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torch.Size([7, 3, 448, 448]) |
question: ['How many wartgogs are in the image?'], responses:['2'] |
question: ['Are there human shoes in the image?'], responses:['yes'] |
[('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']] |
[('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']] |
question: ['Is there a human 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([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 |
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 |
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: 1860 |
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: 1861 |
tensor([9.8069e-01, 3.3224e-03, 1.3009e-03, 7.1355e-04, 8.3917e-04, 7.4056e-04, |
1.2345e-02, 4.5537e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.8069e-01, 3.3224e-03, 1.3009e-03, 7.1355e-04, 8.3917e-04, 7.4056e-04, |
1.2345e-02, 4.5537e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9807, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0193, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
ANSWER0=VQA(image=RIGHT,question='How many flutes are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
tensor([5.6839e-01, 1.3296e-02, 4.1583e-01, 1.2452e-03, 9.2142e-05, 2.8583e-04, |
1.0014e-04, 7.6515e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([5.6839e-01, 1.3296e-02, 4.1583e-01, 1.2452e-03, 9.2142e-05, 2.8583e-04, |
1.0014e-04, 7.6515e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([7.9735e-01, 7.4164e-02, 1.9960e-02, 9.5227e-02, 7.8161e-03, 2.4578e-03, |
2.7859e-03, 2.3926e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([7.9735e-01, 7.4164e-02, 1.9960e-02, 9.5227e-02, 7.8161e-03, 2.4578e-03, |
2.7859e-03, 2.3926e-04], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.5684, device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(0.4158, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0158, device='cuda:1', grad_fn=<SubBackward0>)} |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8926, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.1074, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
tensor([9.8388e-01, 1.5903e-02, 2.6520e-05, 1.6176e-05, 4.4509e-05, 5.0123e-05, |
4.4911e-05, 3.5689e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.8388e-01, 1.5903e-02, 2.6520e-05, 1.6176e-05, 4.4509e-05, 5.0123e-05, |
4.4911e-05, 3.5689e-05], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9839, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many animals are eating in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
question: ['How many animals are eating 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 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
question: ['How many flutes are in the image?'], responses:['20'] |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
[('20', 0.12771895156791702), ('21', 0.12586912554208884), ('22', 0.12503044546440548), ('26', 0.12459144863554222), ('30', 0.1243482131473721), ('48', 0.12418849501124658), ('27', 0.12415656019926104), ('28', 0.12409676043216668)] |
[['20', '21', '22', '26', '30', '48', '27', '28']] |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([7.4770e-01, 2.8991e-02, 6.2698e-03, 2.1419e-01, 1.6354e-03, 5.8251e-04, |
5.8275e-04, 4.5233e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([7.4770e-01, 2.8991e-02, 6.2698e-03, 2.1419e-01, 1.6354e-03, 5.8251e-04, |
5.8275e-04, 4.5233e-05], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7477, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.2523, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)} |
tensor([0.3613, 0.1039, 0.1067, 0.0821, 0.1804, 0.0445, 0.0653, 0.0558], |
device='cuda:3', grad_fn=<SoftmaxBackward0>) |
20 ************* |
['20', '21', '22', '26', '30', '48', '27', '28'] tensor([0.3613, 0.1039, 0.1067, 0.0821, 0.1804, 0.0445, 0.0653, 0.0558], |
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>)} |
ANSWER0=VQA(image=RIGHT,question='How many monkeys are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
question: ['How many monkeys 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 |
tensor([9.5361e-01, 1.4481e-02, 1.8995e-03, 2.8798e-02, 6.3612e-04, 2.6437e-04, |
2.9074e-04, 2.4836e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.5361e-01, 1.4481e-02, 1.8995e-03, 2.8798e-02, 6.3612e-04, 2.6437e-04, |
2.9074e-04, 2.4836e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0288, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9712, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
[2024-10-22 17:31:05,384] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.35 | optimizer_gradients: 0.32 | optimizer_step: 0.32 |
[2024-10-22 17:31:05,384] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 8875.86 | backward_microstep: 16588.31 | backward_inner_microstep: 8345.61 | backward_allreduce_microstep: 8242.64 | step_microstep: 7.74 |
[2024-10-22 17:31:05,385] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 8875.88 | backward: 16588.30 | backward_inner: 8345.62 | backward_allreduce: 8242.63 | step: 7.76 |
1%|β | 32/2424 [12:37<14:50:36, 22.34s/it]Registering VQA_lavis step |
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