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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
tensor([0.4129, 0.1911, 0.3019, 0.0054, 0.0387, 0.0130, 0.0354, 0.0017], |
device='cuda:0', grad_fn=<SoftmaxBackward0>) |
4 ************* |
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([0.4129, 0.1911, 0.3019, 0.0054, 0.0387, 0.0130, 0.0354, 0.0017], |
device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.3019, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.6981, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many windows are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
question: ['How many sled dogs are in the image?'], responses:['4'] |
question: ['Are all the balls in the image white?'], responses:['no'] |
[('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']] |
question: ['How many windows are in the image?'], responses:['2'] |
[('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']] |
[('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([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
tensor([9.0152e-01, 4.7770e-02, 2.1866e-02, 1.9910e-02, 4.7297e-03, 2.6109e-03, |
1.4879e-03, 1.0443e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.0152e-01, 4.7770e-02, 2.1866e-02, 1.9910e-02, 4.7297e-03, 2.6109e-03, |
1.4879e-03, 1.0443e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9015, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0985, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
question: ['Are the pencils supported with bands?'], 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([13, 3, 448, 448]) knan debug pixel values shape |
tensor([0.3035, 0.3358, 0.0999, 0.0514, 0.1753, 0.0050, 0.0173, 0.0118], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
5 ************* |
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([0.3035, 0.3358, 0.0999, 0.0514, 0.1753, 0.0050, 0.0173, 0.0118], |
device='cuda:2', grad_fn=<SelectBackward0>) |
tensor([5.1509e-01, 4.8390e-01, 1.6094e-05, 1.1430e-04, 1.1161e-04, 2.9321e-04, |
4.7167e-04, 6.8647e-06], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([5.1509e-01, 4.8390e-01, 1.6094e-05, 1.1430e-04, 1.1161e-04, 2.9321e-04, |
4.7167e-04, 6.8647e-06], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0223, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.9777, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.4839, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.5151, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0010, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='What color is the flower in the white vase?') |
ANSWER1=EVAL(expr='{ANSWER0} == "yellow"') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='How many black labs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['What color is the flower in the white vase?'], responses:['yellow'] |
question: ['How many black labs are in the image?'], responses:['0'] |
[('yellow', 0.13019233292980176), ('red', 0.12608840659087261), ('green', 0.12436926918223776), ('maroon', 0.12425930516133966), ('pink', 0.12421440410307089), ('mask', 0.12363437991296296), ('orange', 0.12363130058084727), ('color', 0.12361060153886716)] |
[['yellow', 'red', 'green', 'maroon', 'pink', 'mask', 'orange', 'color']] |
[('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([13, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([5.6833e-01, 1.2612e-02, 4.1579e-01, 1.3415e-03, 2.0252e-04, 5.8100e-04, |
9.2755e-05, 1.0491e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([5.6833e-01, 1.2612e-02, 4.1579e-01, 1.3415e-03, 2.0252e-04, 5.8100e-04, |
9.2755e-05, 1.0491e-03], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.5683, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.4158, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0159, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is there a woman in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 3, 448, 448]) |
question: ['Is there a woman 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([5, 3, 448, 448]) knan debug pixel values shape |
tensor([9.1062e-01, 1.8078e-02, 7.0219e-02, 5.8852e-04, 8.0981e-05, 2.1602e-04, |
2.0248e-05, 1.7867e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.1062e-01, 1.8078e-02, 7.0219e-02, 5.8852e-04, 8.0981e-05, 2.1602e-04, |
2.0248e-05, 1.7867e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9106, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0702, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0192, device='cuda:3', grad_fn=<DivBackward0>)} |
tensor([8.9158e-01, 2.0864e-02, 2.6510e-02, 1.2691e-02, 4.0775e-02, 2.4103e-05, |
6.9952e-03, 5.5593e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yellow ************* |
['yellow', 'red', 'green', 'maroon', 'pink', 'mask', 'orange', 'color'] tensor([8.9158e-01, 2.0864e-02, 2.6510e-02, 1.2691e-02, 4.0775e-02, 2.4103e-05, |
6.9952e-03, 5.5593e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([9.9254e-01, 1.0271e-03, 8.2762e-04, 1.2730e-04, 7.2046e-04, 1.7361e-04, |
7.9317e-04, 3.7944e-03], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
0 ************* |
['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle'] tensor([9.9254e-01, 1.0271e-03, 8.2762e-04, 1.2730e-04, 7.2046e-04, 1.7361e-04, |
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