text stringlengths 0 1.16k |
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1.4293e-10, 1.5176e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.0467e-08, 1.7610e-07, 1.6848e-12, 1.7167e-12, 3.8120e-10, |
1.4293e-10, 1.5176e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0467e-08, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.3842e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
torch.Size([13, 3, 448, 448]) |
ANSWER0=VQA(image=RIGHT,question='How many elephants are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
tensor([1.0000e+00, 4.1137e-09, 6.6916e-10, 1.1930e-08, 2.5543e-11, 6.1276e-11, |
1.0777e-10, 3.1360e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 4.1137e-09, 6.6916e-10, 1.1930e-08, 2.5543e-11, 6.1276e-11, |
1.0777e-10, 3.1360e-09], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(6.6916e-10, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-6.6916e-10, device='cuda:1', grad_fn=<SubBackward0>)} |
question: ['How many elephants are in the image?'], responses:['δΈ'] |
[('biking', 0.12639990046765587), ('geese', 0.1262789403477572), ('cushion', 0.1253965842661667), ('bulldog', 0.1252365705078606), ('striped', 0.12499404846420245), ('floral', 0.12444127054742124), ('stove', 0.12381223353082338), ('dodgers', 0.12344045186811266)] |
[['biking', 'geese', 'cushion', 'bulldog', 'striped', 'floral', 'stove', 'dodgers']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
question: ['How many dogs 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: 7, images per sample: 7.0, dynamic token length: 1862 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
tensor([1.3255e-04, 3.7292e-03, 3.7054e-02, 7.8710e-01, 1.0410e-01, 5.1435e-02, |
1.0993e-02, 5.4574e-03], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
bulldog ************* |
['biking', 'geese', 'cushion', 'bulldog', 'striped', 'floral', 'stove', 'dodgers'] tensor([1.3255e-04, 3.7292e-03, 3.7054e-02, 7.8710e-01, 1.0410e-01, 5.1435e-02, |
1.0993e-02, 5.4574e-03], 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>)} |
tensor([1.0000e+00, 2.2067e-10, 7.9920e-11, 2.7677e-10, 1.4026e-10, 1.6986e-08, |
3.0225e-09, 2.2232e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 2.2067e-10, 7.9920e-11, 2.7677e-10, 1.4026e-10, 1.6986e-08, |
3.0225e-09, 2.2232e-10], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(3.0225e-09, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
[2024-10-24 10:09:44,826] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.40 | optimizer_gradients: 0.30 | optimizer_step: 0.32 |
[2024-10-24 10:09:44,827] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 7121.68 | backward_microstep: 10590.84 | backward_inner_microstep: 6741.30 | backward_allreduce_microstep: 3849.34 | step_microstep: 7.55 |
[2024-10-24 10:09:44,827] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 7121.70 | backward: 10590.83 | backward_inner: 6741.39 | backward_allreduce: 3849.23 | step: 7.57 |
97%|ββββββββββ| 4681/4844 [19:28:28<43:03, 15.85s/it]Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 7') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Is there at least one book with its pages splayed open in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='Does the left image show water buffalo upright in water?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
ANSWER0=VQA(image=RIGHT,question='Does the image on the right have a horse with a red tassel on its head?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([5, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many dogs are in the image?'], responses:['100'] |
[('100', 0.1277092174007614), ('120', 0.12519936731884676), ('88', 0.12483671971182599), ('80', 0.12474858811112934), ('60', 0.12457749608485191), ('99', 0.1243465850330014), ('90', 0.12430147627057883), ('101', 0.12428055006900451)] |
[['100', '120', '88', '80', '60', '99', '90', '101']] |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
question: ['Is there at least one book with its pages splayed open in the image?'], responses:['yes'] |
question: ['Does the left image show water buffalo upright in 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']] |
[('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: 1868 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 |
question: ['Does the image on the right have a horse with a red tassel on its head?'], responses:['no'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 |
[('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: 1869 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 |
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