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ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.6760e-08, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)}
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torch.Size([7, 3, 448, 448])
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ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} >= 3')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([13, 3, 448, 448])
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question: ['Does the car in the image have a top?'], responses:['yes']
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[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)]
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[['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate']]
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torch.Size([3, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838
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question: ['How many gorillas are in the image?'], responses:['2']
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839
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[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)]
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[['2', '3', '4', '1', '5', '8', '7', '29']]
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838
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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839
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tensor([1.0000e+00, 2.2525e-08, 3.6535e-08, 8.4686e-09, 2.7462e-10, 5.3770e-10,
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5.3782e-10, 4.7819e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.2525e-08, 3.6535e-08, 8.4686e-09, 2.7462e-10, 5.3770e-10,
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5.3782e-10, 4.7819e-09], device='cuda:0', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(3.6535e-08, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(-3.6535e-08, device='cuda:0', grad_fn=<DivBackward0>)}
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question: ['How many dogs are in the image?'], responses:['4']
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[('4', 0.12804651361935848), ('5', 0.12521071898947128), ('3', 0.12515925906184908), ('8', 0.12489091845155219), ('6', 0.1245383468146311), ('1', 0.12441141527606933), ('2', 0.12403713327181662), ('11', 0.12370569451525179)]
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[['4', '5', '3', '8', '6', '1', '2', '11']]
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torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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tensor([1.0000e+00, 1.9948e-06, 3.7482e-07, 2.9525e-09, 3.4384e-09, 1.1013e-08,
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7.5379e-09, 1.4496e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>)
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2 *************
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['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 1.9948e-06, 3.7482e-07, 2.9525e-09, 3.4384e-09, 1.1013e-08,
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7.5379e-09, 1.4496e-09], device='cuda:2', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.9525e-09, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)}
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tensor([9.7697e-01, 3.3479e-05, 2.2994e-02, 9.4857e-10, 5.8110e-09, 2.5068e-08,
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1.9585e-08, 2.2821e-08], device='cuda:3', grad_fn=<SoftmaxBackward0>)
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4 *************
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['4', '5', '3', '8', '6', '1', '2', '11'] tensor([9.7697e-01, 3.3479e-05, 2.2994e-02, 9.4857e-10, 5.8110e-09, 2.5068e-08,
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1.9585e-08, 2.2821e-08], device='cuda:3', grad_fn=<SelectBackward0>)
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ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(4.4652e-08, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)}
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[2024-10-24 10:35:19,018] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.36 | optimizer_gradients: 0.37 | optimizer_step: 0.33
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[2024-10-24 10:35:19,019] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 5716.13 | backward_microstep: 12157.12 | backward_inner_microstep: 5464.07 | backward_allreduce_microstep: 6692.96 | step_microstep: 7.65
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[2024-10-24 10:35:19,019] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 5716.15 | backward: 12157.12 | backward_inner: 5464.10 | backward_allreduce: 6692.91 | step: 7.66
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99%|ββββββββββ| 4785/4844 [19:54:02<15:36, 15.87s/it]Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} >= 4')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} == 2')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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ANSWER0=VQA(image=LEFT,question='Is there a table lamp in the image?')
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ANSWER1=EVAL(expr='{ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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ANSWER0=VQA(image=LEFT,question='Is the pug wearing a swimming vest?')
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ANSWER1=EVAL(expr='{ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([5, 3, 448, 448])
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torch.Size([5, 3, 448, 448])
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torch.Size([13, 3, 448, 448])
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torch.Size([13, 3, 448, 448])
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question: ['How many dogs are in the image?'], responses:['2']
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question: ['Is there a table lamp in the image?'], responses:['no']
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[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)]
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[['2', '3', '4', '1', '5', '8', '7', '29']]
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[('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)]
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[['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock']]
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torch.Size([5, 3, 448, 448]) knan debug pixel values shape
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torch.Size([5, 3, 448, 448]) knan debug pixel values shape
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question: ['How many animals are in the image?'], responses:['1']
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question: ['Is the pug wearing a swimming vest?'], responses:['yes']
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[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)]
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[['1', '3', '4', '8', '6', '12', '2', '47']]
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[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)]
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[['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate']]
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torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396
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torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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tensor([1.0000e+00, 2.5360e-07, 4.7923e-09, 5.8964e-07, 3.8053e-10, 3.8727e-10,
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1.2949e-09, 9.5564e-11], device='cuda:2', grad_fn=<SoftmaxBackward0>)
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2 *************
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['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 2.5360e-07, 4.7923e-09, 5.8964e-07, 3.8053e-10, 3.8727e-10,
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1.2949e-09, 9.5564e-11], device='cuda:2', grad_fn=<SelectBackward0>)
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tensor([1.0000e+00, 1.9363e-09, 6.8928e-07, 7.3184e-12, 1.2366e-11, 1.5042e-09,
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9.6770e-11, 2.2148e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>)
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