text stringlengths 0 1.16k |
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1.0956e-02, 1.1236e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
white ************* |
['white', 'black', 'purple', 'orange', 'maroon', 'color', 'brown', 'dark'] tensor([9.8849e-01, 1.9141e-04, 1.0389e-06, 7.0983e-06, 3.4077e-04, 7.7501e-08, |
1.0956e-02, 1.1236e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:1', grad_fn=<DivBackward0>)} |
[2024-10-24 09:45:06,279] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.36 | optimizer_gradients: 0.32 | optimizer_step: 0.32 |
[2024-10-24 09:45:06,279] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 1177.08 | backward_microstep: 16499.65 | backward_inner_microstep: 1194.93 | backward_allreduce_microstep: 15304.57 | step_microstep: 7.65 |
[2024-10-24 09:45:06,279] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 1177.08 | backward: 16499.64 | backward_inner: 1194.96 | backward_allreduce: 15304.54 | step: 7.67 |
95%|ββββββββββ| 4585/4844 [19:03:50<1:07:25, 15.62s/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 |
Registering VQA_lavis stepRegistering EVAL step |
Registering RESULT step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='Is the penguin looking down?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
ANSWER0=VQA(image=RIGHT,question='How many monkeys are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
ANSWER0=VQA(image=RIGHT,question='Is there a single, white dog lying down in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='How many full lemons are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Is the penguin looking down?'], 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([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 |
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: 323 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 |
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, 7.9792e-09, 2.4862e-09, 1.6113e-08, 2.7383e-10, 3.5262e-10, |
2.1183e-10, 7.6924e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 7.9792e-09, 2.4862e-09, 1.6113e-08, 2.7383e-10, 3.5262e-10, |
2.1183e-10, 7.6924e-09], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(2.4862e-09, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-2.4862e-09, device='cuda:0', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many rodents are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['How many monkeys are in the image?'], responses:['2'] |
question: ['How many full lemons are in the image?'], 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']] |
[('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']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
question: ['Is there a single, white dog lying down in the image?'], responses:['yes'] |
question: ['How many rodents are in the image?'], responses:['1'] |
[('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']] |
[('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 |
torch.Size([13, 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: 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: 1861 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
tensor([9.9999e-01, 4.7923e-09, 2.0408e-10, 2.4952e-11, 7.6932e-11, 1.1738e-09, |
1.1479e-05, 2.2096e-11], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.9999e-01, 4.7923e-09, 2.0408e-10, 2.4952e-11, 7.6932e-11, 1.1738e-09, |
1.1479e-05, 2.2096e-11], device='cuda:2', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 4.4069e-08, 2.1422e-09, 1.4761e-08, 1.2573e-10, 7.0126e-10, |
8.8302e-10, 3.0151e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 4.4069e-08, 2.1422e-09, 1.4761e-08, 1.2573e-10, 7.0126e-10, |
8.8302e-10, 3.0151e-10], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.1485e-05, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(4.8223e-08, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many birds are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='How many rodents are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 7') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
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