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Registering RESULT step
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Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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ANSWER0=VQA(image=RIGHT,question='Is there at least one person in a dark red graduation gown with black stripes on the sleeves?')
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ANSWER1=EVAL(expr='{ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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ANSWER0=VQA(image=RIGHT,question='How many shades of lipstick are presented in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} == 6')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([1, 3, 448, 448])
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torch.Size([3, 3, 448, 448])
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ANSWER0=VQA(image=RIGHT,question='How many dogs 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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ANSWER0=VQA(image=RIGHT,question='Does the image contain a human child playing a saxophone?')
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FINAL_ANSWER=RESULT(var=ANSWER0)
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torch.Size([5, 3, 448, 448])
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torch.Size([13, 3, 448, 448])
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question: ['How many shades of lipstick are presented 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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question: ['Is there at least one person in a dark red graduation gown with black stripes on the sleeves?'], 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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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848
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question: ['Does the image contain a human child playing a saxophone?'], responses:['no']
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851
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tensor([5.6923e-07, 3.1282e-01, 3.2820e-01, 2.5961e-04, 3.5580e-01, 1.5186e-04,
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2.1406e-03, 6.2690e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>)
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feet *************
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['7 eleven', 'babies', 'sunrise', 'eating', 'feet', 'candle', 'light', 'floating'] tensor([5.6923e-07, 3.1282e-01, 3.2820e-01, 2.5961e-04, 3.5580e-01, 1.5186e-04,
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2.1406e-03, 6.2690e-04], device='cuda:1', grad_fn=<SelectBackward0>)
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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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ๆๅ็ๆฆ็ๅๅธไธบ: {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: 3, images per sample: 3.0, dynamic token length: 848
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ANSWER0=VQA(image=LEFT,question='How many dogs 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([5, 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: 849
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849
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tensor([1.0000e+00, 1.4208e-08, 2.1317e-06, 1.4482e-08, 1.2214e-08, 6.4111e-10,
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7.6660e-11, 3.5121e-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, 1.4208e-08, 2.1317e-06, 1.4482e-08, 1.2214e-08, 6.4111e-10,
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7.6660e-11, 3.5121e-09], device='cuda:0', grad_fn=<SelectBackward0>)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(2.1317e-06, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.4105e-08, device='cuda:0', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='Does the hog on the right have its mouth on the ground?')
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ANSWER1=EVAL(expr='{ANSWER0}')
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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 dogs are in the image?'], responses:['5']
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question: ['How many dogs are in the image?'], responses:['2']
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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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[('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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question: ['Does the hog on the right have its mouth on the ground?'], 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([1, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329
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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329
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torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330
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tensor([1.0000e+00, 3.8507e-09, 1.5134e-07, 4.2026e-12, 8.3517e-13, 1.0878e-09,
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1.6991e-10, 1.4763e-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, 3.8507e-09, 1.5134e-07, 4.2026e-12, 8.3517e-13, 1.0878e-09,
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1.6991e-10, 1.4763e-07], device='cuda:0', grad_fn=<SelectBackward0>)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(3.8507e-09, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.3842e-07, device='cuda:0', grad_fn=<DivBackward0>)}
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tensor([1.0000e+00, 9.1463e-10, 2.3875e-07, 8.3754e-11, 1.0716e-09, 5.1189e-08,
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1.2362e-09, 4.4880e-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, 9.1463e-10, 2.3875e-07, 8.3754e-11, 1.0716e-09, 5.1189e-08,
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1.2362e-09, 4.4880e-07], device='cuda:2', grad_fn=<SelectBackward0>)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(9.1463e-10, device='cuda:2', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(7.1526e-07, device='cuda:2', grad_fn=<SubBackward0>)}
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ANSWER0=VQA(image=LEFT,question='How many water buffaloes 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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