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FINAL_ANSWER=RESULT(var=ANSWER0) |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=LEFT,question='How many laptops are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Do the sails in the image have the color white on them?') |
ANSWER1=EVAL(expr='not {ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='Does the dessert contain any berries?') |
ANSWER1=EVAL(expr='not {ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many laptops are in the image?'], responses:['3'] |
[('3', 0.12809209985493852), ('4', 0.12520382509374006), ('1', 0.1251059160028928), ('5', 0.12483070991268265), ('8', 0.12458076282181878), ('2', 0.12413212281858195), ('6', 0.1241125313968017), ('12', 0.12394203209854344)] |
[['3', '4', '1', '5', '8', '2', '6', '12']] |
torch.Size([3, 3, 448, 448]) knan debug pixel values shape |
question: ['Does the dessert contain any berries?'], responses:['yes'] |
question: ['Do the sails in the image have the color white on them?'], 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([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: 1866 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 |
tensor([0.5932, 0.1097, 0.0356, 0.0196, 0.0021, 0.2318, 0.0068, 0.0011], |
device='cuda:3', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([0.5932, 0.1097, 0.0356, 0.0196, 0.0021, 0.2318, 0.0068, 0.0011], |
device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0356, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9644, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT, question='Is the dog wearing a harness?') |
FINAL_ANSWER = RESULT(var=ANSWER0) |
question: ['Does the dog in the image have a white coat?'], responses:['no'] |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
[('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: 7, images per sample: 7.0, dynamic token length: 1866 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
question: ['Is the dog wearing a harness?'], 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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
tensor([7.6868e-01, 1.7232e-02, 2.0781e-01, 2.8497e-03, 1.2339e-04, 3.1190e-04, |
4.8959e-05, 2.9434e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([7.6868e-01, 1.7232e-02, 2.0781e-01, 2.8497e-03, 1.2339e-04, 3.1190e-04, |
4.8959e-05, 2.9434e-03], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([9.4304e-01, 5.6634e-02, 2.3563e-06, 2.6785e-05, 4.5315e-05, 7.5459e-05, |
1.6648e-04, 1.2067e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.4304e-01, 5.6634e-02, 2.3563e-06, 2.6785e-05, 4.5315e-05, 7.5459e-05, |
1.6648e-04, 1.2067e-05], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.2078, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.7687, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0235, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many skunks are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9430, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0566, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Does the image contain a flower?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([3, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many skunks 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([3, 3, 448, 448]) knan debug pixel values shape |
tensor([7.8345e-01, 3.0453e-02, 1.1172e-02, 3.2084e-03, 4.9726e-03, 2.3467e-03, |
1.6422e-01, 1.8040e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([7.8345e-01, 3.0453e-02, 1.1172e-02, 3.2084e-03, 4.9726e-03, 2.3467e-03, |
1.6422e-01, 1.8040e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7834, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.2166, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([8.4402e-01, 1.5759e-02, 1.3802e-01, 1.0184e-03, 7.0835e-05, 2.1972e-04, |
3.7571e-05, 8.4723e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.4402e-01, 1.5759e-02, 1.3802e-01, 1.0184e-03, 7.0835e-05, 2.1972e-04, |
3.7571e-05, 8.4723e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8440, device='cuda:3', grad_fn=<UnbindBackward0>), False: tensor(0.1380, device='cuda:3', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0180, device='cuda:3', grad_fn=<SubBackward0>)} |
question: ['Does the image contain a flower?'], 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: 3395 |
tensor([6.4705e-01, 3.5145e-01, 5.1719e-05, 1.1306e-04, 1.1151e-04, 8.5857e-04, |
2.9080e-04, 7.2111e-05], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([6.4705e-01, 3.5145e-01, 5.1719e-05, 1.1306e-04, 1.1151e-04, 8.5857e-04, |
2.9080e-04, 7.2111e-05], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.3515, device='cuda:2', grad_fn=<UnbindBackward0>), False: tensor(0.6470, device='cuda:2', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0015, device='cuda:2', grad_fn=<SubBackward0>)} |
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