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ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['What are the sled dogs doing?'], responses:['walk'] |
question: ['Is the image of two hands wearing turquoise fingerless mittens?'], responses:['no'] |
question: ['How many antelope are in the image?'], responses:['ไธ'] |
question: ['How many animals are in the image?'], responses:['2'] |
[('walk', 0.1300850101155056), ('go', 0.12480680855916267), ('eat', 0.12468355470235862), ('drive', 0.12445259875307695), ('ride', 0.12426839580448305), ('man', 0.12404790730553829), ('throw', 0.12383246462384812), ('fell', 0.12382326013602675)] |
[['walk', 'go', 'eat', 'drive', 'ride', 'man', 'throw', 'fell']] |
[('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)] |
[['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock']] |
[('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']] |
[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)] |
[['2', '3', '4', '1', '5', '8', '7', '29']] |
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 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3402 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3402 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3402 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3402 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
tensor([1.8385e-01, 8.5638e-03, 2.4416e-02, 2.4415e-02, 2.5150e-01, 3.9912e-04, |
2.4200e-04, 5.0662e-01], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
fell ************* |
['walk', 'go', 'eat', 'drive', 'ride', 'man', 'throw', 'fell'] tensor([1.8385e-01, 8.5638e-03, 2.4416e-02, 2.4415e-02, 2.5150e-01, 3.9912e-04, |
2.4200e-04, 5.0662e-01], device='cuda:1', grad_fn=<SelectBackward0>) |
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>)} |
tensor([1.0000e+00, 1.1472e-09, 7.2242e-07, 2.6746e-10, 9.5634e-09, 2.6190e-08, |
4.6830e-08, 8.5291e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.1472e-09, 7.2242e-07, 2.6746e-10, 9.5634e-09, 2.6190e-08, |
4.6830e-08, 8.5291e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
ANSWER0=VQA(image=RIGHT,question='Does the image in the right television display portray a person?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
tensor([6.6423e-05, 1.0477e-01, 4.2836e-02, 6.4091e-01, 1.0952e-01, 9.2494e-02, |
4.4415e-03, 4.9636e-03], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
bulldog ************* |
['biking', 'geese', 'cushion', 'bulldog', 'striped', 'floral', 'stove', 'dodgers'] tensor([6.6423e-05, 1.0477e-01, 4.2836e-02, 6.4091e-01, 1.0952e-01, 9.2494e-02, |
4.4415e-03, 4.9636e-03], device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.1472e-09, 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>)} |
ANSWER0=VQA(image=LEFT,question='What color is the stingray?') |
ANSWER1=EVAL(expr='{ANSWER0} == "black"') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
tensor([1.0000e+00, 4.0525e-07, 1.3440e-08, 1.6990e-08, 2.3239e-10, 2.9810e-10, |
1.0777e-09, 7.6231e-11], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 4.0525e-07, 1.3440e-08, 1.6990e-08, 2.3239e-10, 2.9810e-10, |
1.0777e-09, 7.6231e-11], device='cuda:3', grad_fn=<SelectBackward0>) |
torch.Size([1, 3, 448, 448]) |
ๆๅ็ๆฆ็ๅๅธไธบ: {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>)} |
ANSWER0=VQA(image=RIGHT,question='How many dogs are sitting in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.6990e-08, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many warthogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 5') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([4, 3, 448, 448]) |
question: ['What color is the stingray?'], responses:['black'] |
question: ['How many dogs are sitting in the image?'], responses:['1'] |
[('black', 0.12706825260511387), ('white', 0.12527812565897103), ('dark', 0.1250491849195085), ('purple', 0.12486259083591467), ('orange', 0.12479002203010545), ('red', 0.12434049404478545), ('maroon', 0.12433890776852753), ('blue', 0.12427242213707339)] |
[['black', 'white', 'dark', 'purple', 'orange', 'red', 'maroon', 'blue']] |
[('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([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 |
torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
question: ['How many warthogs are in the image?'], responses:['5'] |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 |
[('5', 0.12793059870235002), ('8', 0.12539646467821697), ('4', 0.12509737486793587), ('6', 0.12470234839853608), ('3', 0.12467331676337925), ('7', 0.12441254825093238), ('11', 0.12401867309944531), ('9', 0.12376867523920407)] |
[['5', '8', '4', '6', '3', '7', '11', '9']] |
tensor([9.9727e-01, 1.6601e-03, 3.8154e-04, 8.7704e-06, 3.1534e-05, 5.4384e-05, |
6.2805e-05, 5.2589e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
black ************* |
['black', 'white', 'dark', 'purple', 'orange', 'red', 'maroon', 'blue'] tensor([9.9727e-01, 1.6601e-03, 3.8154e-04, 8.7704e-06, 3.1534e-05, 5.4384e-05, |
6.2805e-05, 5.2589e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:0', grad_fn=<DivBackward0>)} |
tensor([1.0000e+00, 2.3860e-10, 6.8358e-11, 1.9170e-10, 1.1533e-10, 1.8948e-08, |
4.0355e-09, 1.5872e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 2.3860e-10, 6.8358e-11, 1.9170e-10, 1.1533e-10, 1.8948e-08, |
4.0355e-09, 1.5872e-10], device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(2.3756e-08, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
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