Datasets:
TMarcus
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InternVL

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ANSWER0=VQA(image=RIGHT,question='How many keys are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
question: ['How many uncapped bottles are in the image?'], responses:['11']
question: ['Is the elephant being attended to by humans?'], responses:['no']
[('11', 0.12740768001087358), ('10', 0.12548679249075975), ('12', 0.12538137681693887), ('9', 0.12485855662563465), ('8', 0.12469919178932766), ('13', 0.12431757055023795), ('7', 0.12396146028399917), ('14', 0.1238873714322284)]
[['11', '10', '12', '9', '8', '13', '7', '14']]
[('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([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: 1861
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
tensor([1.0000e+00, 1.9556e-08, 1.0145e-08, 2.8616e-09, 9.7919e-11, 1.0527e-09,
4.6433e-10, 1.0661e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>)
2 *************
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 1.9556e-08, 1.0145e-08, 2.8616e-09, 9.7919e-11, 1.0527e-09,
4.6433e-10, 1.0661e-10], device='cuda:3', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), False: tensor(3.4284e-08, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=RIGHT,question='Is the chimp showing his teeth?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([1, 3, 448, 448])
question: ['How many keys are in the image?'], responses:['7']
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
[('7', 0.12828776251745355), ('8', 0.1258361832781132), ('11', 0.12481772898325143), ('5', 0.124759881092759), ('9', 0.12447036165452931), ('10', 0.1239759375399529), ('6', 0.12393017600998846), ('12', 0.12392196892395223)]
[['7', '8', '11', '5', '9', '10', '6', '12']]
question: ['Is the chimp showing his teeth?'], 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([1, 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: 1861
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861
tensor([1.0000e+00, 9.7362e-10, 4.2690e-07, 1.2378e-10, 2.2451e-10, 3.4823e-08,
2.7176e-09, 2.7842e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 9.7362e-10, 4.2690e-07, 1.2378e-10, 2.2451e-10, 3.4823e-08,
2.7176e-09, 2.7842e-07], device='cuda:3', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(9.7362e-10, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(8.3447e-07, device='cuda:3', grad_fn=<DivBackward0>)}
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862
tensor([9.8554e-01, 2.1559e-03, 3.1368e-03, 6.2382e-03, 1.5954e-05, 2.2949e-03,
3.4847e-05, 5.8025e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>)
11 *************
['11', '10', '12', '9', '8', '13', '7', '14'] tensor([1.0000e+00, 2.7036e-10, 4.9078e-07, 2.2897e-11, 1.8430e-10, 4.8485e-09,
5.1684e-10, 5.2290e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.8554e-01, 2.1559e-03, 3.1368e-03, 6.2382e-03, 1.5954e-05, 2.2949e-03,
3.4847e-05, 5.8025e-04], device='cuda:2', grad_fn=<SelectBackward0>)
tensor([1.0000e+00, 2.7036e-10, 4.9078e-07, 2.2897e-11, 1.8430e-10, 4.8485e-09,
5.1684e-10, 5.2290e-07], device='cuda:0', 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>)}
ANSWER0=VQA(image=LEFT,question='How many windows are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([1, 3, 448, 448])
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(2.7036e-10, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(9.5367e-07, device='cuda:0', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=RIGHT,question='Is the dog on the right baring its teeth?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([13, 3, 448, 448])
question: ['How many windows are in the image?'], responses:['ไธค']
[('monday', 0.12552664945614717), ('awake', 0.12538722310550102), ('leopard', 0.12525924776083958), ('kia', 0.12492343076783531), ('human', 0.1247803436217969), ('gone', 0.12471007192930383), ('thumb', 0.12470975620047144), ('halloween', 0.12470327715810482)]
[['monday', 'awake', 'leopard', 'kia', 'human', 'gone', 'thumb', 'halloween']]
torch.Size([1, 3, 448, 448]) knan debug pixel values shape
tensor([0.7148, 0.0009, 0.0710, 0.1938, 0.0059, 0.0058, 0.0067, 0.0010],
device='cuda:1', grad_fn=<SoftmaxBackward0>)
7 *************
['7', '8', '11', '5', '9', '10', '6', '12'] tensor([0.7148, 0.0009, 0.0710, 0.1938, 0.0059, 0.0058, 0.0067, 0.0010],
device='cuda:1', grad_fn=<SelectBackward0>)
tensor([2.3694e-02, 2.6506e-01, 2.6104e-02, 3.3329e-01, 1.5540e-01, 1.6461e-01,
1.7993e-04, 3.1661e-02], device='cuda:2', grad_fn=<SoftmaxBackward0>)
kia *************
['monday', 'awake', 'leopard', 'kia', 'human', 'gone', 'thumb', 'halloween'] tensor([2.3694e-02, 2.6506e-01, 2.6104e-02, 3.3329e-01, 1.5540e-01, 1.6461e-01,
1.7993e-04, 3.1661e-02], device='cuda:2', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)}
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:2', grad_fn=<DivBackward0>)}
question: ['Is the dog on the right baring its teeth?'], 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: 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: 3400
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: 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
tensor([1.0000e+00, 7.4650e-10, 1.4202e-07, 7.5078e-11, 8.6941e-11, 3.5994e-08,
2.8388e-09, 2.1854e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 7.4650e-10, 1.4202e-07, 7.5078e-11, 8.6941e-11, 3.5994e-08,
2.8388e-09, 2.1854e-07], device='cuda:0', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(7.4650e-10, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(3.5763e-07, device='cuda:0', grad_fn=<DivBackward0>)}
[2024-10-24 09:22:03,120] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.54 | optimizer_gradients: 0.21 | optimizer_step: 0.30
[2024-10-24 09:22:03,120] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 7114.84 | backward_microstep: 6794.11 | backward_inner_microstep: 6789.04 | backward_allreduce_microstep: 5.00 | step_microstep: 7.66