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question: ['Are the animals standing on their hind legs?'], responses:['yes'] |
question: ['Is the dog standing in the water?'], responses:['no'] |
[('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']] |
[('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([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 1.0467e-08, 1.7972e-07, 2.0568e-10, 3.8958e-10, 2.6209e-08, |
2.2495e-09, 2.6313e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.0467e-08, 1.7972e-07, 2.0568e-10, 3.8958e-10, 2.6209e-08, |
2.2495e-09, 2.6313e-07], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0467e-08, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many animals 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: 3400 |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
tensor([4.7737e-01, 1.9389e-03, 2.7317e-01, 6.2560e-03, 2.2551e-01, 1.5559e-02, |
1.1054e-04, 7.5648e-05], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
9 ************* |
['9', '8', '11', '10', '7', '12', '5', '14'] tensor([4.7737e-01, 1.9389e-03, 2.7317e-01, 6.2560e-03, 2.2551e-01, 1.5559e-02, |
1.1054e-04, 7.5648e-05], 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='How many animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 5') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
question: ['How many animals 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']] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
question: ['How many animals are in the image?'], responses:['five'] |
[('7 eleven', 0.1264466744091217), ('babies', 0.124977990347662), ('sunrise', 0.12490143984830117), ('eating', 0.1247676656843781), ('feet', 0.12475702323703439), ('candle', 0.12473210928138137), ('light', 0.12472650705175181), ('floating', 0.12469059014036947)] |
[['7 eleven', 'babies', 'sunrise', 'eating', 'feet', 'candle', 'light', 'floating']] |
torch.Size([3, 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 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
tensor([2.4911e-07, 6.9332e-01, 3.4988e-02, 1.1060e-03, 2.7001e-01, 1.0901e-04, |
1.3086e-04, 3.4147e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
babies ************* |
['7 eleven', 'babies', 'sunrise', 'eating', 'feet', 'candle', 'light', 'floating'] tensor([2.4911e-07, 6.9332e-01, 3.4988e-02, 1.1060e-03, 2.7001e-01, 1.0901e-04, |
1.3086e-04, 3.4147e-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>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
tensor([1.0000e+00, 1.1294e-09, 3.5262e-10, 3.8126e-10, 2.7448e-10, 2.8880e-08, |
8.1520e-09, 1.7938e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 1.1294e-09, 3.5262e-10, 3.8126e-10, 2.7448e-10, 2.8880e-08, |
8.1520e-09, 1.7938e-09], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(8.1520e-09, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([9.1514e-01, 2.7352e-09, 8.4860e-02, 4.3807e-09, 7.1735e-12, 9.3169e-12, |
1.6396e-10, 1.3832e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.1514e-01, 2.7352e-09, 8.4860e-02, 4.3807e-09, 7.1735e-12, 9.3169e-12, |
1.6396e-10, 1.3832e-09], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9151, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0849, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.9802e-08, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Is the animal standing up?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
tensor([1.0000e+00, 9.4224e-07, 1.1134e-07, 4.2355e-12, 2.3057e-13, 5.7947e-10, |
7.1864e-11, 1.3125e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 9.4224e-07, 1.1134e-07, 4.2355e-12, 2.3057e-13, 5.7947e-10, |
7.1864e-11, 1.3125e-07], device='cuda:3', grad_fn=<SelectBackward0>) |
torch.Size([3, 3, 448, 448]) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(9.4224e-07, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.3842e-07, device='cuda:3', 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) |
torch.Size([7, 3, 448, 448]) |
question: ['Is the animal standing up?'], 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 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 |
question: ['How many birds 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: 3, images per sample: 3.0, dynamic token length: 834 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 |
tensor([1.0000e+00, 6.5659e-09, 1.6562e-09, 7.8596e-09, 4.0148e-11, 2.9864e-11, |
5.4843e-11, 1.9640e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 6.5659e-09, 1.6562e-09, 7.8596e-09, 4.0148e-11, 2.9864e-11, |
5.4843e-11, 1.9640e-09], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(1.6562e-09, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-1.6562e-09, device='cuda:0', grad_fn=<SubBackward0>)} |
tensor([1.0000e+00, 1.6374e-07, 2.6729e-08, 3.3456e-09, 4.1793e-10, 1.3838e-09, |
1.3623e-09, 9.4887e-11], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
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