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TMarcus
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InternVL

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tensor([5.6181e-01, 2.6538e-01, 2.7971e-02, 1.3383e-01, 8.0372e-03, 1.1700e-03,
1.7384e-03, 5.7520e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>)
2 *************
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([5.6181e-01, 2.6538e-01, 2.7971e-02, 1.3383e-01, 8.0372e-03, 1.1700e-03,
1.7384e-03, 5.7520e-05], device='cuda:1', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0.5618, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.4382, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)}
tensor([5.7318e-01, 2.6021e-02, 3.9394e-01, 3.3280e-03, 2.1190e-04, 6.4673e-04,
5.8175e-04, 2.0856e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([5.7318e-01, 2.6021e-02, 3.9394e-01, 3.3280e-03, 2.1190e-04, 6.4673e-04,
5.8175e-04, 2.0856e-03], device='cuda:3', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0.3939, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.5732, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0329, device='cuda:3', grad_fn=<DivBackward0>)}
question: ['Is the lipstick in the image uncapped?'], 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([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
tensor([5.6899e-01, 1.1182e-01, 4.3874e-02, 7.6235e-03, 1.1786e-02, 3.8355e-03,
2.5191e-01, 1.7063e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([5.6899e-01, 1.1182e-01, 4.3874e-02, 7.6235e-03, 1.1786e-02, 3.8355e-03,
2.5191e-01, 1.7063e-04], device='cuda:2', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0.5690, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.4310, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)}
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
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: 3398
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
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([5.1517e-01, 4.8395e-01, 4.8922e-05, 1.8898e-04, 7.6516e-05, 2.2231e-04,
2.9872e-04, 4.9786e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([5.1517e-01, 4.8395e-01, 4.8922e-05, 1.8898e-04, 7.6516e-05, 2.2231e-04,
2.9872e-04, 4.9786e-05], device='cuda:0', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0.4839, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.5152, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)}
[2024-10-23 14:50:56,376] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.50 | optimizer_gradients: 0.26 | optimizer_step: 0.31
[2024-10-23 14:50:56,376] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 9191.66 | backward_microstep: 8821.48 | backward_inner_microstep: 8814.99 | backward_allreduce_microstep: 6.41 | step_microstep: 9.98
[2024-10-23 14:50:56,376] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 9191.67 | backward: 8821.47 | backward_inner: 8815.02 | backward_allreduce: 6.37 | step: 10.00
1%| | 38/4844 [09:40<21:11:12, 15.87s/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 someone holding up the dog?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='How many creatures are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} <= 8')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='Are there paws sticking out of the blanket on the pug in the image?')
ANSWER1=EVAL(expr='not {ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
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])
torch.Size([7, 3, 448, 448])
torch.Size([13, 3, 448, 448])
torch.Size([13, 3, 448, 448])
question: ['How many dogs are in the image?'], responses:['3']
question: ['How many creatures are in the image?'], responses:['many']
[('3', 0.12809209985493852), ('4', 0.12520382509374006), ('1', 0.1251059160028928), ('5', 0.12483070991268265), ('8', 0.12458076282181878), ('2', 0.12413212281858195), ('6', 0.1241125313968017), ('12', 0.12394203209854344)]
[['3', '4', '1', '5', '8', '2', '6', '12']]
[('many', 0.12680051474066337), ('few', 0.12559712123098582), ('several', 0.12545126119006317), ('blinds', 0.12452572291517987), ('moss', 0.12441899466837554), ('rainbow', 0.1244056457460399), ('kite', 0.12440323404357946), ('directions', 0.12439750546511286)]
[['many', 'few', 'several', 'blinds', 'moss', 'rainbow', 'kite', 'directions']]
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: 1861
question: ['Are there paws sticking out of the blanket on the pug in the image?'], responses:['yes']
question: ['Is someone holding up the dog?'], 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']]
[('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']]
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
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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
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
tensor([0.7416, 0.1555, 0.0179, 0.0231, 0.0014, 0.0535, 0.0060, 0.0009],
device='cuda:3', grad_fn=<SoftmaxBackward0>)
3 *************
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([0.7416, 0.1555, 0.0179, 0.0231, 0.0014, 0.0535, 0.0060, 0.0009],
device='cuda:3', grad_fn=<SelectBackward0>)
tensor([0.5892, 0.0967, 0.1939, 0.0116, 0.0235, 0.0528, 0.0126, 0.0197],
device='cuda:0', grad_fn=<SoftmaxBackward0>)
many *************