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question: ['Is there a human hand near a laptop in the image?'], responses:['yes']
question: ['How many wild dogs are in the image?'], responses:['1']
[('7 eleven', 0.12650899275575006), ('4', 0.125210025275264), ('first', 0.12483048280083887), ('3', 0.12473532336671392), ('5', 0.1247268629491862), ('dark', 0.12470563072493092), ('forward', 0.12466964370422237), ('bag', 0.12461303842309367)]
[['7 eleven', '4', 'first', '3', '5', 'dark', 'forward', 'bag']]
[('biking', 0.12639990046765587), ('geese', 0.1262789403477572), ('cushion', 0.1253965842661667), ('bulldog', 0.1252365705078606), ('striped', 0.12499404846420245), ('floral', 0.12444127054742124), ('stove', 0.12381223353082338), ('dodgers', 0.12344045186811266)]
[['biking', 'geese', 'cushion', 'bulldog', 'striped', 'floral', 'stove', 'dodgers']]
[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)]
[['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate']]
[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)]
[['1', '3', '4', '8', '6', '12', '2', '47']]
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397
tensor([2.6006e-14, 9.9927e-01, 2.9115e-06, 6.9250e-04, 2.4756e-05, 5.7856e-06,
5.1920e-06, 1.3553e-06], device='cuda:0', grad_fn=<SoftmaxBackward0>)
4 *************
['7 eleven', '4', 'first', '3', '5', 'dark', 'forward', 'bag'] tensor([2.6006e-14, 9.9927e-01, 2.9115e-06, 6.9250e-04, 2.4756e-05, 5.7856e-06,
5.1920e-06, 1.3553e-06], device='cuda:0', grad_fn=<SelectBackward0>)
tensor([1.4400e-04, 5.2830e-03, 7.3954e-02, 5.8369e-01, 1.5219e-01, 1.5959e-01,
1.7848e-02, 7.3022e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>)
bulldog *************
['biking', 'geese', 'cushion', 'bulldog', 'striped', 'floral', 'stove', 'dodgers'] tensor([1.4400e-04, 5.2830e-03, 7.3954e-02, 5.8369e-01, 1.5219e-01, 1.5959e-01,
1.7848e-02, 7.3022e-03], device='cuda:1', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.9993, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.5378e-05, device='cuda:0', grad_fn=<DivBackward0>)}
tensor([1.0000e+00, 5.2114e-10, 7.8989e-11, 2.1554e-10, 1.2280e-10, 3.0934e-09,
6.9728e-09, 2.7939e-11], device='cuda:2', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 5.2114e-10, 7.8989e-11, 2.1554e-10, 1.2280e-10, 3.0934e-09,
6.9728e-09, 2.7939e-11], device='cuda:2', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {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>)}
ANSWER0=VQA(image=RIGHT,question='How many zebras are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 3')
FINAL_ANSWER=RESULT(var=ANSWER1)
tensor([1.0000e+00, 2.0633e-08, 4.5729e-09, 5.5665e-07, 2.5696e-09, 4.7923e-09,
9.6043e-10, 1.2385e-08], device='cuda:3', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.0633e-08, 4.5729e-09, 5.5665e-07, 2.5696e-09, 4.7923e-09,
9.6043e-10, 1.2385e-08], device='cuda:3', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.1033e-08, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)}
torch.Size([3, 3, 448, 448])
ANSWER0=VQA(image=LEFT,question='How many dogs are sitting on the ground?')
ANSWER1=EVAL(expr='{ANSWER0} == 3')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(4.5729e-09, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9147e-07, device='cuda:3', grad_fn=<DivBackward0>)}
torch.Size([3, 3, 448, 448])
ANSWER0=VQA(image=RIGHT,question='Is there a black horse in the image?')
ANSWER1=RESULT(var=ANSWER0)
torch.Size([13, 3, 448, 448])
question: ['How many animals are in the image?'], responses:['ε››']
question: ['How many dogs are sitting on the ground?'], responses:['3']
[('geese', 0.12791273653846358), ('cushion', 0.12632164867635856), ('biking', 0.12559214056053666), ('bulldog', 0.12532071672327474), ('striped', 0.12486304389654934), ('goose', 0.12402122964730407), ('vegetable', 0.12318440383239601), ('dodgers', 0.12278408012511692)]
[['geese', 'cushion', 'biking', 'bulldog', 'striped', 'goose', 'vegetable', 'dodgers']]
[('3', 0.12809209985493852), ('4', 0.12520382509374006), ('1', 0.1251059160028928), ('5', 0.12483070991268265), ('8', 0.12458076282181878), ('2', 0.12413212281858195), ('6', 0.1241125313968017), ('12', 0.12394203209854344)]
[['3', '4', '1', '5', '8', '2', '6', '12']]
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
question: ['How many zebras are in the image?'], responses:['1']
[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)]
[['1', '3', '4', '8', '6', '12', '2', '47']]
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
tensor([9.8033e-03, 3.7348e-02, 1.8177e-05, 4.7223e-01, 8.4355e-02, 1.6986e-02,
3.7779e-01, 1.4775e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>)
bulldog *************
['geese', 'cushion', 'biking', 'bulldog', 'striped', 'goose', 'vegetable', 'dodgers'] tensor([9.8033e-03, 3.7348e-02, 1.8177e-05, 4.7223e-01, 8.4355e-02, 1.6986e-02,
3.7779e-01, 1.4775e-03], device='cuda:1', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {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>)}
tensor([1.0000e+00, 2.3403e-07, 4.5498e-07, 3.5492e-10, 4.3950e-11, 4.6329e-07,
1.5349e-10, 7.0647e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>)
3 *************
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([1.0000e+00, 2.3403e-07, 4.5498e-07, 3.5492e-10, 4.3950e-11, 4.6329e-07,
1.5349e-10, 7.0647e-09], device='cuda:2', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.1599e-06, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)}
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
question: ['Is there a black horse in the image?'], responses:['yes']
[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)]
[['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate']]
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
tensor([1.0000e+00, 2.2067e-10, 1.8398e-11, 6.6765e-11, 5.1986e-11, 2.8132e-09,
5.4304e-09, 3.6126e-11], device='cuda:0', grad_fn=<SoftmaxBackward0>)
1 *************