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tensor([0.2618, 0.1527, 0.1905, 0.1720, 0.0411, 0.0248, 0.0770, 0.0802],
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device='cuda:0', grad_fn=<SoftmaxBackward0>)
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15 *************
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['15', '14', '13', '16', '29', '35', '22', '21'] tensor([0.2618, 0.1527, 0.1905, 0.1720, 0.0411, 0.0248, 0.0770, 0.0802],
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device='cuda:0', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), False: tensor(1.0000, 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=LEFT,question='How many cheetahs 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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torch.Size([7, 3, 448, 448])
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tensor([9.1000e-01, 3.1138e-02, 1.0761e-02, 4.2554e-02, 2.9877e-03, 1.4103e-03,
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1.0647e-03, 8.2916e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>)
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2 *************
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['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.1000e-01, 3.1138e-02, 1.0761e-02, 4.2554e-02, 2.9877e-03, 1.4103e-03,
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1.0647e-03, 8.2916e-05], device='cuda:1', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9100, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0900, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=LEFT,question='How many elephants 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([7, 3, 448, 448])
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question: ['How many cheetahs are in the image?'], responses:['2']
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[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)]
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[['2', '3', '4', '1', '5', '8', '7', '29']]
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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: 1863
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863
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question: ['How many elephants are in the image?'], responses:['1']
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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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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863
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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: 1863
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863
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tensor([6.9668e-01, 6.0536e-02, 1.1193e-02, 2.2481e-01, 4.1176e-03, 1.1082e-03,
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1.4689e-03, 7.8859e-05], device='cuda:2', grad_fn=<SoftmaxBackward0>)
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2 *************
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['2', '3', '4', '1', '5', '8', '7', '29'] tensor([6.9668e-01, 6.0536e-02, 1.1193e-02, 2.2481e-01, 4.1176e-03, 1.1082e-03,
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1.4689e-03, 7.8859e-05], device='cuda:2', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6967, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.3033, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:2', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='Is the dog running?')
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ANSWER1=EVAL(expr='not {ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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tensor([9.2690e-01, 2.0475e-02, 9.9795e-03, 4.1547e-03, 5.5080e-03, 2.9236e-03,
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2.9795e-02, 2.6662e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>)
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1 *************
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['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.2690e-01, 2.0475e-02, 9.9795e-03, 4.1547e-03, 5.5080e-03, 2.9236e-03,
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2.9795e-02, 2.6662e-04], device='cuda:3', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9269, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0731, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:3', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='Is the egg in the image brown?')
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FINAL_ANSWER=RESULT(var=ANSWER0)
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torch.Size([1, 3, 448, 448])
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torch.Size([7, 3, 448, 448])
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863
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question: ['Is the egg in the image brown?'], 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([1, 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: 1863
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tensor([7.5727e-01, 1.1603e-01, 2.3570e-02, 9.0442e-02, 8.1534e-03, 1.9956e-03,
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2.4074e-03, 1.3317e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>)
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2 *************
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['2', '3', '4', '1', '5', '8', '7', '29'] tensor([7.5727e-01, 1.1603e-01, 2.3570e-02, 9.0442e-02, 8.1534e-03, 1.9956e-03,
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2.4074e-03, 1.3317e-04], device='cuda:0', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9096, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0904, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:0', grad_fn=<DivBackward0>)}
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tensor([6.9807e-01, 2.2282e-02, 2.7336e-01, 3.0176e-03, 2.3519e-04, 6.7620e-04,
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6.5835e-05, 2.2852e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.9807e-01, 2.2282e-02, 2.7336e-01, 3.0176e-03, 2.3519e-04, 6.7620e-04,
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6.5835e-05, 2.2852e-03], device='cuda:3', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6981, device='cuda:3', grad_fn=<UnbindBackward0>), False: tensor(0.2734, device='cuda:3', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0286, device='cuda:3', grad_fn=<SubBackward0>)}
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question: ['Is the dog running?'], responses:['no']
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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([7, 3, 448, 448]) knan debug pixel values shape
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tensor([9.3881e-01, 1.1101e-02, 4.4839e-03, 1.4494e-03, 1.7004e-03, 1.1555e-03,
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4.1248e-02, 5.4257e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>)
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1 *************
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['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.3881e-01, 1.1101e-02, 4.4839e-03, 1.4494e-03, 1.7004e-03, 1.1555e-03,
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4.1248e-02, 5.4257e-05], device='cuda:1', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0111, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9889, 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='Is the seal facing right?')
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FINAL_ANSWER=RESULT(var=ANSWER0)
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torch.Size([7, 3, 448, 448])
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question: ['Is the seal facing right?'], 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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tensor([9.2335e-01, 7.5793e-02, 5.8969e-05, 5.6297e-05, 3.3855e-05, 3.3984e-04,
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2.1867e-04, 1.4607e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>)
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no *************
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['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.2335e-01, 7.5793e-02, 5.8969e-05, 5.6297e-05, 3.3855e-05, 3.3984e-04,
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2.1867e-04, 1.4607e-04], device='cuda:2', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9234, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.0758, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0009, device='cuda:2', grad_fn=<DivBackward0>)}
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tensor([6.0207e-01, 2.2643e-02, 3.7165e-01, 8.9989e-04, 1.3683e-04, 1.6168e-03,
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1.0561e-04, 8.6849e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.0207e-01, 2.2643e-02, 3.7165e-01, 8.9989e-04, 1.3683e-04, 1.6168e-03,
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1.0561e-04, 8.6849e-04], device='cuda:1', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6021, device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(0.3717, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0263, device='cuda:1', grad_fn=<SubBackward0>)}
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