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ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.8554e-07, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many chimpanzees are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
tensor([1.0000e+00, 1.4761e-08, 3.7910e-09, 1.5230e-08, 1.5724e-10, 3.5809e-10, |
3.9624e-10, 1.0693e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 1.4761e-08, 3.7910e-09, 1.5230e-08, 1.5724e-10, 3.5809e-10, |
3.9624e-10, 1.0693e-10], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([5.0626e-01, 1.8403e-01, 3.0855e-01, 3.4714e-06, 7.5653e-04, 2.9221e-06, |
3.8272e-04, 1.0857e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
4 ************* |
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([5.0626e-01, 1.8403e-01, 3.0855e-01, 3.4714e-06, 7.5653e-04, 2.9221e-06, |
3.8272e-04, 1.0857e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
torch.Size([7, 3, 448, 448]) |
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>)} |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0008, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9992, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many bulldogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
question: ['How many chimpanzees 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([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
question: ['How many bulldogs are in the image?'], responses:['δΈ'] |
question: ['How many dogs are in the image?'], responses:['2'] |
[('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']] |
[('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: 13, images per sample: 13.0, dynamic token length: 3402 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 1.4703e-06, 9.4237e-08, 7.7842e-10, 9.3962e-08, 6.1537e-09, |
8.8761e-08, 1.4669e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
0 ************* |
['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle'] tensor([1.0000e+00, 1.4703e-06, 9.4237e-08, 7.7842e-10, 9.3962e-08, 6.1537e-09, |
8.8761e-08, 1.4669e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.0266e-06, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many items are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
question: ['How many items are in the image?'], responses:['4'] |
[('4', 0.12804651361935848), ('5', 0.12521071898947128), ('3', 0.12515925906184908), ('8', 0.12489091845155219), ('6', 0.1245383468146311), ('1', 0.12441141527606933), ('2', 0.12403713327181662), ('11', 0.12370569451525179)] |
[['4', '5', '3', '8', '6', '1', '2', '11']] |
torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
tensor([1.0000e+00, 4.2713e-08, 2.2510e-08, 6.4992e-09, 6.7968e-10, 5.8948e-09, |
1.7898e-09, 1.6046e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 4.2713e-08, 2.2510e-08, 6.4992e-09, 6.7968e-10, 5.8948e-09, |
1.7898e-09, 1.6046e-09], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(8.1690e-08, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 |
tensor([5.5446e-01, 1.6955e-03, 4.4381e-01, 1.0993e-07, 1.1342e-05, 1.8911e-05, |
2.7977e-06, 3.3384e-06], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
4 ************* |
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([5.5446e-01, 1.6955e-03, 4.4381e-01, 1.0993e-07, 1.1342e-05, 1.8911e-05, |
2.7977e-06, 3.3384e-06], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.8911e-05, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
tensor([9.9995e-01, 4.5398e-05, 2.3222e-08, 7.2655e-08, 1.6114e-09, 3.0396e-10, |
1.2199e-09, 2.7676e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9995e-01, 4.5398e-05, 2.3222e-08, 7.2655e-08, 1.6114e-09, 3.0396e-10, |
1.2199e-09, 2.7676e-10], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(7.2655e-08, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([2.5611e-04, 3.9105e-03, 7.1659e-02, 6.1221e-01, 1.9844e-01, 6.1424e-02, |
8.2924e-03, 4.3812e-02], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
bulldog ************* |
['biking', 'geese', 'cushion', 'bulldog', 'striped', 'floral', 'stove', 'dodgers'] tensor([2.5611e-04, 3.9105e-03, 7.1659e-02, 6.1221e-01, 1.9844e-01, 6.1424e-02, |
8.2924e-03, 4.3812e-02], 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>)} |
[2024-10-24 09:31:14,482] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.43 | optimizer_gradients: 0.42 | optimizer_step: 0.35 |
[2024-10-24 09:31:14,482] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 5067.99 | backward_microstep: 8815.20 | backward_inner_microstep: 4956.06 | backward_allreduce_microstep: 3859.02 | step_microstep: 8.02 |
[2024-10-24 09:31:14,482] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 5068.00 | backward: 8815.19 | backward_inner: 4956.09 | backward_allreduce: 3858.94 | step: 8.03 |
93%|ββββββββββ| 4529/4844 [18:49:58<1:17:40, 14.79s/it]Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='Is a human at least partially visible in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
Registering VQA_lavis step |
Registering EVAL step |
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