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FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Is there a person standing on the shore in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Is there a plant in one of the vases?'], responses:['no'] |
question: ['Does the left image contain a skunk in a basket?'], responses:['yes'] |
question: ['Is there a person standing on the shore in the image?'], 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']] |
[('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 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
question: ['What does the left image feature?'], responses:['crate'] |
[('container', 0.125207830016166), ('shelf', 0.12504824405139073), ('vase', 0.12501535136974068), ('garage', 0.12498380890170739), ('bowl', 0.12494915675837098), ('bowls', 0.12494551238489669), ('milk', 0.12494145928280445), ('glass', 0.12490863723492313)] |
[['container', 'shelf', 'vase', 'garage', 'bowl', 'bowls', 'milk', 'glass']] |
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 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
tensor([1.0000e+00, 1.7456e-10, 9.9262e-07, 7.2049e-12, 1.3951e-11, 1.7354e-08, |
1.0917e-09, 9.5182e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.7456e-10, 9.9262e-07, 7.2049e-12, 1.3951e-11, 1.7354e-08, |
1.0917e-09, 9.5182e-07], device='cuda:2', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 1.2502e-09, 7.3369e-07, 1.4616e-09, 1.0731e-08, 5.2357e-07, |
1.1489e-08, 3.7069e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.2502e-09, 7.3369e-07, 1.4616e-09, 1.0731e-08, 5.2357e-07, |
1.1489e-08, 3.7069e-07], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 1.5780e-09, 1.0587e-10, 6.7713e-09, 3.7967e-11, 5.4498e-11, |
2.4675e-11, 7.3543e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.5780e-09, 1.0587e-10, 6.7713e-09, 3.7967e-11, 5.4498e-11, |
2.4675e-11, 7.3543e-09], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.7456e-10, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.9073e-06, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the banana flower purple?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 3, 448, 448]) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0587e-10, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.0587e-10, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Are the boats in the water?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.2502e-09, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.6689e-06, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many syringes are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
question: ['How many syringes 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([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
question: ['Is the banana flower purple?'], 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']] |
tensor([1.0000e+00, 7.9979e-09, 5.3455e-09, 1.7038e-08, 4.5985e-09, 2.0354e-07, |
5.1616e-08, 2.8776e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 7.9979e-09, 5.3455e-09, 1.7038e-08, 4.5985e-09, 2.0354e-07, |
5.1616e-08, 2.8776e-09], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
question: ['Are the boats in the water?'], 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: 13, images per sample: 13.0, dynamic token length: 3395 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([9.9242e-01, 4.6165e-09, 7.5771e-03, 6.1081e-09, 8.8551e-12, 1.8838e-11, |
5.4787e-11, 3.8732e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.9242e-01, 4.6165e-09, 7.5771e-03, 6.1081e-09, 8.8551e-12, 1.8838e-11, |
5.4787e-11, 3.8732e-09], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9924, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.0076, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.6298e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
tensor([0.0795, 0.0592, 0.1484, 0.0099, 0.0420, 0.6194, 0.0343, 0.0074], |
device='cuda:0', grad_fn=<SoftmaxBackward0>) |
bowls ************* |
['container', 'shelf', 'vase', 'garage', 'bowl', 'bowls', 'milk', 'glass'] tensor([0.0795, 0.0592, 0.1484, 0.0099, 0.0420, 0.6194, 0.0343, 0.0074], |
device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is there a clown fish in the image?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([7, 3, 448, 448]) |
question: ['Is there a clown fish in the image?'], 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([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
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