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1.7143e-09, 1.9137e-07], device='cuda:3', grad_fn=<SelectBackward0>)
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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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ζεηζ¦ηεεΈδΈΊ: {True: tensor(9.3748e-10, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1912e-06, device='cuda:3', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='How many pillows are visible 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([1, 3, 448, 448])
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torch.Size([5, 3, 448, 448]) knan debug pixel values shape
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question: ['Are there elephants standing in or beside water?'], 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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question: ['How many pillows are visible 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([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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tensor([9.9909e-01, 2.5337e-07, 1.3854e-08, 5.0072e-10, 3.4486e-09, 3.5936e-08,
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9.1105e-04, 2.4570e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>)
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1 *************
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['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.9909e-01, 2.5337e-07, 1.3854e-08, 5.0072e-10, 3.4486e-09, 3.5936e-08,
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9.1105e-04, 2.4570e-10], device='cuda:3', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0009, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9991, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)}
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question: ['Is there a hyena standing in a field?'], responses:['yes']
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
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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: 7, images per sample: 7.0, dynamic token length: 1862
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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: 1861
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tensor([9.9989e-01, 8.4809e-05, 9.8174e-06, 1.8923e-05, 1.6892e-07, 7.3639e-09,
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4.6907e-08, 1.0202e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>)
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2 *************
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['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9989e-01, 8.4809e-05, 9.8174e-06, 1.8923e-05, 1.6892e-07, 7.3639e-09,
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4.6907e-08, 1.0202e-09], device='cuda:1', grad_fn=<SelectBackward0>)
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dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9999, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0001, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)}
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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([7, 3, 448, 448])
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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([9.9844e-01, 9.5101e-07, 1.8157e-05, 1.3838e-04, 6.6701e-04, 4.6565e-04,
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8.9582e-05, 1.8064e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.9844e-01, 9.5101e-07, 1.8157e-05, 1.3838e-04, 6.6701e-04, 4.6565e-04,
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8.9582e-05, 1.8064e-04], device='cuda:0', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9984, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.8157e-05, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='Is there a hand in the image?')
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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 warthogs are in the image?'], responses:['11']
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[('11', 0.12740768001087358), ('10', 0.12548679249075975), ('12', 0.12538137681693887), ('9', 0.12485855662563465), ('8', 0.12469919178932766), ('13', 0.12431757055023795), ('7', 0.12396146028399917), ('14', 0.1238873714322284)]
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[['11', '10', '12', '9', '8', '13', '7', '14']]
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question: ['Is there a hand 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([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: 324
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324
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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: 325
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
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tensor([1.0000e+00, 6.7332e-09, 9.3167e-07, 2.5932e-08, 1.1506e-07, 1.5930e-06,
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4.3555e-08, 3.7848e-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, 6.7332e-09, 9.3167e-07, 2.5932e-08, 1.1506e-07, 1.5930e-06,
|
4.3555e-08, 3.7848e-07], device='cuda:0', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(6.7332e-09, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(3.0994e-06, device='cuda:0', grad_fn=<DivBackward0>)}
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tensor([9.6791e-01, 6.5215e-03, 1.9886e-03, 3.0802e-03, 1.3535e-04, 1.2839e-03,
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1.8872e-02, 2.0963e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>)
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11 *************
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['11', '10', '12', '9', '8', '13', '7', '14'] tensor([9.6791e-01, 6.5215e-03, 1.9886e-03, 3.0802e-03, 1.3535e-04, 1.2839e-03,
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1.8872e-02, 2.0963e-04], device='cuda:1', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)}
|
tensor([1.0000e+00, 4.2459e-09, 7.3338e-11, 1.8619e-08, 2.8799e-10, 5.2005e-11,
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3.2792e-11, 7.2261e-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, 4.2459e-09, 7.3338e-11, 1.8619e-08, 2.8799e-10, 5.2005e-11,
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3.2792e-11, 7.2261e-09], device='cuda:2', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(7.3338e-11, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-7.3338e-11, device='cuda:2', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=RIGHT,question='How many birds are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} == 1')
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FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([7, 3, 448, 448])
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question: ['How many birds are in the image?'], responses:['5']
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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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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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tensor([9.8605e-01, 1.7970e-08, 1.3868e-02, 7.0752e-05, 8.9520e-09, 1.4760e-05,
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2.3219e-08, 8.1646e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>)
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5 *************
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