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ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.9994, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(-5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Does the elephant have tusks in the image?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([3, 3, 448, 448]) |
question: ['Does the elephant have tusks 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']] |
torch.Size([3, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
tensor([1.0000e+00, 3.6955e-10, 3.0722e-07, 7.3603e-13, 1.0428e-12, 6.1346e-10, |
1.1717e-10, 3.0149e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 3.6955e-10, 3.0722e-07, 7.3603e-13, 1.0428e-12, 6.1346e-10, |
1.1717e-10, 3.0149e-07], device='cuda:3', grad_fn=<SelectBackward0>) |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
question: ['How many guinea pigs are in the image?'], responses:['2'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(3.6955e-10, device='cuda:3', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(7.1526e-07, device='cuda:3', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['How many mirrors hang over the sinks?'], responses:['1'] |
[('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']] |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
torch.Size([13, 3, 448, 448]) |
[('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: 3, images per sample: 3.0, dynamic token length: 838 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 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 |
tensor([1.0000e+00, 1.3101e-09, 3.8461e-07, 1.3027e-08, 4.0267e-09, 2.9146e-07, |
6.8062e-09, 2.8290e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.3101e-09, 3.8461e-07, 1.3027e-08, 4.0267e-09, 2.9146e-07, |
6.8062e-09, 2.8290e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.3101e-09, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(9.5367e-07, device='cuda:0', grad_fn=<SubBackward0>)} |
question: ['How many animals are in the image?'], responses:['five'] |
[('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']] |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 4.4069e-08, 5.1817e-09, 1.1496e-08, 3.7244e-10, 7.1570e-10, |
5.9269e-10, 2.5168e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 4.4069e-08, 5.1817e-09, 1.1496e-08, 3.7244e-10, 7.1570e-10, |
5.9269e-10, 2.5168e-10], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.1496e-08, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the skunk being bottle fed?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
tensor([1.0000e+00, 2.7249e-10, 5.2413e-11, 3.7747e-11, 8.1815e-11, 4.1588e-09, |
4.2714e-08, 4.7128e-11], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 2.7249e-10, 5.2413e-11, 3.7747e-11, 8.1815e-11, 4.1588e-09, |
4.2714e-08, 4.7128e-11], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(4.2714e-08, 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>)} |
ANSWER0=VQA(image=RIGHT,question='How many seals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 4') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['How many seals 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([7, 3, 448, 448]) knan debug pixel values shape |
tensor([4.8860e-09, 6.9432e-01, 7.3709e-03, 3.5314e-04, 2.9690e-01, 1.3714e-04, |
8.1501e-04, 1.0673e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
babies ************* |
['7 eleven', 'babies', 'sunrise', 'eating', 'feet', 'candle', 'light', 'floating'] question: ['Is the skunk being bottle fed?'], responses:['yes'] |
tensor([4.8860e-09, 6.9432e-01, 7.3709e-03, 3.5314e-04, 2.9690e-01, 1.3714e-04, |
8.1501e-04, 1.0673e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:3', grad_fn=<DivBackward0>)} |
[('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 |
tensor([9.9795e-01, 2.0515e-03, 1.0146e-07, 3.6835e-07, 2.0316e-10, 2.5414e-08, |
1.6519e-09, 2.9078e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([9.9795e-01, 2.0515e-03, 1.0146e-07, 3.6835e-07, 2.0316e-10, 2.5414e-08, |
1.6519e-09, 2.9078e-08], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(3.9928e-07, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
tensor([1.0000e+00, 1.7053e-08, 4.9445e-09, 2.1387e-08, 5.1298e-12, 1.1997e-10, |
7.2086e-11, 1.5514e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.7053e-08, 4.9445e-09, 2.1387e-08, 5.1298e-12, 1.1997e-10, |
7.2086e-11, 1.5514e-09], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(4.9445e-09, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-4.9445e-09, device='cuda:1', grad_fn=<SubBackward0>)} |
[2024-10-24 09:49:22,482] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.36 | optimizer_gradients: 0.33 | optimizer_step: 0.33 |
[2024-10-24 09:49:22,483] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 1837.13 | backward_microstep: 15906.06 | backward_inner_microstep: 1697.06 | backward_allreduce_microstep: 14208.75 | step_microstep: 7.80 |
[2024-10-24 09:49:22,483] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 1837.13 | backward: 15906.05 | backward_inner: 1697.20 | backward_allreduce: 14208.71 | step: 7.82 |
95%|ββββββββββ| 4601/4844 [19:08:06<1:05:13, 16.11s/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 |
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