text stringlengths 0 1.16k |
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torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
tensor([0.2824, 0.1502, 0.1251, 0.0861, 0.0896, 0.0860, 0.1768, 0.0038], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([0.2824, 0.1502, 0.1251, 0.0861, 0.0896, 0.0860, 0.1768, 0.0038], |
device='cuda:2', grad_fn=<SelectBackward0>) |
tensor([0.3603, 0.2053, 0.2890, 0.0096, 0.0569, 0.0203, 0.0552, 0.0033], |
device='cuda:1', grad_fn=<SoftmaxBackward0>) |
4 ************* |
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([0.3603, 0.2053, 0.2890, 0.0096, 0.0569, 0.0203, 0.0552, 0.0033], |
device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.2654, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.7346, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', 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) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.2890, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.7110, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Are the pencils supported with bands?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Are all the balls in the image white?'], 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([7, 3, 448, 448]) knan debug pixel values shape |
question: ['Is the dog against a white background?'], 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: 3396 |
question: ['What color is the flower in the white vase?'], responses:['yellow'] |
question: ['Are the pencils supported with bands?'], responses:['yes'] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
[('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']] |
[('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 |
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 |
tensor([5.2206e-01, 4.7675e-01, 2.3738e-05, 1.3320e-04, 1.3245e-04, 3.6230e-04, |
5.2771e-04, 1.1099e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([5.2206e-01, 4.7675e-01, 2.3738e-05, 1.3320e-04, 1.3245e-04, 3.6230e-04, |
5.2771e-04, 1.1099e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.4767, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.5221, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0012, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many sled dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
question: ['How many sled dogs are in the image?'], responses:['4'] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
[('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']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
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: 3397 |
tensor([8.8974e-01, 1.5269e-02, 9.3847e-02, 2.8248e-04, 7.9401e-05, 2.2470e-04, |
2.8505e-05, 5.3062e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.8974e-01, 1.5269e-02, 9.3847e-02, 2.8248e-04, 7.9401e-05, 2.2470e-04, |
2.8505e-05, 5.3062e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8897, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0938, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
tensor([5.8028e-01, 1.7146e-02, 3.9883e-01, 1.5416e-03, 2.3635e-04, 6.7184e-04, |
1.1439e-04, 1.1788e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([5.8028e-01, 1.7146e-02, 3.9883e-01, 1.5416e-03, 2.3635e-04, 6.7184e-04, |
1.1439e-04, 1.1788e-03], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.5803, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.3988, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0209, device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([8.7690e-01, 2.4733e-02, 2.9539e-02, 1.4740e-02, 4.5325e-02, 3.0123e-05, |
8.0370e-03, 6.9990e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yellow ************* |
['yellow', 'red', 'green', 'maroon', 'pink', 'mask', 'orange', 'color'] tensor([8.7690e-01, 2.4733e-02, 2.9539e-02, 1.4740e-02, 4.5325e-02, 3.0123e-05, |
8.0370e-03, 6.9990e-04], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is there a woman in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
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([5, 3, 448, 448]) |
tensor([0.2717, 0.3039, 0.1054, 0.0718, 0.1962, 0.0079, 0.0253, 0.0178], |
device='cuda:3', grad_fn=<SoftmaxBackward0>) |
5 ************* |
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([0.2717, 0.3039, 0.1054, 0.0718, 0.1962, 0.0079, 0.0253, 0.0178], |
device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0332, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9668, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many white dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
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