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InternVL

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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3395
tensor([1.0000e+00, 2.1353e-08, 5.7806e-09, 1.6383e-09, 6.1277e-11, 4.6255e-11,
1.1585e-11, 3.1849e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.1353e-08, 5.7806e-09, 1.6383e-09, 6.1277e-11, 4.6255e-11,
1.1585e-11, 3.1849e-09], device='cuda:0', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1., device='cuda:0', grad_fn=<DivBackward0>), False: tensor(5.7806e-09, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(-5.7806e-09, device='cuda:0', grad_fn=<DivBackward0>)}
[2024-10-24 10:01:45,739] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.53 | optimizer_gradients: 0.23 | optimizer_step: 0.31
[2024-10-24 10:01:45,740] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 8982.43 | backward_microstep: 8699.12 | backward_inner_microstep: 8693.60 | backward_allreduce_microstep: 5.34 | step_microstep: 7.49
[2024-10-24 10:01:45,740] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 8982.45 | backward: 8699.12 | backward_inner: 8693.65 | backward_allreduce: 5.32 | step: 7.51
96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ| 4650/4844 [19:20:29<54:59, 17.01s/it]Registering VQA_lavis step
Registering VQA_lavis step
Registering EVAL step
Registering RESULT step
ANSWER0=VQA(image=LEFT,question='How many sails are unfurled on the boat?')
ANSWER1=EVAL(expr='{ANSWER0} > 4')
FINAL_ANSWER=RESULT(var=ANSWER1)
Registering EVAL step
Registering RESULT 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='Is the door of the bus open?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='What color is the graduation gown?')
ANSWER1=EVAL(expr='{ANSWER0} == "blue"')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='How many parrots are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([13, 3, 448, 448])
torch.Size([7, 3, 448, 448])
torch.Size([3, 3, 448, 448])
torch.Size([13, 3, 448, 448])
question: ['How many parrots are in the image?'], responses:['ε››']
[('geese', 0.12791273653846358), ('cushion', 0.12632164867635856), ('biking', 0.12559214056053666), ('bulldog', 0.12532071672327474), ('striped', 0.12486304389654934), ('goose', 0.12402122964730407), ('vegetable', 0.12318440383239601), ('dodgers', 0.12278408012511692)]
[['geese', 'cushion', 'biking', 'bulldog', 'striped', 'goose', 'vegetable', 'dodgers']]
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
question: ['Is the door of the bus open?'], 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([7, 3, 448, 448]) knan debug pixel values shape
question: ['How many sails are unfurled on the boat?'], responses:['2']
tensor([2.4124e-03, 7.3456e-03, 3.3184e-06, 2.2840e-01, 6.3428e-02, 2.4802e-03,
6.9482e-01, 1.1044e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>)
vegetable *************
['geese', 'cushion', 'biking', 'bulldog', 'striped', 'goose', 'vegetable', 'dodgers'] tensor([2.4124e-03, 7.3456e-03, 3.3184e-06, 2.2840e-01, 6.3428e-02, 2.4802e-03,
6.9482e-01, 1.1044e-03], device='cuda:3', grad_fn=<SelectBackward0>)
question: ['What color is the graduation gown?'], responses:['blue']
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:3', grad_fn=<DivBackward0>)}
[('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']]
[('blue', 0.12610723189030773), ('kitten', 0.12505925935446505), ('iris', 0.12496487399785434), ('lemon', 0.12480860793572608), ('cherry', 0.12478264542061647), ('bright', 0.12478001416316817), ('peach', 0.12475640037922975), ('cookie', 0.12474096685863247)]
[['blue', 'kitten', 'iris', 'lemon', 'cherry', 'bright', 'peach', 'cookie']]
ANSWER0=VQA(image=LEFT,question='Is the bowl all white?')
FINAL_ANSWER=RESULT(var=ANSWER0)
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
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
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
tensor([1.9556e-08, 9.8511e-09, 1.0000e+00, 2.3796e-09, 5.5987e-12, 4.5901e-12,
9.6388e-10, 2.5274e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>)
no *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.9556e-08, 9.8511e-09, 1.0000e+00, 2.3796e-09, 5.5987e-12, 4.5901e-12,
9.6388e-10, 2.5274e-09], device='cuda:2', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1.9556e-08, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many zebras are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} <= 3')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([13, 3, 448, 448])
question: ['Is the bowl all white?'], responses:['yes']
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
[('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([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
question: ['How many zebras are in the image?'], responses:['20']
[('20', 0.12771895156791702), ('21', 0.12586912554208884), ('22', 0.12503044546440548), ('26', 0.12459144863554222), ('30', 0.1243482131473721), ('48', 0.12418849501124658), ('27', 0.12415656019926104), ('28', 0.12409676043216668)]
[['20', '21', '22', '26', '30', '48', '27', '28']]
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
tensor([9.9997e-01, 3.0269e-05, 1.2886e-06, 1.0851e-06, 4.8644e-08, 6.4420e-08,
2.3831e-07, 3.2985e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>)
2 *************
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9997e-01, 3.0269e-05, 1.2886e-06, 1.0851e-06, 4.8644e-08, 6.4420e-08,
2.3831e-07, 3.2985e-09], device='cuda:0', grad_fn=<SelectBackward0>)
tensor([9.9908e-01, 1.1387e-06, 8.0441e-07, 3.2679e-04, 1.8751e-04, 9.7367e-06,
3.9485e-04, 1.2433e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>)
blue *************
['blue', 'kitten', 'iris', 'lemon', 'cherry', 'bright', 'peach', 'cookie'] tensor([9.9908e-01, 1.1387e-06, 8.0441e-07, 3.2679e-04, 1.8751e-04, 9.7367e-06,