text stringlengths 0 1.16k |
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1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([7.8679e-01, 3.4565e-02, 1.4407e-02, 5.4633e-03, 7.9548e-03, 4.8083e-03, |
1.4554e-01, 4.6977e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.1455, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.8545, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many kids are holding pillows in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
question: ['How many kids are holding pillows 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([1, 3, 448, 448]) knan debug pixel values shape |
tensor([9.6379e-01, 6.2938e-03, 2.4647e-03, 9.9423e-04, 1.3188e-03, 9.5588e-04, |
2.4128e-02, 5.4419e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.6379e-01, 6.2938e-03, 2.4647e-03, 9.9423e-04, 1.3188e-03, 9.5588e-04, |
2.4128e-02, 5.4419e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.9638, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0362, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([4.3541e-01, 9.7163e-02, 4.0009e-02, 5.4806e-03, 1.2989e-02, 3.9780e-03, |
4.0475e-01, 2.2768e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([4.3541e-01, 9.7163e-02, 4.0009e-02, 5.4806e-03, 1.2989e-02, 3.9780e-03, |
4.0475e-01, 2.2768e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.4047, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.5953, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
tensor([5.7174e-01, 2.3689e-02, 4.0125e-01, 1.6100e-03, 1.2490e-04, 6.1934e-04, |
1.4370e-04, 8.1772e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([5.7174e-01, 2.3689e-02, 4.0125e-01, 1.6100e-03, 1.2490e-04, 6.1934e-04, |
1.4370e-04, 8.1772e-04], device='cuda:2', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.5717, device='cuda:2', grad_fn=<UnbindBackward0>), False: tensor(0.4013, device='cuda:2', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0270, device='cuda:2', grad_fn=<SubBackward0>)} |
[2024-10-23 14:45:37,002] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.36 | optimizer_gradients: 0.34 | optimizer_step: 0.33 |
[2024-10-23 14:45:37,002] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 3769.63 | backward_microstep: 8765.12 | backward_inner_microstep: 3505.43 | backward_allreduce_microstep: 5259.54 | step_microstep: 7.76 |
[2024-10-23 14:45:37,002] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 3769.64 | backward: 8765.11 | backward_inner: 3505.48 | backward_allreduce: 5259.52 | step: 7.78 |
0%| | 17/4844 [04:20<18:00:00, 13.42s/it]Registering VQA_lavis step |
Registering EVAL step |
Registering RESULT step |
Registering VQA_lavis step |
Registering VQA_lavis step |
Registering EVAL stepRegistering VQA_lavis step |
Registering RESULT step |
Registering EVAL step |
Registering RESULT step |
Registering EVAL step |
Registering RESULT step |
ANSWER0=VQA(image=RIGHT,question='Is the banana flower purple?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
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='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([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
question: ['Is there an item on top of the cabinet?'], 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 |
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: 1865 |
question: ['Is the lock in the image on the right in the locked position?'], responses:['no'] |
question: ['Is the banana flower purple?'], responses:['yes'] |
question: ['How many warthogs are in the image?'], responses:['5'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
[('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']] |
[('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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
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: 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: 1863 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 |
tensor([8.9435e-01, 1.6369e-02, 8.3187e-02, 3.6382e-03, 9.4211e-05, 3.0722e-04, |
8.8851e-04, 1.1693e-03], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.9435e-01, 1.6369e-02, 8.3187e-02, 3.6382e-03, 9.4211e-05, 3.0722e-04, |
8.8851e-04, 1.1693e-03], device='cuda:0', grad_fn=<SelectBackward0>) |
ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.8943, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0832, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the dog facing left?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([13, 3, 448, 448]) |
question: ['Is the dog facing left?'], 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([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3394 |
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