANSWER0=VQA(image=RIGHT,question='Is the hyena baring its teeth?')
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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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[('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)]
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[['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock']]
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torch.Size([13, 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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question: ['Is the hyena baring its teeth?'], 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: 3400
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tensor([1.0000e+00, 5.1794e-09, 1.1628e-10, 1.4812e-08, 1.0568e-10, 9.1463e-10,
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6.8218e-11, 2.2892e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 5.1794e-09, 1.1628e-10, 1.4812e-08, 1.0568e-10, 9.1463e-10,
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6.8218e-11, 2.2892e-09], device='cuda:2', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.1628e-10, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1628e-10, device='cuda:2', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=LEFT,question='How many chimpanzees are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} == 1')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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tensor([0.3295, 0.0287, 0.0071, 0.0236, 0.5066, 0.0101, 0.0907, 0.0037],
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device='cuda:3', grad_fn=<SoftmaxBackward0>)
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bending *************
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['charging', 'cutting', 'setting', 'scarf', 'bending', 'circle', 'blending', 'decorative'] tensor([0.3295, 0.0287, 0.0071, 0.0236, 0.5066, 0.0101, 0.0907, 0.0037],
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device='cuda:3', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:3', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='Is the dog on the right white with black spots?')
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FINAL_ANSWER=RESULT(var=ANSWER0)
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torch.Size([13, 3, 448, 448])
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torch.Size([13, 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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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
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tensor([1.0000e+00, 1.5816e-08, 9.2180e-10, 5.7981e-08, 2.9856e-10, 2.9067e-09,
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6.8320e-10, 9.7236e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.5816e-08, 9.2180e-10, 5.7981e-08, 2.9856e-10, 2.9067e-09,
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6.8320e-10, 9.7236e-09], device='cuda:1', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(9.2180e-10, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1829e-07, device='cuda:1', grad_fn=<DivBackward0>)}
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question: ['How many chimpanzees are in the image?'], responses:['1']
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question: ['Is the dog on the right white with black spots?'], responses:['yes']
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[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)]
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[['1', '3', '4', '8', '6', '12', '2', '47']]
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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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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
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torch.Size([13, 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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tensor([9.9992e-01, 7.4846e-05, 7.1127e-08, 5.9727e-12, 8.5006e-12, 1.8069e-10,
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3.6945e-11, 1.0488e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>)
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no *************
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['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.9992e-01, 7.4846e-05, 7.1127e-08, 5.9727e-12, 8.5006e-12, 1.8069e-10,
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3.6945e-11, 1.0488e-07], device='cuda:0', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(7.4846e-05, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(0.9999, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(2.3842e-07, device='cuda:0', grad_fn=<SubBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='Does the image contain a dung ball?')
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FINAL_ANSWER=RESULT(var=ANSWER0)
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torch.Size([7, 3, 448, 448])
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question: ['Does the image contain a dung ball?'], 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: 7, images per sample: 7.0, dynamic token length: 1861
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
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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: 1861
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
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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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tensor([1.0000e+00, 4.2940e-09, 2.9229e-11, 3.4007e-08, 8.9531e-10, 5.3769e-10,
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3.2426e-11, 7.7395e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 4.2940e-09, 2.9229e-11, 3.4007e-08, 8.9531e-10, 5.3769e-10,
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3.2426e-11, 7.7395e-09], device='cuda:0', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(2.9229e-11, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-2.9229e-11, device='cuda:0', grad_fn=<SubBackward0>)}
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tensor([1.0000e+00, 2.8780e-10, 8.5074e-11, 3.3122e-10, 1.0251e-10, 2.5844e-08,
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3.6458e-09, 3.7569e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>)
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1 *************
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['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 2.8780e-10, 8.5074e-11, 3.3122e-10, 1.0251e-10, 2.5844e-08,
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3.6458e-09, 3.7569e-10], device='cuda:2', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(3.0672e-08, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)}
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