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Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='How many antelope are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='How many people are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='How many window shades are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='Is the animal in the image standing on all fours?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([5, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many window shades 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']] |
question: ['How many people are in the image?'], responses:['4'] |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
[('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([7, 3, 448, 448]) knan debug pixel values shape |
question: ['How many antelope are in the image?'], responses:['6'] |
question: ['Is the animal in the image standing on all fours?'], responses:['yes'] |
[('6', 0.12794147189263105), ('8', 0.12539492259598553), ('12', 0.12539359088927945), ('5', 0.12471292164321114), ('4', 0.12443617393590153), ('1', 0.12417386497855347), ('11', 0.12398049124372558), ('3', 0.12396656282071232)] |
[['6', '8', '12', '5', '4', '1', '11', '3']] |
[('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 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400 |
tensor([6.7488e-01, 5.8926e-02, 2.0376e-02, 6.4018e-03, 1.2750e-02, 7.2426e-03, |
2.1911e-01, 3.1127e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([6.7488e-01, 5.8926e-02, 2.0376e-02, 6.4018e-03, 1.2750e-02, 7.2426e-03, |
2.1911e-01, 3.1127e-04], device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.2191, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.7809, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many frames are on the wall in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400 |
tensor([0.6231, 0.1677, 0.1778, 0.0019, 0.0147, 0.0041, 0.0098, 0.0010], |
device='cuda:1', grad_fn=<SoftmaxBackward0>) |
4 ************* |
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([0.6231, 0.1677, 0.1778, 0.0019, 0.0147, 0.0041, 0.0098, 0.0010], |
device='cuda:1', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.9959, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0041, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400 |
question: ['How many dogs are in the image?'], responses:['2'] |
question: ['How many frames are on the wall in the image?'], responses:['1'] |
[('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']] |
[('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: 13, images per sample: 13.0, dynamic token length: 3400 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
tensor([0.2365, 0.1626, 0.0485, 0.2222, 0.1284, 0.0456, 0.0636, 0.0926], |
device='cuda:3', grad_fn=<SoftmaxBackward0>) |
6 ************* |
['6', '8', '12', '5', '4', '1', '11', '3'] tensor([0.2365, 0.1626, 0.0485, 0.2222, 0.1284, 0.0456, 0.0636, 0.0926], |
device='cuda:3', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.1383, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.8617, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Are there tinted lips in the image?') |
ANSWER1=EVAL(expr='not {ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
tensor([6.7511e-01, 2.1908e-02, 2.9956e-01, 1.0731e-03, 2.3598e-04, 9.5162e-04, |
3.4261e-05, 1.1227e-03], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.7511e-01, 2.1908e-02, 2.9956e-01, 1.0731e-03, 2.3598e-04, 9.5162e-04, |
3.4261e-05, 1.1227e-03], device='cuda:0', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.6751, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.2996, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the lipstick in the image uncapped?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['Are there tinted lips in the image?'], responses:['yes'] |
torch.Size([13, 3, 448, 448]) |
[('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([1, 3, 448, 448]) knan debug pixel values shape |
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