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Registering RESULT step |
Registering VQA_lavis step |
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=LEFT,question='How many yellowish anemone that resemble flowers are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 8') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Does the golfball in the image have a square-shaped design?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Are people wearing white shirts banging steel drum instruments?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
ANSWER0=VQA(image=LEFT,question='How many men are standing next to each-other in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Does the golfball in the image have a square-shaped design?'], responses:['no'] |
[('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([3, 3, 448, 448]) knan debug pixel values shape |
question: ['Are people wearing white shirts banging steel drum instruments?'], responses:['yes'] |
question: ['How many yellowish anemone that resemble flowers are in the image?'], responses:['100'] |
[('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']] |
[('100', 0.1277092174007614), ('120', 0.12519936731884676), ('88', 0.12483671971182599), ('80', 0.12474858811112934), ('60', 0.12457749608485191), ('99', 0.1243465850330014), ('90', 0.12430147627057883), ('101', 0.12428055006900451)] |
[['100', '120', '88', '80', '60', '99', '90', '101']] |
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: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 |
tensor([1.0000e+00, 3.1609e-10, 2.5426e-07, 3.2858e-12, 2.6745e-11, 7.3553e-09, |
3.1299e-10, 1.5007e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 3.1609e-10, 2.5426e-07, 3.2858e-12, 2.6745e-11, 7.3553e-09, |
3.1299e-10, 1.5007e-07], device='cuda:3', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(3.1609e-10, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(3.5763e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many stingrays are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
question: ['How many men are standing next to each-other in the image?'], responses:['3'] |
torch.Size([7, 3, 448, 448]) |
[('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: 7, images per sample: 7.0, dynamic token length: 1864 |
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 |
question: ['How many stingrays are in the image?'], responses:['3'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 |
[('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([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 |
tensor([1.0000e+00, 1.7214e-08, 6.9980e-11, 2.5786e-08, 2.1053e-10, 3.6954e-10, |
3.8669e-11, 1.3464e-08], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.7009e-01, 1.0666e-03, 1.4492e-05, 5.6967e-03, 1.5480e-02, 1.3132e-03, |
5.7509e-03, 5.8469e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
tensor([1.0000e+00, 1.7214e-08, 6.9980e-11, 2.5786e-08, 2.1053e-10, 3.6954e-10, |
3.8669e-11, 1.3464e-08], device='cuda:0', grad_fn=<SelectBackward0>) |
100 ************* |
['100', '120', '88', '80', '60', '99', '90', '101'] tensor([9.7009e-01, 1.0666e-03, 1.4492e-05, 5.6967e-03, 1.5480e-02, 1.3132e-03, |
5.7509e-03, 5.8469e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1., device='cuda:0', grad_fn=<DivBackward0>), False: tensor(6.9980e-11, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(-6.9980e-11, device='cuda:0', grad_fn=<DivBackward0>)} |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many baboons are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 5') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many baboons 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([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
question: ['How many dogs are in the image?'], responses:['11'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
tensor([9.8202e-01, 1.7976e-02, 2.9178e-09, 6.5564e-07, 3.1001e-10, 4.6505e-07, |
6.0832e-09, 1.6268e-08], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([9.8202e-01, 1.7976e-02, 2.9178e-09, 6.5564e-07, 3.1001e-10, 4.6505e-07, |
6.0832e-09, 1.6268e-08], device='cuda:3', grad_fn=<SelectBackward0>) |
[('11', 0.12740768001087358), ('10', 0.12548679249075975), ('12', 0.12538137681693887), ('9', 0.12485855662563465), ('8', 0.12469919178932766), ('13', 0.12431757055023795), ('7', 0.12396146028399917), ('14', 0.1238873714322284)] |
[['11', '10', '12', '9', '8', '13', '7', '14']] |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(2.9178e-09, 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>)} |
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