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Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='How many parts of a flute are held horizontally?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1)Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='How many elephants are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
ANSWER0=VQA(image=LEFT,question='How many toes can be counted?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
ANSWER0=VQA(image=LEFT,question='How many wine glasses are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many elephants are in the image?'], responses:['2'] |
[('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([1, 3, 448, 448]) knan debug pixel values shape |
question: ['How many wine glasses 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([3, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 3.3597e-07, 1.9864e-08, 3.2242e-08, 4.7869e-10, 6.6648e-10, |
9.6971e-10, 1.1540e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 3.3597e-07, 1.9864e-08, 3.2242e-08, 4.7869e-10, 6.6648e-10, |
9.6971e-10, 1.1540e-10], device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(3.2242e-08, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Do all dogs have blue harnesses?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['How many parts of a flute are held horizontally?'], responses:['2'] |
torch.Size([7, 3, 448, 448]) |
[('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([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
tensor([1.0000e+00, 4.6715e-10, 9.0560e-11, 2.2413e-10, 1.7865e-10, 1.7233e-08, |
3.8208e-09, 2.0182e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 4.6715e-10, 9.0560e-11, 2.2413e-10, 1.7865e-10, 1.7233e-08, |
3.8208e-09, 2.0182e-10], device='cuda:3', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(2.2216e-08, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['How many toes can be counted?'], responses:['4'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
torch.Size([13, 3, 448, 448]) |
question: ['Do all dogs have blue harnesses?'], responses:['no'] |
[('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']] |
[('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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
tensor([9.4774e-01, 4.9725e-03, 1.2450e-04, 4.7154e-02, 7.0250e-06, 1.0337e-07, |
1.6681e-06, 1.6970e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.4774e-01, 4.9725e-03, 1.2450e-04, 4.7154e-02, 7.0250e-06, 1.0337e-07, |
1.6681e-06, 1.6970e-09], device='cuda:0', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.9950, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many cheetahs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['How many animals are in the image?'], responses:['1'] |
torch.Size([13, 3, 448, 448]) |
[('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 |
tensor([9.9977e-01, 2.3051e-04, 4.3806e-07, 4.8462e-11, 3.1629e-11, 1.8724e-09, |
4.6842e-10, 2.4140e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.9977e-01, 2.3051e-04, 4.3806e-07, 4.8462e-11, 3.1629e-11, 1.8724e-09, |
4.6842e-10, 2.4140e-07], device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.0002, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.9998, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(7.1526e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
question: ['How many cheetahs are in the image?'], responses:['3'] |
[('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([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
tensor([9.8976e-01, 2.5603e-05, 9.9275e-07, 9.1153e-03, 1.0887e-03, 2.8829e-08, |
5.0416e-06, 4.7361e-06], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
4 ************* |
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