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[2024-10-22 17:29:57,734] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 9577.56 | backward: 10443.30 | backward_inner: 9040.79 | backward_allreduce: 1402.46 | step: 7.61 |
1%| | 29/2424 [11:30<13:55:35, 20.93s/it]Registering VQA_lavis step |
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 stacks of towels are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=LEFT,question='Is there any dog lying down in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ANSWER0=VQA(image=RIGHT,question='Are the eyes of the dog half open?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
ANSWER0=VQA(image=RIGHT,question='Is the cabinet a square shape?') |
ANSWER1=EVAL(expr='not {ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) |
question: ['Are the eyes of the dog half open?'], 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 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
question: ['Is there any dog lying down in the image?'], responses:['no'] |
question: ['Is the cabinet a square shape?'], 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']] |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 |
[('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: 3, images per sample: 3.0, dynamic token length: 837 |
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: 3, images per sample: 3.0, dynamic token length: 838 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 |
tensor([5.1501e-01, 4.8381e-01, 3.2331e-05, 1.4815e-04, 7.7756e-05, 5.3478e-04, |
3.2122e-04, 6.6391e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([5.1501e-01, 4.8381e-01, 3.2331e-05, 1.4815e-04, 7.7756e-05, 5.3478e-04, |
3.2122e-04, 6.6391e-05], device='cuda:0', grad_fn=<SelectBackward0>) |
question: ['How many stacks of towels are in the image?'], responses:['5'] |
最后的概率分布为: {True: tensor(0.4838, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.5150, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Do some of the bottles have rounded tops in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('5', 0.12793059870235002), ('8', 0.12539646467821697), ('4', 0.12509737486793587), ('6', 0.12470234839853608), ('3', 0.12467331676337925), ('7', 0.12441254825093238), ('11', 0.12401867309944531), ('9', 0.12376867523920407)] |
[['5', '8', '4', '6', '3', '7', '11', '9']] |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([9.4619e-01, 5.3392e-02, 1.9326e-05, 3.5605e-05, 3.1202e-05, 2.0506e-04, |
1.0237e-04, 2.0203e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.4619e-01, 5.3392e-02, 1.9326e-05, 3.5605e-05, 3.1202e-05, 2.0506e-04, |
1.0237e-04, 2.0203e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([6.9213e-01, 3.0713e-01, 3.2616e-05, 7.8449e-05, 7.0803e-05, 2.4022e-04, |
2.9560e-04, 1.6385e-05], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([6.9213e-01, 3.0713e-01, 3.2616e-05, 7.8449e-05, 7.0803e-05, 2.4022e-04, |
2.9560e-04, 1.6385e-05], device='cuda:2', grad_fn=<SelectBackward0>) |
最后的概率分布为: {True: tensor(0.0534, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9462, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0004, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many objects with plungers are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['Do some of the bottles have rounded tops in the image?'], responses:['yes'] |
最后的概率分布为: {True: tensor(0.6921, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.3071, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0007, device='cuda:2', grad_fn=<DivBackward0>)} |
torch.Size([5, 3, 448, 448]) |
[('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']] |
ANSWER0=VQA(image=RIGHT,question='How many seals are 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]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400 |
question: ['How many objects with plungers 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([5, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400 |
question: ['How many seals are in the image?'], responses:['1'] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
[('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([13, 3, 448, 448]) knan debug pixel values shape |
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