text stringlengths 0 1.16k |
|---|
Registering RESULT step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=LEFT,question='Is the white dog lying in the grass?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='Is the dog's tail up and curled over its back?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='How many tubes filled with liquid are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} > 5') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Is the dog in the image standing up on all four feet?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
torch.Size([3, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
question: ['Is the dog'], responses:['yes'] |
question: ['How many tubes filled with liquid are in the image?'], responses:['1'] |
[('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']] |
[('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 |
torch.Size([3, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
question: ['Is the white dog lying in the grass?'], responses:['yes'] |
question: ['Is the dog in the image standing up on all four feet?'], 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: 3, images per sample: 3.0, dynamic token length: 839 |
[('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: 3, images per sample: 3.0, dynamic token length: 839 |
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: 3, images per sample: 3.0, dynamic token length: 839 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
tensor([9.9997e-01, 5.6816e-08, 2.7538e-05, 1.4572e-07, 1.9957e-09, 1.7805e-08, |
3.6783e-08, 2.0801e-06], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.9997e-01, 5.6816e-08, 2.7538e-05, 1.4572e-07, 1.9957e-09, 1.7805e-08, |
3.6783e-08, 2.0801e-06], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([7.5520e-01, 1.3748e-04, 1.9696e-06, 1.6764e-07, 1.7341e-07, 6.2245e-07, |
2.4466e-01, 9.6479e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([7.5520e-01, 1.3748e-04, 1.9696e-06, 1.6764e-07, 1.7341e-07, 6.2245e-07, |
2.4466e-01, 9.6479e-09], device='cuda:0', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(9.7315e-07, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(2.7538e-05, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.2644e-06, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 5') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
question: ['How many animals are in the image?'], responses:['five'] |
question: ['How many dogs are in the image?'], responses:['2'] |
[('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']] |
[('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]) 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 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
tensor([1.0000e+00, 3.9593e-09, 5.9391e-11, 5.3029e-09, 3.0567e-11, 9.6401e-11, |
3.4607e-11, 5.5450e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 3.9593e-09, 5.9391e-11, 5.3029e-09, 3.0567e-11, 9.6401e-11, |
3.4607e-11, 5.5450e-09], device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(5.9391e-11, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-5.9391e-11, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Which direction are the dogs heading?') |
ANSWER1=EVAL(expr='{ANSWER0} == "right"') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
tensor([1.0000e+00, 3.7652e-09, 2.5651e-09, 4.0091e-09, 1.0586e-10, 2.4374e-11, |
3.8282e-11, 3.5324e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 3.7652e-09, 2.5651e-09, 4.0091e-09, 1.0586e-10, 2.4374e-11, |
3.8282e-11, 3.5324e-09], device='cuda:3', grad_fn=<SelectBackward0>) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
torch.Size([7, 3, 448, 448]) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), False: tensor(2.5651e-09, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-2.5651e-09, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many puppies are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
question: ['How many puppies are in the image?'], responses:['7'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
[('7', 0.12828776251745355), ('8', 0.1258361832781132), ('11', 0.12481772898325143), ('5', 0.124759881092759), ('9', 0.12447036165452931), ('10', 0.1239759375399529), ('6', 0.12393017600998846), ('12', 0.12392196892395223)] |
[['7', '8', '11', '5', '9', '10', '6', '12']] |
torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.