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FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='How many convertible vehicles are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([3, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
ANSWER0=VQA(image=LEFT,question='How many warthogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['How many convertible vehicles 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']] |
torch.Size([3, 3, 448, 448]) knan debug pixel values shape |
question: ['Does the dessert contain berries?'], 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']] |
question: ['How many warthogs 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([7, 3, 448, 448]) knan debug pixel values shape |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 3.5410e-08, 2.2159e-08, 1.1677e-08, 2.0408e-10, 2.7094e-09, |
5.8137e-10, 3.9030e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 3.5410e-08, 2.2159e-08, 1.1677e-08, 2.0408e-10, 2.7094e-09, |
5.8137e-10, 3.9030e-10], device='cuda:3', grad_fn=<SelectBackward0>) |
question: ['Do the windows in the image have dark brown shades?'], responses:['no'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(7.3132e-08, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many pump-top products are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
[('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']] |
question: ['How many pump-top products are in the image?'], responses:['11'] |
[('11', 0.12740768001087358), ('10', 0.12548679249075975), ('12', 0.12538137681693887), ('9', 0.12485855662563465), ('8', 0.12469919178932766), ('13', 0.12431757055023795), ('7', 0.12396146028399917), ('14', 0.1238873714322284)] |
[['11', '10', '12', '9', '8', '13', '7', '14']] |
torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
tensor([8.6833e-01, 1.7985e-02, 8.0722e-02, 2.6202e-02, 5.7861e-04, 2.0208e-03, |
3.5469e-03, 6.1701e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
11 ************* |
['11', '10', '12', '9', '8', '13', '7', '14'] tensor([8.6833e-01, 1.7985e-02, 8.0722e-02, 2.6202e-02, 5.7861e-04, 2.0208e-03, |
3.5469e-03, 6.1701e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), False: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400 |
tensor([1.0000e+00, 2.3860e-10, 5.2411e-07, 2.3209e-12, 5.8560e-13, 3.8695e-09, |
1.3810e-10, 1.6022e-06], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 2.3860e-10, 5.2411e-07, 2.3209e-12, 5.8560e-13, 3.8695e-09, |
1.3810e-10, 1.6022e-06], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(2.3860e-10, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.0266e-06, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many pigs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
tensor([1.0000e+00, 3.6098e-10, 4.3622e-11, 1.1313e-10, 6.2423e-11, 5.5986e-09, |
5.9641e-09, 3.5924e-11], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 3.6098e-10, 4.3622e-11, 1.1313e-10, 6.2423e-11, 5.5986e-09, |
5.9641e-09, 3.5924e-11], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.2179e-08, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
ANSWER0=VQA(image=RIGHT,question='Is a human petting a stingray in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
question: ['How many pigs are in the image?'], responses:['50'] |
[('50', 0.12746329354121594), ('51', 0.12494443111915052), ('60', 0.12471995183640609), ('55', 0.12470016949940634), ('54', 0.12460076157014638), ('52', 0.12454269500997545), ('44', 0.12453681395238846), ('48', 0.1244918834713108)] |
[['50', '51', '60', '55', '54', '52', '44', '48']] |
question: ['Is a human petting a stingray in the image?'], responses:['no'] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
[('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: 13, images per sample: 13.0, dynamic token length: 3400 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400 |
tensor([1.0000e+00, 2.4862e-09, 7.5452e-08, 1.7383e-12, 1.6980e-12, 1.6171e-10, |
1.6814e-10, 1.9596e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 2.4862e-09, 7.5452e-08, 1.7383e-12, 1.6980e-12, 1.6171e-10, |
1.6814e-10, 1.9596e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.4862e-09, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(3.5763e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many glasses of wine are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
tensor([0.9621, 0.0012, 0.0121, 0.0175, 0.0022, 0.0013, 0.0013, 0.0023], |
device='cuda:1', grad_fn=<SoftmaxBackward0>) |
50 ************* |
['50', '51', '60', '55', '54', '52', '44', '48'] tensor([0.9621, 0.0012, 0.0121, 0.0175, 0.0022, 0.0013, 0.0013, 0.0023], |
device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([1.0000e+00, 2.5398e-10, 6.0037e-07, 2.4752e-12, 3.5059e-10, 7.0145e-09, |
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