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Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=LEFT,question='Is the food on a white plate?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='How many lipsticks are standing up with their caps off?') |
ANSWER1=EVAL(expr='{ANSWER0} % 2 == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Is the animal standing in side profile with its head turned toward the camera?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Is the dog standing on the grass?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([5, 3, 448, 448]) |
torch.Size([3, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
question: ['Is the animal standing in side profile with its head turned toward the camera?'], 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([3, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 |
question: ['How many lipsticks are standing up with their caps off?'], 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']] |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 |
question: ['Is the food on a white plate?'], responses:['yes'] |
question: ['Is the dog standing on the grass?'], responses:['no'] |
[('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: 3, images per sample: 3.0, dynamic token length: 844 |
[('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: 3, images per sample: 3.0, dynamic token length: 843 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 |
tensor([5.2153e-01, 1.5862e-02, 4.6024e-01, 9.3342e-04, 1.2508e-04, 6.2318e-04, |
1.2031e-04, 5.6836e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([5.2153e-01, 1.5862e-02, 4.6024e-01, 9.3342e-04, 1.2508e-04, 6.2318e-04, |
1.2031e-04, 5.6836e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.5215, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.4602, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the puppy bounding across the grass?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
tensor([0.1893, 0.1960, 0.1490, 0.1475, 0.0342, 0.1796, 0.0940, 0.0105], |
device='cuda:1', grad_fn=<SoftmaxBackward0>) |
4 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([0.1893, 0.1960, 0.1490, 0.1475, 0.0342, 0.1796, 0.0940, 0.0105], |
device='cuda:1', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.4857, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.5143, 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 zebras are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 5') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 3, 448, 448]) |
question: ['How many zebras are in the image?'], responses:['5'] |
[('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([8.8957e-01, 1.3524e-02, 9.3828e-02, 6.7283e-04, 7.6797e-05, 2.4692e-04, |
1.0741e-05, 2.0734e-03], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.8957e-01, 1.3524e-02, 9.3828e-02, 6.7283e-04, 7.6797e-05, 2.4692e-04, |
1.0741e-05, 2.0734e-03], device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.8896, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.0938, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0166, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Are the dogs on grass?') |
ANSWER1=EVAL(expr='not {ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
tensor([8.3505e-01, 1.6443e-01, 3.7932e-05, 5.1666e-05, 3.7702e-05, 1.8687e-04, |
1.5907e-04, 5.1271e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([8.3505e-01, 1.6443e-01, 3.7932e-05, 5.1666e-05, 3.7702e-05, 1.8687e-04, |
1.5907e-04, 5.1271e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
question: ['Is the puppy bounding across the grass?'], responses:['yes'] |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.1644, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.8350, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0005, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many puppies are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 4') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('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([7, 3, 448, 448]) |
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 |
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