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Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=LEFT,question='How many animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='How many perfume bottles are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='How many chimpanzees are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
torch.Size([3, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
ANSWER0=VQA(image=LEFT,question='Is the clownfish within the anemone?') |
ANSWER1=EVAL(expr='not {ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
question: ['How many perfume bottles are in the image?'], responses:['11'] |
question: ['How many chimpanzees are in the image?'], responses:['2'] |
question: ['Is the clownfish within the anemone?'], responses:['yes'] |
[('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']] |
[('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']] |
[('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 |
torch.Size([3, 3, 448, 448]) knan debug pixel values shape |
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 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
question: ['How many animals 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']] |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
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: 840 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 |
tensor([8.7444e-01, 1.5867e-03, 2.9959e-02, 4.5485e-04, 5.7217e-06, 6.3378e-02, |
2.5894e-04, 2.9917e-02], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
11 ************* |
['11', '10', '12', '9', '8', '13', '7', '14'] tensor([8.7444e-01, 1.5867e-03, 2.9959e-02, 4.5485e-04, 5.7217e-06, 6.3378e-02, |
2.5894e-04, 2.9917e-02], device='cuda:2', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 7.4965e-08, 3.9114e-09, 9.2374e-09, 8.4412e-11, 1.9140e-10, |
2.1633e-10, 4.9810e-11], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 7.4965e-08, 3.9114e-09, 9.2374e-09, 8.4412e-11, 1.9140e-10, |
2.1633e-10, 4.9810e-11], device='cuda:3', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 6.7610e-09, 1.5558e-09, 2.3165e-08, 3.6018e-11, 6.1276e-11, |
3.2233e-11, 4.0205e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 6.7610e-09, 1.5558e-09, 2.3165e-08, 3.6018e-11, 6.1276e-11, |
3.2233e-11, 4.0205e-09], device='cuda:0', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
ๆๅ็ๆฆ็ๅๅธไธบ: ANSWER0=VQA(image=LEFT,question='Is there water in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
{True: tensor(7.9418e-08, 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>)} |
ANSWER0=VQA(image=LEFT,question='How many birds are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.5558e-09, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.5558e-09, device='cuda:0', grad_fn=<DivBackward0>)} |
torch.Size([7, 3, 448, 448]) |
ANSWER0=VQA(image=RIGHT,question='Is there at least one full mug of beer sitting on the table to the right of the pizza?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Is there at least one full mug of beer sitting on the table to the right of the pizza?'], 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 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 |
question: ['How many birds 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: 3, images per sample: 3.0, dynamic token length: 848 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 |
tensor([9.9998e-01, 2.4300e-05, 7.0421e-08, 1.4908e-07, 2.0291e-09, 2.4251e-10, |
3.5061e-09, 1.7975e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9998e-01, 2.4300e-05, 7.0421e-08, 1.4908e-07, 2.0291e-09, 2.4251e-10, |
3.5061e-09, 1.7975e-10], device='cuda:1', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(2.4526e-05, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
question: ['Is there water in the image?'], responses:['no'] |
tensor([1.0000e+00, 3.3983e-09, 1.0731e-06, 1.6398e-10, 5.7378e-10, 7.8478e-08, |
3.6306e-09, 4.6351e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 3.3983e-09, 1.0731e-06, 1.6398e-10, 5.7378e-10, 7.8478e-08, |
3.6306e-09, 4.6351e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
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