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ANSWER0=VQA(image=RIGHT,question='How many glass panels does the furniture piece have?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
question: ['Do prairie dogs pose together in the image?'], 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 |
question: ['Is the panda nibbling something?'], 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([7, 3, 448, 448]) knan debug pixel values shape |
tensor([7.2845e-01, 3.1192e-02, 2.3649e-01, 2.1491e-03, 1.1547e-04, 4.8216e-04, |
7.9145e-05, 1.0410e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([7.2845e-01, 3.1192e-02, 2.3649e-01, 2.1491e-03, 1.1547e-04, 4.8216e-04, |
7.9145e-05, 1.0410e-03], device='cuda:1', grad_fn=<SelectBackward0>) |
question: ['Is the fragrance bottle a different color than its box?'], responses:['yes'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7284, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.2365, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0351, 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) |
[('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]) |
question: ['How many glass panels does the furniture piece have?'], 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([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3402 |
question: ['How many baboons are in the image?'], responses:['0'] |
[('0', 0.13077743594303964), ('circles', 0.12449813349255197), ('maroon', 0.12428926693968681), ('large', 0.1242263466991631), ('rooster', 0.12409315512763705), ('nuts', 0.12408018414184876), ('beige', 0.1240288472550799), ('bottle', 0.12400663040099273)] |
[['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
tensor([8.9911e-01, 1.9276e-02, 7.8565e-02, 1.4326e-03, 7.2572e-05, 4.1056e-04, |
4.5072e-05, 1.0868e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.9911e-01, 1.9276e-02, 7.8565e-02, 1.4326e-03, 7.2572e-05, 4.1056e-04, |
4.5072e-05, 1.0868e-03], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8991, device='cuda:3', grad_fn=<UnbindBackward0>), False: tensor(0.0786, device='cuda:3', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0223, device='cuda:3', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many pug dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
question: ['How many pug dogs 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']] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
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 |
tensor([9.8188e-01, 1.9850e-03, 1.5839e-03, 6.3531e-04, 1.3214e-03, 1.2848e-03, |
2.1430e-03, 9.1653e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
0 ************* |
['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle'] tensor([9.8188e-01, 1.9850e-03, 1.5839e-03, 6.3531e-04, 1.3214e-03, 1.2848e-03, |
2.1430e-03, 9.1653e-03], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(0.9819, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0181, device='cuda:1', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400 |
tensor([5.2967e-01, 2.7338e-02, 4.3911e-01, 1.1984e-03, 1.8083e-04, 6.5759e-04, |
3.0396e-04, 1.5447e-03], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([5.2967e-01, 2.7338e-02, 4.3911e-01, 1.1984e-03, 1.8083e-04, 6.5759e-04, |
3.0396e-04, 1.5447e-03], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.5297, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(0.4391, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0312, device='cuda:0', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many rodents are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
tensor([0.2697, 0.2130, 0.2238, 0.0641, 0.1056, 0.0771, 0.0451, 0.0015], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([0.2697, 0.2130, 0.2238, 0.0641, 0.1056, 0.0771, 0.0451, 0.0015], |
device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6662, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.3338, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='What color is the keyboard?') |
ANSWER1=EVAL(expr='{ANSWER0} == "black"') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
tensor([0.8462, 0.0299, 0.0308, 0.0050, 0.0009, 0.0838, 0.0025, 0.0009], |
device='cuda:3', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([0.8462, 0.0299, 0.0308, 0.0050, 0.0009, 0.0838, 0.0025, 0.0009], |
device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8462, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.1538, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
question: ['How many rodents 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 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
question: ['What color is the keyboard?'], responses:['black'] |
[('black', 0.12706825260511387), ('white', 0.12527812565897103), ('dark', 0.1250491849195085), ('purple', 0.12486259083591467), ('orange', 0.12479002203010545), ('red', 0.12434049404478545), ('maroon', 0.12433890776852753), ('blue', 0.12427242213707339)] |
[['black', 'white', 'dark', 'purple', 'orange', 'red', 'maroon', 'blue']] |
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 |
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