text stringlengths 0 1.16k |
|---|
[2024-10-23 14:52:33,068] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 5138.80 | backward: 7564.77 | backward_inner: 4963.62 | backward_allreduce: 2601.06 | step: 7.73 |
1%| | 44/4844 [11:16<20:32:33, 15.41s/it]Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='Is the dog wearing a collar?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Is there a person in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=LEFT,question='How many predominately red birds are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
ANSWER0=VQA(image=LEFT,question='How many dogs are standing on all fours in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
question: ['How many predominately red birds 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']] |
torch.Size([3, 3, 448, 448]) knan debug pixel values shape |
question: ['Is the dog wearing a collar?'], responses:['no'] |
question: ['Is there a person in the image?'], responses:['yes'] |
[('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']] |
[('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 |
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: 1863 |
tensor([0.7460, 0.0576, 0.0255, 0.0066, 0.0113, 0.0053, 0.1469, 0.0008], |
device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([0.7460, 0.0576, 0.0255, 0.0066, 0.0113, 0.0053, 0.1469, 0.0008], |
device='cuda:1', grad_fn=<SelectBackward0>) |
最后的概率分布为: {True: tensor(0.7460, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.2540, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How are the pencils laying?') |
ANSWER1=EVAL(expr='{ANSWER0} == "points facing down and slightly left"') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
torch.Size([13, 3, 448, 448]) |
question: ['How many dogs are standing on all fours in the image?'], responses:['0'] |
[('0', 0.13077743594303964), ('circles', 0.12449813349255197), ('maroon', 0.12428926693968681), ('large', 0.1242263466991631), ('rooster', 0.12409315512763705), ('nuts', 0.12408018414184876), ('beige', 0.1240288472550799), ('bottle', 0.12400663040099273)] |
[['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle']] |
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: 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: 1861 |
question: ['How are the pencils laying?'], responses:['in'] |
tensor([6.5466e-01, 1.7354e-02, 3.2525e-01, 1.1695e-03, 1.2970e-04, 6.0262e-04, |
7.4140e-05, 7.6809e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.5466e-01, 1.7354e-02, 3.2525e-01, 1.1695e-03, 1.2970e-04, 6.0262e-04, |
7.4140e-05, 7.6809e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
tensor([8.8642e-01, 1.1281e-01, 6.5973e-05, 1.0435e-04, 2.8497e-05, 2.8058e-04, |
2.0371e-04, 8.6523e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([8.8642e-01, 1.1281e-01, 6.5973e-05, 1.0435e-04, 2.8497e-05, 2.8058e-04, |
2.0371e-04, 8.6523e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
最后的概率分布为: {True: tensor(0.6547, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.3252, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)} |
最后的概率分布为: {True: tensor(0.1128, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.8864, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0008, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the hog on the right image facing left?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Is there a female in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('in', 0.12653170127573085), ('on', 0.12523252646732688), ('grill', 0.12489620059528794), ('diamond', 0.12481047348484683), ('dome', 0.12465643787718596), ('opaque', 0.1246316849007534), ('focus', 0.12462272792755001), ('fireplace', 0.12461824747131818)] |
[['in', 'on', 'grill', 'diamond', 'dome', 'opaque', 'focus', 'fireplace']] |
torch.Size([7, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
question: ['Is there a female 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 |
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 |
question: ['Is the hog on the right image facing left?'], responses:['no'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
[('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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.