text stringlengths 0 1.16k |
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3.8109e-04, 1.6507e-05], device='cuda:2', grad_fn=<SelectBackward0>) |
tensor([9.2490e-01, 1.4484e-02, 6.6325e-03, 2.5104e-03, 3.1299e-03, 2.1411e-03, |
4.6034e-02, 1.6766e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.2490e-01, 1.4484e-02, 6.6325e-03, 2.5104e-03, 3.1299e-03, 2.1411e-03, |
4.6034e-02, 1.6766e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9715, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.0285, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['How many animals are in the image?'], responses:['1'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9249, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0751, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Are the dogs lined up?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
torch.Size([3, 3, 448, 448]) |
[('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']] |
question: ['How many wolves are in the image?'], responses:['5'] |
[('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: 13, images per sample: 13.0, dynamic token length: 3396 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
question: ['Are the dogs lined up?'], 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([3, 3, 448, 448]) knan debug pixel values shape |
question: ['How many dogs are in the image?'], responses:['1'] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
[('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: 3396 |
tensor([8.2635e-01, 1.8346e-02, 1.5286e-01, 8.7279e-04, 9.8677e-05, 3.1381e-04, |
7.4675e-05, 1.0897e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.2635e-01, 1.8346e-02, 1.5286e-01, 8.7279e-04, 9.8677e-05, 3.1381e-04, |
7.4675e-05, 1.0897e-03], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8263, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.1529, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0208, device='cuda:1', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
tensor([0.4523, 0.0366, 0.1074, 0.2577, 0.0155, 0.1071, 0.0038, 0.0195], |
device='cuda:3', grad_fn=<SoftmaxBackward0>) |
5 ************* |
['5', '8', '4', '6', '3', '7', '11', '9'] tensor([0.4523, 0.0366, 0.1074, 0.2577, 0.0155, 0.1071, 0.0038, 0.0195], |
device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.4523, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.5477, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
tensor([9.6826e-01, 3.9570e-03, 1.3674e-03, 6.4499e-04, 9.1061e-04, 5.7816e-04, |
2.4240e-02, 3.8773e-05], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.6826e-01, 3.9570e-03, 1.3674e-03, 6.4499e-04, 9.1061e-04, 5.7816e-04, |
2.4240e-02, 3.8773e-05], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0242, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.9758, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
tensor([9.8293e-01, 2.5935e-03, 8.1595e-04, 3.3920e-04, 5.4338e-04, 3.7929e-04, |
1.2373e-02, 2.7194e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.8293e-01, 2.5935e-03, 8.1595e-04, 3.3920e-04, 5.4338e-04, 3.7929e-04, |
1.2373e-02, 2.7194e-05], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.9992, 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([13, 3, 448, 448]) |
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([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396 |
tensor([9.8649e-01, 2.6028e-03, 1.1912e-03, 6.7591e-04, 8.1813e-04, 6.4516e-04, |
7.5319e-03, 4.7874e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.8649e-01, 2.6028e-03, 1.1912e-03, 6.7591e-04, 8.1813e-04, 6.4516e-04, |
7.5319e-03, 4.7874e-05], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.9925, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
[2024-10-23 14:53:04,844] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.42 | optimizer_gradients: 0.25 | optimizer_step: 0.32 |
[2024-10-23 14:53:04,844] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 9038.57 | backward_microstep: 8737.30 | backward_inner_microstep: 8731.22 | backward_allreduce_microstep: 5.95 | step_microstep: 7.38 |
[2024-10-23 14:53:04,844] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 9038.58 | backward: 8737.29 | backward_inner: 8731.28 | backward_allreduce: 5.88 | step: 7.39 |
1%| | 46/4844 [11:48<21:05:25, 15.82s/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 |
ANSWER0=VQA(image=RIGHT,question='Does the dog in the image have a white coat?') |
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