text stringlengths 0 1.16k |
|---|
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.8190e-09, 1.6455e-07, 5.7893e-12, 2.2407e-11, 2.7898e-09, |
1.0973e-10, 4.1977e-07], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.8190e-09, device='cuda:3', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(5.9605e-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) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
torch.Size([1, 3, 448, 448]) |
question: ['How many animals 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: 7, images per sample: 7.0, dynamic token length: 1868 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
tensor([9.5792e-01, 4.2074e-02, 8.8327e-06, 2.5893e-10, 1.9518e-07, 3.1423e-08, |
2.9628e-09, 4.4483e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
4 ************* |
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([9.5792e-01, 4.2074e-02, 8.8327e-06, 2.5893e-10, 1.9518e-07, 3.1423e-08, |
2.9628e-09, 4.4483e-09], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(8.8327e-06, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 |
tensor([9.9930e-01, 4.3034e-04, 5.7114e-07, 2.8110e-06, 2.1668e-09, 2.6108e-04, |
9.1248e-07, 3.1971e-08], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([9.9930e-01, 4.3034e-04, 5.7114e-07, 2.8110e-06, 2.1668e-09, 2.6108e-04, |
9.1248e-07, 3.1971e-08], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 3.1414e-07, 5.4190e-10, 5.6661e-08, 5.6348e-10, 1.9556e-08, |
1.4416e-09, 4.4267e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 3.1414e-07, 5.4190e-10, 5.6661e-08, 5.6348e-10, 1.9556e-08, |
1.4416e-09, 4.4267e-08], device='cuda:2', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 2.9171e-09, 7.5077e-11, 3.1017e-09, 2.4233e-10, 3.8949e-11, |
2.0148e-11, 1.1371e-08], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.9171e-09, 7.5077e-11, 3.1017e-09, 2.4233e-10, 3.8949e-11, |
2.0148e-11, 1.1371e-08], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0003, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9997, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Are the animals on a snowy rocky cliff?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:0', grad_fn=<DivBackward0>), False: tensor(7.5077e-11, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(-7.5077e-11, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(5.4190e-10, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(4.7630e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many chimneys are visible in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Are the animals on a snowy rocky cliff?'], 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 |
tensor([1.0000e+00, 2.9694e-10, 1.6422e-07, 2.3759e-12, 2.0868e-12, 3.7498e-09, |
7.4354e-10, 5.0278e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 2.9694e-10, 1.6422e-07, 2.3759e-12, 2.0868e-12, 3.7498e-09, |
7.4354e-10, 5.0278e-07], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.9694e-10, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
question: ['How many dogs are in the image?'], responses:['δΈ'] |
question: ['How many chimneys are visible 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']] |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
tensor([1.5087e-04, 1.0099e-03, 3.0441e-02, 8.2350e-01, 1.0539e-01, 1.7582e-02, |
2.1231e-03, 1.9803e-02], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
bulldog ************* |
['biking', 'geese', 'cushion', 'bulldog', 'striped', 'floral', 'stove', 'dodgers'] tensor([1.5087e-04, 1.0099e-03, 3.0441e-02, 8.2350e-01, 1.0539e-01, 1.7582e-02, |
2.1231e-03, 1.9803e-02], 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([9.9990e-01, 8.4807e-05, 1.1478e-05, 2.6993e-07, 1.5622e-07, 5.2328e-08, |
3.6894e-07, 6.0810e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9990e-01, 8.4807e-05, 1.1478e-05, 2.6993e-07, 1.5622e-07, 5.2328e-08, |
3.6894e-07, 6.0810e-09], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), False: tensor(2.6993e-07, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-2.3842e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
[2024-10-24 09:51:11,569] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.35 | optimizer_gradients: 0.39 | optimizer_step: 0.33 |
[2024-10-24 09:51:11,569] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 7052.62 | backward_microstep: 6875.85 | backward_inner_microstep: 6715.71 | backward_allreduce_microstep: 160.04 | step_microstep: 8.03 |
[2024-10-24 09:51:11,569] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 7052.62 | backward: 6875.84 | backward_inner: 6715.73 | backward_allreduce: 160.03 | step: 8.04 |
95%|ββββββββββ| 4608/4844 [19:09:55<1:00:02, 15.26s/it]Registering VQA_lavis step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
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