text stringlengths 0 1.16k |
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[('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([1, 3, 448, 448]) knan debug pixel values shape |
question: ['Is there an unworn knee pad to the right of a model'], 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']] |
tensor([5.7084e-01, 4.2715e-01, 4.3599e-04, 1.2927e-04, 3.0892e-04, 5.6251e-04, |
2.2540e-04, 3.5009e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([5.7084e-01, 4.2715e-01, 4.3599e-04, 1.2927e-04, 3.0892e-04, 5.6251e-04, |
2.2540e-04, 3.5009e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.4271, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.5708, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0020, device='cuda:1', grad_fn=<DivBackward0>)} |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 |
ANSWER0=VQA(image=RIGHT,question='How many binders are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 3, 448, 448]) |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 |
question: ['How many binders 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: 5, images per sample: 5.0, dynamic token length: 1353 |
question: ['How many sled dogs are in the image?'], responses:['5'] |
question: ['How many white dogs are in the image?'], responses:['2'] |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
[('5', 0.12793059870235002), ('8', 0.12539646467821697), ('4', 0.12509737486793587), ('6', 0.12470234839853608), ('3', 0.12467331676337925), ('7', 0.12441254825093238), ('11', 0.12401867309944531), ('9', 0.12376867523920407)] |
[['5', '8', '4', '6', '3', '7', '11', '9']] |
[('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: 5, images per sample: 5.0, dynamic token length: 1353 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 |
tensor([4.9787e-01, 2.4805e-02, 4.7431e-01, 8.8042e-04, 1.5428e-04, 9.1300e-04, |
2.0996e-04, 8.5512e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([4.9787e-01, 2.4805e-02, 4.7431e-01, 8.8042e-04, 1.5428e-04, 9.1300e-04, |
2.0996e-04, 8.5512e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.4979, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.4743, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the goat laying down?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([13, 3, 448, 448]) |
tensor([4.6140e-01, 1.6972e-01, 5.5140e-02, 2.6126e-01, 3.4249e-02, 8.3962e-03, |
9.4074e-03, 4.2021e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([4.6140e-01, 1.6972e-01, 5.5140e-02, 2.6126e-01, 3.4249e-02, 8.3962e-03, |
9.4074e-03, 4.2021e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.4614, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.5386, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
question: ['Is the goat laying down?'], 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 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3394 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3394 |
tensor([0.2845, 0.0577, 0.1950, 0.2214, 0.0815, 0.1185, 0.0094, 0.0319], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
5 ************* |
['5', '8', '4', '6', '3', '7', '11', '9'] tensor([0.2845, 0.0577, 0.1950, 0.2214, 0.0815, 0.1185, 0.0094, 0.0319], |
device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7824, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.2176, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
tensor([6.4528e-01, 3.6411e-02, 7.6319e-03, 3.0486e-01, 3.1169e-03, 1.2837e-03, |
1.2842e-03, 1.2918e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([6.4528e-01, 3.6411e-02, 7.6319e-03, 3.0486e-01, 3.1169e-03, 1.2837e-03, |
1.2842e-03, 1.2918e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6951, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.3049, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Can you see the lamp in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3394 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3394 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
question: ['How many dogs are in the image?'], responses:['5'] |
question: ['Can you see the lamp in the image?'], responses:['no'] |
[('5', 0.12793059870235002), ('8', 0.12539646467821697), ('4', 0.12509737486793587), ('6', 0.12470234839853608), ('3', 0.12467331676337925), ('7', 0.12441254825093238), ('11', 0.12401867309944531), ('9', 0.12376867523920407)] |
[['5', '8', '4', '6', '3', '7', '11', '9']] |
[('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']] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([8.7773e-01, 2.2216e-02, 9.8478e-02, 6.5496e-04, 5.4639e-05, 2.2879e-04, |
3.7067e-05, 6.0475e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.7773e-01, 2.2216e-02, 9.8478e-02, 6.5496e-04, 5.4639e-05, 2.2879e-04, |
3.7067e-05, 6.0475e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8777, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(0.0985, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0238, device='cuda:0', grad_fn=<SubBackward0>)} |
tensor([0.3476, 0.0567, 0.0934, 0.3067, 0.0196, 0.1358, 0.0079, 0.0323], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
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