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FINAL_ANSWER=RESULT(var=ANSWER1)
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ANSWER0=VQA(image=LEFT,question='Is the dog eating out of a bowl?')
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ANSWER1=EVAL(expr='{ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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ANSWER0=VQA(image=LEFT,question='How many animals 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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torch.Size([7, 3, 448, 448])
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torch.Size([13, 3, 448, 448])
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question: ['Are there several puppies nestled on straw?'], 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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tensor([1.0000e+00, 2.4097e-09, 2.8173e-09, 1.0607e-08, 6.1524e-12, 3.2799e-11,
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2.7420e-11, 1.4215e-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, 2.4097e-09, 2.8173e-09, 1.0607e-08, 6.1524e-12, 3.2799e-11,
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2.7420e-11, 1.4215e-09], device='cuda:3', grad_fn=<SelectBackward0>)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), False: tensor(2.8173e-09, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-2.8173e-09, device='cuda:3', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=LEFT,question='How many people 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 animals are in the image?'], responses:['2']
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question: ['Is the dog eating out of a bowl?'], responses:['no']
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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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[('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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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: 1860
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860
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question: ['Are both beavers standing up on their hind legs?'], responses:['no']
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question: ['How many people are in the image?'], responses:['1']
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860
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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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[('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([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: 1860
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torch.Size([13, 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: 1860
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860
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tensor([1.0000e+00, 2.5798e-10, 5.3403e-07, 3.7751e-11, 3.3159e-11, 3.0753e-08,
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1.1862e-09, 1.1723e-06], 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, 2.5798e-10, 5.3403e-07, 3.7751e-11, 3.3159e-11, 3.0753e-08,
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1.1862e-09, 1.1723e-06], device='cuda:2', grad_fn=<SelectBackward0>)
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tensor([9.9995e-01, 4.8326e-05, 7.2655e-08, 2.3823e-07, 5.8714e-09, 1.4247e-10,
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2.1265e-09, 6.5225e-11], device='cuda:0', grad_fn=<SoftmaxBackward0>)
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2 *************
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['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9995e-01, 4.8326e-05, 7.2655e-08, 2.3823e-07, 5.8714e-09, 1.4247e-10,
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2.1265e-09, 6.5225e-11], device='cuda:0', grad_fn=<SelectBackward0>)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(2.5798e-10, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.6689e-06, device='cuda:2', grad_fn=<DivBackward0>)}
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(4.8645e-05, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='Does the beagle wear a leash in the image?')
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ANSWER1=EVAL(expr='{ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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ANSWER0=VQA(image=LEFT,question='How many warthogs 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([3, 3, 448, 448])
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torch.Size([7, 3, 448, 448])
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question: ['Does the beagle wear a leash in the image?'], 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([3, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840
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tensor([9.9996e-01, 8.3978e-06, 3.2562e-07, 7.9796e-08, 1.4761e-08, 6.0833e-07,
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3.3214e-05, 3.5060e-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([9.9996e-01, 8.3978e-06, 3.2562e-07, 7.9796e-08, 1.4761e-08, 6.0833e-07,
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3.3214e-05, 3.5060e-09], device='cuda:3', grad_fn=<SelectBackward0>)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(3.2562e-07, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)}
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841
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question: ['How many warthogs are in the image?'], responses:['1']
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840
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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: 3, images per sample: 3.0, dynamic token length: 840
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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841
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tensor([1.0000e+00, 5.3768e-10, 9.6154e-07, 1.3280e-10, 3.2864e-11, 8.1671e-08,
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2.4309e-10, 4.6602e-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([1.0000e+00, 5.3768e-10, 9.6154e-07, 1.3280e-10, 3.2864e-11, 8.1671e-08,
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2.4309e-10, 4.6602e-07], device='cuda:0', grad_fn=<SelectBackward0>)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(5.3768e-10, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.5497e-06, device='cuda:0', grad_fn=<DivBackward0>)}
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tensor([1.0000e+00, 1.7630e-09, 1.1797e-07, 3.5390e-12, 2.0962e-12, 1.7749e-09,
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2.5758e-10, 6.2717e-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, 1.7630e-09, 1.1797e-07, 3.5390e-12, 2.0962e-12, 1.7749e-09,
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