Datasets:
TMarcus
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InternVL

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tensor([8.8817e-01, 2.0888e-02, 8.7025e-03, 2.8231e-03, 4.1095e-03, 2.1871e-03,
7.2905e-02, 2.1758e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([8.8817e-01, 2.0888e-02, 8.7025e-03, 2.8231e-03, 4.1095e-03, 2.1871e-03,
7.2905e-02, 2.1758e-04], device='cuda:2', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0.1118, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.8882, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=RIGHT,question='How many baboons are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} <= 5')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([3, 3, 448, 448])
question: ['How many baboons are in the image?'], responses:['10']
[('10', 0.1277249466426885), ('11', 0.12579928416580372), ('12', 0.12560051978633632), ('8', 0.1247991444010043), ('9', 0.12459861387933152), ('26', 0.12389435171102943), ('13', 0.12388731669200545), ('6', 0.12369582272180085)]
[['10', '11', '12', '8', '9', '26', '13', '6']]
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
tensor([0.1996, 0.1208, 0.1289, 0.1693, 0.1459, 0.0204, 0.0830, 0.1322],
device='cuda:2', grad_fn=<SoftmaxBackward0>)
10 *************
['10', '11', '12', '8', '9', '26', '13', '6'] tensor([0.1996, 0.1208, 0.1289, 0.1693, 0.1459, 0.0204, 0.0830, 0.1322],
device='cuda:2', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), False: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)}
[2024-10-22 17:21:45,469] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.35 | optimizer_gradients: 0.32 | optimizer_step: 0.34
[2024-10-22 17:21:45,469] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 6876.45 | backward_microstep: 15681.97 | backward_inner_microstep: 6563.41 | backward_allreduce_microstep: 9118.49 | step_microstep: 7.75
[2024-10-22 17:21:45,469] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 6876.47 | backward: 15681.96 | backward_inner: 6563.42 | backward_allreduce: 9118.48 | step: 7.76
0%| | 8/2424 [03:17<16:01:56, 23.89s/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 the lock in the image on the right in the locked position?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=LEFT,question='Is there an item on top of the cabinet?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='Is the animal in the image holding one paw off the ground?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='How many warthogs are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} <= 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
torch.Size([13, 3, 448, 448])
torch.Size([7, 3, 448, 448])
torch.Size([13, 3, 448, 448])
question: ['Is there an item on top of the cabinet?'], responses:['yes']
question: ['Is the animal in the image holding one paw off the ground?'], 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']]
[('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
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869
question: ['Is the lock in the image on the right in the locked position?'], responses:['no']
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866
[('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']]
question: ['How many warthogs are in the image?'], responses:['5']
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867
[('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]) knan debug pixel values shape
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867
tensor([8.9388e-01, 1.6904e-02, 8.3143e-02, 3.6111e-03, 9.3631e-05, 3.0716e-04,
9.1390e-04, 1.1514e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.9388e-01, 1.6904e-02, 8.3143e-02, 3.6111e-03, 9.3631e-05, 3.0716e-04,
9.1390e-04, 1.1514e-03], device='cuda:1', grad_fn=<SelectBackward0>)
tensor([5.9818e-01, 1.9341e-02, 3.7948e-01, 1.3427e-03, 1.6487e-04, 6.0538e-04,
9.6113e-05, 7.8912e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([5.9818e-01, 1.9341e-02, 3.7948e-01, 1.3427e-03, 1.6487e-04, 6.0538e-04,
9.6113e-05, 7.8912e-04], device='cuda:0', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0.8939, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0831, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0230, device='cuda:1', grad_fn=<DivBackward0>)}
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0.5982, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.3795, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='What color are the girl's pajamas?')
ANSWER1=EVAL(expr='{ANSWER0} == "gray"')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=LEFT,question='Is there a glove on a hand in the image?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([5, 3, 448, 448])
torch.Size([13, 3, 448, 448])
question: ['Is there a glove on a hand in the image?'], 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([5, 3, 448, 448]) knan debug pixel values shape