text stringlengths 0 1.16k |
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torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
question: ['How many round plates are visible 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([3, 3, 448, 448]) knan debug pixel values shape |
tensor([0.2631, 0.1627, 0.2080, 0.1714, 0.0356, 0.0245, 0.0707, 0.0639], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
15 ************* |
['15', '14', '13', '16', '29', '35', '22', '21'] tensor([0.2631, 0.1627, 0.2080, 0.1714, 0.0356, 0.0245, 0.0707, 0.0639], |
device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Is the dog's head laying down?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['How many people are in the image?'], responses:['0'] |
question: ['Is there at least one person standing in front of and staring ahead at a row of vending machines?'], responses:['no'] |
torch.Size([13, 3, 448, 448]) |
[('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']] |
[('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([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: 1873 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 |
tensor([0.4146, 0.2198, 0.1731, 0.0799, 0.0630, 0.0265, 0.0225, 0.0007], |
device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([0.4146, 0.2198, 0.1731, 0.0799, 0.0630, 0.0265, 0.0225, 0.0007], |
device='cuda:1', grad_fn=<SelectBackward0>) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9201, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0799, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Are there people in a shop in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 |
question: ['Is the dog'], 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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 |
tensor([7.3001e-01, 2.6855e-01, 7.3181e-05, 1.5731e-04, 6.8819e-04, 7.2243e-05, |
2.9207e-04, 1.5594e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([7.3001e-01, 2.6855e-01, 7.3181e-05, 1.5731e-04, 6.8819e-04, 7.2243e-05, |
2.9207e-04, 1.5594e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
tensor([9.8619e-01, 1.9168e-03, 1.9260e-03, 4.9876e-04, 2.1007e-03, 3.7738e-04, |
1.6239e-03, 5.3693e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
0 ************* |
['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle'] tensor([9.8619e-01, 1.9168e-03, 1.9260e-03, 4.9876e-04, 2.1007e-03, 3.7738e-04, |
1.6239e-03, 5.3693e-03], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), False: tensor(0.9862, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0138, device='cuda:3', grad_fn=<DivBackward0>)} |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.2686, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.7300, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many birds are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Does the sink have a double basin?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Are there people in a shop 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([13, 3, 448, 448]) knan debug pixel values shape |
question: ['How many birds are in the image?'], responses:['2'] |
question: ['Does the sink have a double basin?'], responses:['yes'] |
[('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([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
tensor([0.5989, 0.0273, 0.3588, 0.0028, 0.0010, 0.0030, 0.0009, 0.0074], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([0.5989, 0.0273, 0.3588, 0.0028, 0.0010, 0.0030, 0.0009, 0.0074], |
device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.5989, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.3588, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0423, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many mountain goats 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: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
question: ['How many mountain goats are in the image?'], responses:['3'] |
tensor([7.5998e-01, 1.9655e-02, 2.1774e-01, 1.4044e-03, 9.7516e-05, 3.4476e-04, |
8.8610e-05, 6.9323e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([7.5998e-01, 1.9655e-02, 2.1774e-01, 1.4044e-03, 9.7516e-05, 3.4476e-04, |
8.8610e-05, 6.9323e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7600, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.2177, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0223, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many animals are on the rock?') |
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