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6.6778e-03, 1.4567e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0067, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9933, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='What are the vultures doing in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == "feeding"') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
question: ['What are the vultures doing in the image?'], responses:['standing'] |
[('standing', 0.12723967049623947), ('sitting', 0.12550921268440737), ('kneeling', 0.12533132135475653), ('floating', 0.12470854046371647), ('movement', 0.12442871056656102), ('moving', 0.12438049520499413), ('falling', 0.12421897137183824), ('leaning', 0.1241830778574868)] |
[['standing', 'sitting', 'kneeling', 'floating', 'movement', 'moving', 'falling', 'leaning']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
tensor([4.7599e-01, 4.0917e-01, 4.0512e-02, 6.2745e-02, 9.0395e-03, 1.0142e-03, |
1.4680e-03, 5.5833e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([4.7599e-01, 4.0917e-01, 4.0512e-02, 6.2745e-02, 9.0395e-03, 1.0142e-03, |
1.4680e-03, 5.5833e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0627, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9373, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([0.4617, 0.0845, 0.0195, 0.2689, 0.0872, 0.0086, 0.0616, 0.0078], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
13 ************* |
['13', '14', '21', '12', '11', '27', '15', '29'] tensor([0.4617, 0.0845, 0.0195, 0.2689, 0.0872, 0.0086, 0.0616, 0.0078], |
device='cuda:2', 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=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Is the dog on a leash?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
tensor([0.2268, 0.0807, 0.1558, 0.1937, 0.1063, 0.1438, 0.0250, 0.0679], |
device='cuda:0', grad_fn=<SoftmaxBackward0>) |
5 ************* |
['5', '8', '4', '6', '3', '7', '11', '9'] tensor([0.2268, 0.0807, 0.1558, 0.1937, 0.1063, 0.1438, 0.0250, 0.0679], |
device='cuda:0', grad_fn=<SelectBackward0>) |
torch.Size([13, 3, 448, 448]) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0929, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.9071, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Are there red oars in the image?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([7, 3, 448, 448]) |
question: ['Is the dog on a leash?'], 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([1, 3, 448, 448]) knan debug pixel values shape |
tensor([9.7220e-01, 2.7579e-02, 3.3903e-05, 3.4372e-05, 5.4000e-06, 5.4206e-05, |
5.2897e-05, 4.2456e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.7220e-01, 2.7579e-02, 3.3903e-05, 3.4372e-05, 5.4000e-06, 5.4206e-05, |
5.2897e-05, 4.2456e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0276, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9722, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0002, device='cuda:1', grad_fn=<DivBackward0>)} |
question: ['Are there red oars 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: 1861 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 |
question: ['How many dogs are in the image?'], responses:['2'] |
tensor([0.5222, 0.2609, 0.0947, 0.0365, 0.0010, 0.0425, 0.0364, 0.0058], |
device='cuda:3', grad_fn=<SoftmaxBackward0>) |
standing ************* |
['standing', 'sitting', 'kneeling', 'floating', 'movement', 'moving', 'falling', 'leaning'] tensor([0.5222, 0.2609, 0.0947, 0.0365, 0.0010, 0.0425, 0.0364, 0.0058], |
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>)} |
[('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: 7, images per sample: 7.0, dynamic token length: 1861 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
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: 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 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
tensor([6.9659e-01, 1.1711e-02, 2.9038e-01, 6.2767e-04, 5.3597e-05, 2.5049e-04, |
2.6557e-05, 3.5492e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.9659e-01, 1.1711e-02, 2.9038e-01, 6.2767e-04, 5.3597e-05, 2.5049e-04, |
2.6557e-05, 3.5492e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6966, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(0.2904, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0130, device='cuda:0', grad_fn=<SubBackward0>)} |
tensor([7.2917e-01, 1.6008e-02, 2.6299e-03, 2.5041e-01, 9.6132e-04, 4.0033e-04, |
3.9078e-04, 2.8352e-05], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([7.2917e-01, 1.6008e-02, 2.6299e-03, 2.5041e-01, 9.6132e-04, 4.0033e-04, |
3.9078e-04, 2.8352e-05], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7496, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.2504, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
[2024-10-23 14:54:57,695] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.36 | optimizer_gradients: 0.34 | optimizer_step: 0.32 |
[2024-10-23 14:54:57,696] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 5193.99 | backward_microstep: 8610.18 | backward_inner_microstep: 4840.13 | backward_allreduce_microstep: 3769.87 | step_microstep: 7.71 |
[2024-10-23 14:54:57,696] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 5193.99 | backward: 8610.17 | backward_inner: 4840.20 | backward_allreduce: 3769.81 | step: 7.72 |
1%| | 53/4844 [13:41<20:45:01, 15.59s/it]Registering VQA_lavis step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='How many blue parrots are in the image?') |
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