text stringlengths 0 1.16k |
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tensor([1.0000e+00, 1.6591e-09, 1.3440e-08, 1.9878e-09, 5.1567e-11, 4.0186e-11, |
5.1353e-12, 4.2415e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.6591e-09, 1.3440e-08, 1.9878e-09, 5.1567e-11, 4.0186e-11, |
5.1353e-12, 4.2415e-09], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.3440e-08, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.3440e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many chimneys are visible in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
question: ['Are some of the animals lying on the green grass?'], responses:['no'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 |
torch.Size([13, 3, 448, 448]) |
[('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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 |
tensor([1.0000e+00, 1.6451e-08, 4.0186e-11, 8.3904e-08, 7.6763e-10, 2.5651e-09, |
3.3657e-11, 1.0155e-08], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.6451e-08, 4.0186e-11, 8.3904e-08, 7.6763e-10, 2.5651e-09, |
3.3657e-11, 1.0155e-08], device='cuda:3', grad_fn=<SelectBackward0>) |
tensor([1.0000e+00, 8.8649e-10, 3.4964e-07, 1.2967e-12, 6.1648e-12, 1.7715e-09, |
3.0642e-10, 8.8176e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 8.8649e-10, 3.4964e-07, 1.2967e-12, 6.1648e-12, 1.7715e-09, |
3.0642e-10, 8.8176e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
question: ['How many chimneys are visible in the image?'], responses:['1'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(4.0186e-11, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1917e-07, device='cuda:3', grad_fn=<DivBackward0>)} |
ζεηζ¦ηεεΈδΈΊ: ANSWER0=VQA(image=RIGHT,question='How many school buses are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
{True: tensor(8.8649e-10, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(1.1921e-06, device='cuda:0', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
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']] |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
question: ['How many dogs are in the image?'], responses:['2'] |
[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)] |
[['2', '3', '4', '1', '5', '8', '7', '29']] |
torch.Size([3, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 |
tensor([1.0000e+00, 2.9939e-06, 8.9032e-08, 2.4986e-08, 4.9747e-09, 8.8857e-09, |
1.6785e-08, 1.0661e-08], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 2.9939e-06, 8.9032e-08, 2.4986e-08, 4.9747e-09, 8.8857e-09, |
1.6785e-08, 1.0661e-08], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(3.1492e-06, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)} |
question: ['How many school buses are in the image?'], responses:['2'] |
[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)] |
[['2', '3', '4', '1', '5', '8', '7', '29']] |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 1.9474e-10, 4.2451e-07, 4.7351e-11, 5.9162e-10, 3.8351e-08, |
6.6330e-10, 9.6199e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.9474e-10, 4.2451e-07, 4.7351e-11, 5.9162e-10, 3.8351e-08, |
6.6330e-10, 9.6199e-07], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.9474e-10, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.4305e-06, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the dog in the image lying down?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['Is the dog in the image lying down?'], 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([7, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 1.3027e-08, 5.4243e-10, 6.0326e-11, 1.3595e-10, 3.6174e-09, |
3.5009e-06, 3.6911e-11], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 1.3027e-08, 5.4243e-10, 6.0326e-11, 1.3595e-10, 3.6174e-09, |
3.5009e-06, 3.6911e-11], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(3.5183e-06, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([1.0000e+00, 8.8649e-10, 4.3810e-07, 1.4585e-10, 2.2743e-10, 4.8644e-08, |
9.0125e-10, 1.2034e-06], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 8.8649e-10, 4.3810e-07, 1.4585e-10, 2.2743e-10, 4.8644e-08, |
9.0125e-10, 1.2034e-06], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(8.8649e-10, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.7881e-06, device='cuda:2', grad_fn=<DivBackward0>)} |
tensor([1.6344e-01, 8.3618e-01, 3.8216e-04, 1.5709e-06, 2.0171e-06, 2.5536e-09, |
1.6080e-07, 1.2130e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.6344e-01, 8.3618e-01, 3.8216e-04, 1.5709e-06, 2.0171e-06, 2.5536e-09, |
1.6080e-07, 1.2130e-10], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8366, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.1634, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)} |
[2024-10-24 10:15:16,876] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.35 | optimizer_gradients: 0.34 | optimizer_step: 0.33 |
[2024-10-24 10:15:16,876] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 3795.68 | backward_microstep: 10122.46 | backward_inner_microstep: 3510.12 | backward_allreduce_microstep: 6612.28 | step_microstep: 7.65 |
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