Datasets:
TMarcus
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InternVL

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['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.6036e-01, 6.8886e-03, 2.9625e-03, 1.3137e-03, 1.5855e-03, 1.1876e-03,
2.5595e-02, 1.0951e-04], device='cuda:3', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.9604, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0396, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:3', grad_fn=<DivBackward0>)}
question: ['How many tusked animals 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([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
question: ['What color is the jellyfish?'], responses:['blue']
[('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']]
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
tensor([5.3829e-01, 2.3275e-02, 4.3544e-01, 1.6257e-03, 1.0229e-04, 4.4885e-04,
1.0387e-04, 7.1572e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([5.3829e-01, 2.3275e-02, 4.3544e-01, 1.6257e-03, 1.0229e-04, 4.4885e-04,
1.0387e-04, 7.1572e-04], device='cuda:2', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.5383, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.4354, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0263, device='cuda:2', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=RIGHT,question='How many cheetahs are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 4')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
question: ['How many cheetahs 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([7, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
tensor([8.9689e-01, 1.8621e-02, 7.5221e-03, 2.5902e-03, 3.1321e-03, 1.8735e-03,
6.9161e-02, 2.0666e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([8.9689e-01, 1.8621e-02, 7.5221e-03, 2.5902e-03, 3.1321e-03, 1.8735e-03,
6.9161e-02, 2.0666e-04], device='cuda:0', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.8969, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.1031, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
tensor([9.0852e-01, 1.7167e-02, 7.1552e-03, 2.9742e-03, 3.8283e-03, 2.1587e-03,
5.8058e-02, 1.4126e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.0852e-01, 1.7167e-02, 7.1552e-03, 2.9742e-03, 3.8283e-03, 2.1587e-03,
5.8058e-02, 1.4126e-04], device='cuda:2', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.0163, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.9837, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)}
tensor([8.9491e-01, 1.7209e-03, 4.8943e-04, 2.2005e-02, 1.0686e-02, 4.5811e-02,
2.4260e-02, 1.1224e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>)
blue *************
['blue', 'kitten', 'iris', 'lemon', 'cherry', 'bright', 'peach', 'cookie'] tensor([8.9491e-01, 1.7209e-03, 4.8943e-04, 2.2005e-02, 1.0686e-02, 4.5811e-02,
2.4260e-02, 1.1224e-04], device='cuda:1', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {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>)}
question: ['How many dogs 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([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
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: 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: 1860
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860
tensor([9.7163e-01, 4.6423e-03, 1.8178e-03, 8.3145e-04, 1.2489e-03, 8.1863e-04,
1.8944e-02, 6.8086e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.7163e-01, 4.6423e-03, 1.8178e-03, 8.3145e-04, 1.2489e-03, 8.1863e-04,
1.8944e-02, 6.8086e-05], device='cuda:0', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.9716, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-07, device='cuda:0', grad_fn=<DivBackward0>)}
[2024-10-23 14:47:32,483] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.45 | optimizer_gradients: 0.21 | optimizer_step: 0.30
[2024-10-23 14:47:32,484] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 7114.25 | backward_microstep: 6804.65 | backward_inner_microstep: 6799.49 | backward_allreduce_microstep: 5.06 | step_microstep: 7.49
[2024-10-23 14:47:32,484] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 7114.27 | backward: 6804.64 | backward_inner: 6799.50 | backward_allreduce: 5.04 | step: 7.50
1%| | 25/4844 [06:16<17:49:41, 13.32s/it]Registering VQA_lavis step
Registering EVAL step
Registering RESULT step
ANSWER0=VQA(image=LEFT,question='Is there a stack of three books on the front-most corner of the shelf under the couch?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
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='Does a bird fly right above the water in the image?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=LEFT,question='Does the image on the left have a man's leg bending to the right with his heel up?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([1, 3, 448, 448])