text stringlengths 0 1.16k |
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device='cuda:3', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([0.4846, 0.4123, 0.0091, 0.0648, 0.0013, 0.0200, 0.0069, 0.0010], |
device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9154, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0846, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9260, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0740, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Are all the bananas in a bunch in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='How many hartebeests are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
question: ['How many oxen are yolked to the cart 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: 7, images per sample: 7.0, dynamic token length: 1860 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
question: ['How many hartebeests are in the image?'], responses:['1'] |
question: ['Are all the bananas in a bunch in the image?'], responses:['yes'] |
[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)] |
[['1', '3', '4', '8', '6', '12', '2', '47']] |
[('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: 1860 |
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: 1860 |
tensor([9.3515e-01, 2.6532e-02, 7.3676e-03, 2.6532e-02, 2.3183e-03, 1.1290e-03, |
9.0721e-04, 6.9130e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.3515e-01, 2.6532e-02, 7.3676e-03, 2.6532e-02, 2.3183e-03, 1.1290e-03, |
9.0721e-04, 6.9130e-05], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9351, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0649, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many baboons are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
question: ['How many baboons are in the image?'], responses:['1'] |
[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)] |
[['1', '3', '4', '8', '6', '12', '2', '47']] |
torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
tensor([9.3573e-01, 1.3342e-02, 5.9211e-03, 2.7854e-03, 3.1668e-03, 2.5968e-03, |
3.6273e-02, 1.8468e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.3573e-01, 1.3342e-02, 5.9211e-03, 2.7854e-03, 3.1668e-03, 2.5968e-03, |
3.6273e-02, 1.8468e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9357, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0643, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Are there any people in the image?') |
ANSWER1=EVAL(expr='not {ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
tensor([4.9859e-01, 1.1607e-01, 4.2887e-02, 3.1688e-01, 1.5777e-02, 4.7360e-03, |
4.7667e-03, 2.8781e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([4.9859e-01, 1.1607e-01, 4.2887e-02, 3.1688e-01, 1.5777e-02, 4.7360e-03, |
4.7667e-03, 2.8781e-04], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.4986, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.5014, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is there a human in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
question: ['Is there a human 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: ['Are there any people in the image?'], responses:['yes'] |
tensor([5.3160e-01, 8.6777e-02, 2.4100e-02, 4.0065e-03, 7.5839e-03, 2.5374e-03, |
3.4324e-01, 1.5684e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([5.3160e-01, 8.6777e-02, 2.4100e-02, 4.0065e-03, 7.5839e-03, 2.5374e-03, |
3.4324e-01, 1.5684e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.1252, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.8748, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many collies are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} > 1') |
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]) |
tensor([6.4310e-01, 2.8437e-02, 3.2335e-01, 2.0392e-03, 2.2358e-04, 7.7329e-04, |
8.2111e-05, 1.9965e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.4310e-01, 2.8437e-02, 3.2335e-01, 2.0392e-03, 2.2358e-04, 7.7329e-04, |
8.2111e-05, 1.9965e-03], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6431, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.3233, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0336, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many cups are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
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