text stringlengths 0 1.16k |
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[('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']] |
[('6', 0.12794147189263105), ('8', 0.12539492259598553), ('12', 0.12539359088927945), ('5', 0.12471292164321114), ('4', 0.12443617393590153), ('1', 0.12417386497855347), ('11', 0.12398049124372558), ('3', 0.12396656282071232)] |
[['6', '8', '12', '5', '4', '1', '11', '3']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
tensor([8.1906e-01, 3.1755e-02, 1.2850e-02, 3.1431e-03, 4.8698e-03, 2.5219e-03, |
1.2562e-01, 1.7902e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([8.1906e-01, 3.1755e-02, 1.2850e-02, 3.1431e-03, 4.8698e-03, 2.5219e-03, |
1.2562e-01, 1.7902e-04], device='cuda:2', grad_fn=<SelectBackward0>) |
tensor([5.7151e-01, 4.2772e-01, 1.0498e-05, 1.2179e-04, 1.9121e-04, 1.9222e-04, |
2.2754e-04, 2.7009e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([5.7151e-01, 4.2772e-01, 1.0498e-05, 1.2179e-04, 1.9121e-04, 1.9222e-04, |
2.2754e-04, 2.7009e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0318, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.9682, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the egg in the image brown?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([1, 3, 448, 448]) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.4277, device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(0.5715, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0008, device='cuda:1', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many people are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
torch.Size([13, 3, 448, 448]) |
question: ['Is the egg in the image brown?'], 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([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
tensor([6.9834e-01, 2.1973e-02, 2.7347e-01, 2.9935e-03, 2.3498e-04, 6.5565e-04, |
6.5279e-05, 2.2632e-03], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.9834e-01, 2.1973e-02, 2.7347e-01, 2.9935e-03, 2.3498e-04, 6.5565e-04, |
6.5279e-05, 2.2632e-03], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6983, device='cuda:2', grad_fn=<UnbindBackward0>), False: tensor(0.2735, device='cuda:2', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0282, device='cuda:2', grad_fn=<SubBackward0>)} |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
tensor([5.3005e-01, 4.2514e-02, 1.3801e-02, 2.7172e-03, 4.9209e-03, 2.4514e-03, |
4.0335e-01, 2.0395e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([5.3005e-01, 4.2514e-02, 1.3801e-02, 2.7172e-03, 4.9209e-03, 2.4514e-03, |
4.0335e-01, 2.0395e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
tensor([0.4117, 0.1716, 0.0075, 0.3015, 0.0716, 0.0037, 0.0159, 0.0165], |
device='cuda:3', grad_fn=<SoftmaxBackward0>) |
6 ************* |
['6', '8', '12', '5', '4', '1', '11', '3'] tensor([0.4117, 0.1716, 0.0075, 0.3015, 0.0716, 0.0037, 0.0159, 0.0165], |
device='cuda:3', grad_fn=<SelectBackward0>) |
question: ['How many people are in the image?'], responses:['2'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0201, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9798, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many shoes are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Is the dog running?') |
ANSWER1=EVAL(expr='not {ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('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([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
question: ['Is the dog running?'], 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 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 |
question: ['How many shoes are in the image?'], responses:['1'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 |
[('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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 |
tensor([9.1886e-01, 8.0289e-02, 5.3398e-05, 5.2678e-05, 3.4121e-05, 3.4770e-04, |
2.1347e-04, 1.4556e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.1886e-01, 8.0289e-02, 5.3398e-05, 5.2678e-05, 3.4121e-05, 3.4770e-04, |
2.1347e-04, 1.4556e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9189, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0803, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)} |
tensor([7.0504e-01, 6.1605e-02, 1.0705e-02, 2.1623e-01, 3.8386e-03, 1.0014e-03, |
1.4941e-03, 8.1514e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([7.0504e-01, 6.1605e-02, 1.0705e-02, 2.1623e-01, 3.8386e-03, 1.0014e-03, |
1.4941e-03, 8.1514e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7050, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.2950, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([9.3146e-01, 1.8735e-02, 9.4194e-03, 3.9223e-03, 5.0400e-03, 3.0305e-03, |
2.8124e-02, 2.6827e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.3146e-01, 1.8735e-02, 9.4194e-03, 3.9223e-03, 5.0400e-03, 3.0305e-03, |
2.8124e-02, 2.6827e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
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