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torch.Size([7, 3, 448, 448])
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torch.Size([13, 3, 448, 448])
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torch.Size([13, 3, 448, 448])
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question: ['Is there an animal laying bleeding 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([3, 3, 448, 448]) knan debug pixel values shape
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question: ['Is the stairway bordered with glass panels?'], 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([1.0000e+00, 6.4614e-09, 9.7920e-11, 1.6798e-08, 4.6597e-11, 2.1724e-10,
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6.6140e-11, 1.5808e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 6.4614e-09, 9.7920e-11, 1.6798e-08, 4.6597e-11, 2.1724e-10,
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6.6140e-11, 1.5808e-09], device='cuda:3', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), False: tensor(9.7920e-11, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-9.7920e-11, device='cuda:3', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=LEFT,question='How many syringes 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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torch.Size([1, 3, 448, 448])
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question: ['Is there a silver lamp with white lights in the image?'], responses:['no']
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question: ['How many frames are on the wall 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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[('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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question: ['How many syringes 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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torch.Size([1, 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([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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tensor([1.0000e+00, 8.7927e-10, 3.1119e-10, 6.5873e-10, 3.6336e-10, 4.2750e-08,
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5.2943e-09, 1.0499e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>)
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1 *************
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['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 8.7927e-10, 3.1119e-10, 6.5873e-10, 3.6336e-10, 4.2750e-08,
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5.2943e-09, 1.0499e-09], device='cuda:3', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(0., device='cuda:3', 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([1.0000e+00, 3.5817e-10, 3.7612e-07, 6.4584e-12, 1.0135e-11, 6.6270e-09,
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2.0835e-10, 5.2575e-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, 3.5817e-10, 3.7612e-07, 6.4584e-12, 1.0135e-11, 6.6270e-09,
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2.0835e-10, 5.2575e-07], device='cuda:1', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(3.5817e-10, device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(8.3447e-07, device='cuda:1', grad_fn=<SubBackward0>)}
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ANSWER0=VQA(image=LEFT,question='How many test tubes are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} == 5')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([1, 3, 448, 448])
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question: ['How many test tubes are in the image?'], responses:['δΊ']
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
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[('b', 0.13191356159599515), ('goose', 0.1293021784561415), ('geese', 0.12735223987123176), ('cushion', 0.12364316067995791), ('y', 0.12254057047812728), ('k', 0.12209438419566433), ('am', 0.12163540389422718), ('f', 0.12151850082865487)]
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[['b', 'goose', 'geese', 'cushion', 'y', 'k', 'am', 'f']]
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torch.Size([1, 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([2.2816e-04, 1.1039e-01, 8.0379e-02, 7.3921e-01, 6.7252e-02, 9.7143e-04,
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1.5586e-03, 3.4901e-06], device='cuda:1', grad_fn=<SoftmaxBackward0>)
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cushion *************
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['b', 'goose', 'geese', 'cushion', 'y', 'k', 'am', 'f'] tensor([2.2816e-04, 1.1039e-01, 8.0379e-02, 7.3921e-01, 6.7252e-02, 9.7143e-04,
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1.5586e-03, 3.4901e-06], device='cuda:1', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., 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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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
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tensor([9.9999e-01, 7.4225e-09, 5.9983e-10, 1.2573e-10, 2.4617e-10, 2.1265e-09,
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5.0937e-06, 2.9989e-11], device='cuda:0', grad_fn=<SoftmaxBackward0>)
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1 *************
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['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.9999e-01, 7.4225e-09, 5.9983e-10, 1.2573e-10, 2.4617e-10, 2.1265e-09,
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5.0937e-06, 2.9989e-11], device='cuda:0', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.5283e-09, device='cuda:0', grad_fn=<DivBackward0>), 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=RIGHT,question='How many rodents 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([1.0000e+00, 5.9053e-10, 3.1726e-07, 1.0062e-11, 1.3233e-10, 2.1527e-08,
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1.9239e-09, 7.3011e-07], 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([1.0000e+00, 5.9053e-10, 3.1726e-07, 1.0062e-11, 1.3233e-10, 2.1527e-08,
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1.9239e-09, 7.3011e-07], device='cuda:2', grad_fn=<SelectBackward0>)
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torch.Size([7, 3, 448, 448])
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(5.9053e-10, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.0729e-06, device='cuda:2', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=LEFT,question='How many bags/pencil-cases 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([1, 3, 448, 448])
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question: ['How many bags/pencil-cases are in the image?'], responses:['five']
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[('7 eleven', 0.1264466744091217), ('babies', 0.124977990347662), ('sunrise', 0.12490143984830117), ('eating', 0.1247676656843781), ('feet', 0.12475702323703439), ('candle', 0.12473210928138137), ('light', 0.12472650705175181), ('floating', 0.12469059014036947)]
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[['7 eleven', 'babies', 'sunrise', 'eating', 'feet', 'candle', 'light', 'floating']]
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torch.Size([1, 3, 448, 448]) knan debug pixel values shape
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tensor([3.5221e-09, 2.9608e-01, 2.4145e-01, 6.6749e-05, 4.6096e-01, 2.7013e-04,
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7.4621e-04, 4.2698e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>)
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feet *************
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['7 eleven', 'babies', 'sunrise', 'eating', 'feet', 'candle', 'light', 'floating'] tensor([3.5221e-09, 2.9608e-01, 2.4145e-01, 6.6749e-05, 4.6096e-01, 2.7013e-04,
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7.4621e-04, 4.2698e-04], 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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question: ['How many rodents 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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