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torch.Size([3, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many skincare items are in the image?'], responses:['4'] |
[('4', 0.12804651361935848), ('5', 0.12521071898947128), ('3', 0.12515925906184908), ('8', 0.12489091845155219), ('6', 0.1245383468146311), ('1', 0.12441141527606933), ('2', 0.12403713327181662), ('11', 0.12370569451525179)] |
[['4', '5', '3', '8', '6', '1', '2', '11']] |
torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
question: ['How many pairs of free weights are in the image?'], responses:['9'] |
question: ['How many puppies are in the image?'], responses:['7'] |
[('9', 0.12801736482258133), ('8', 0.12565135970392036), ('11', 0.1254560343890198), ('10', 0.1248838582125673), ('7', 0.12420801006143238), ('12', 0.12408347303550306), ('5', 0.12385261492086817), ('14', 0.12384728485410773)] |
[['9', '8', '11', '10', '7', '12', '5', '14']] |
[('7', 0.12828776251745355), ('8', 0.1258361832781132), ('11', 0.12481772898325143), ('5', 0.124759881092759), ('9', 0.12447036165452931), ('10', 0.1239759375399529), ('6', 0.12393017600998846), ('12', 0.12392196892395223)] |
[['7', '8', '11', '5', '9', '10', '6', '12']] |
torch.Size([3, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
torch.Size([3, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
tensor([9.9951e-01, 4.0437e-05, 4.4741e-04, 7.4834e-10, 2.2202e-09, 1.3328e-06, |
1.0813e-07, 4.1382e-08], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
4 ************* |
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([9.9951e-01, 4.0437e-05, 4.4741e-04, 7.4834e-10, 2.2202e-09, 1.3328e-06, |
1.0813e-07, 4.1382e-08], device='cuda:3', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0813e-07, 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>)} |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
ANSWER0=VQA(image=RIGHT,question='Does the image show a brown and white spaniel on the grass?') |
ANSWER1=RESULT(var=ANSWER0) |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
tensor([3.5601e-01, 3.4943e-03, 4.9567e-01, 6.3086e-03, 4.6697e-02, 9.1667e-02, |
9.0986e-06, 1.4674e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
11 ************* |
['9', '8', '11', '10', '7', '12', '5', '14'] tensor([3.5601e-01, 3.4943e-03, 4.9567e-01, 6.3086e-03, 4.6697e-02, 9.1667e-02, |
9.0986e-06, 1.4674e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
tensor([9.9108e-01, 4.5444e-04, 6.2733e-03, 1.6553e-05, 1.3998e-03, 3.3139e-04, |
4.2690e-04, 1.2849e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
7 ************* |
['7', '8', '11', '5', '9', '10', '6', '12'] tensor([9.9108e-01, 4.5444e-04, 6.2733e-03, 1.6553e-05, 1.3998e-03, 3.3139e-04, |
4.2690e-04, 1.2849e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)} |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['Are the dogs outside in the grass?'], responses:['no'] |
ANSWER0=VQA(image=RIGHT,question='How many flutes are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
[('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']] |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
question: ['Does the image show a brown and white spaniel on the grass?'], 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']] |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
question: ['How many animals are in the image?'], responses:['2'] |
question: ['How many flutes are in the image?'], responses:['4'] |
[('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']] |
[('4', 0.12804651361935848), ('5', 0.12521071898947128), ('3', 0.12515925906184908), ('8', 0.12489091845155219), ('6', 0.1245383468146311), ('1', 0.12441141527606933), ('2', 0.12403713327181662), ('11', 0.12370569451525179)] |
[['4', '5', '3', '8', '6', '1', '2', '11']] |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
tensor([1.0000e+00, 7.5825e-10, 3.1448e-07, 2.6923e-12, 1.4015e-12, 5.0706e-09, |
5.7750e-10, 1.1148e-06], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 7.5825e-10, 3.1448e-07, 2.6923e-12, 1.4015e-12, 5.0706e-09, |
5.7750e-10, 1.1148e-06], device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(7.5825e-10, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.4305e-06, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many jellyfish are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
tensor([1.0000e+00, 3.2840e-09, 2.3674e-10, 1.2956e-08, 9.1361e-10, 9.8699e-11, |
5.8422e-11, 1.5110e-08], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 3.2840e-09, 2.3674e-10, 1.2956e-08, 9.1361e-10, 9.8699e-11, |
5.8422e-11, 1.5110e-08], device='cuda:3', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1., device='cuda:3', grad_fn=<UnbindBackward0>), False: tensor(2.3674e-10, device='cuda:3', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-2.3674e-10, device='cuda:3', grad_fn=<SubBackward0>)} |
question: ['How many jellyfish 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']] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
tensor([9.9981e-01, 1.9110e-04, 1.6987e-08, 8.9006e-08, 3.3844e-09, 1.9818e-09, |
9.0393e-09, 4.8431e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9981e-01, 1.9110e-04, 1.6987e-08, 8.9006e-08, 3.3844e-09, 1.9818e-09, |
9.0393e-09, 4.8431e-09], device='cuda:0', grad_fn=<SelectBackward0>) |
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