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tensor([1.0000e+00, 1.0819e-09, 1.8294e-10, 6.6648e-10, 4.0586e-10, 3.3725e-08, |
1.5961e-08, 1.7847e-09], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many boars are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 4') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.5961e-08, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many penguins 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]) |
question: ['How many train cars 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([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 |
question: ['How many chimps are outside in the image?'], responses:['1'] |
question: ['How many boars are in the image?'], responses:['1'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
[('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']] |
[('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: 7, images per sample: 7.0, dynamic token length: 1861 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
question: ['How many penguins are in the image?'], responses:['δΈ'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
[('biking', 0.12639990046765587), ('geese', 0.1262789403477572), ('cushion', 0.1253965842661667), ('bulldog', 0.1252365705078606), ('striped', 0.12499404846420245), ('floral', 0.12444127054742124), ('stove', 0.12381223353082338), ('dodgers', 0.12344045186811266)] |
[['biking', 'geese', 'cushion', 'bulldog', 'striped', 'floral', 'stove', 'dodgers']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 |
tensor([1.0000e+00, 7.1232e-10, 3.2232e-10, 2.7732e-10, 5.0314e-10, 2.5110e-08, |
8.4108e-09, 5.2305e-10], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 7.1232e-10, 3.2232e-10, 2.7732e-10, 5.0314e-10, 2.5110e-08, |
8.4108e-09, 5.2305e-10], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.6736e-08, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Are the dogs running?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
question: ['Are the dogs running?'], 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([3, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 |
tensor([1.0000e+00, 3.0161e-10, 2.6150e-11, 6.8893e-11, 4.7164e-11, 3.1908e-09, |
5.4304e-09, 4.6650e-11], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 3.0161e-10, 2.6150e-11, 6.8893e-11, 4.7164e-11, 3.1908e-09, |
5.4304e-09, 4.6650e-11], device='cuda:1', grad_fn=<SelectBackward0>) |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(3.3797e-09, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 |
dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 |
tensor([1.0000e+00, 9.1463e-10, 3.5948e-07, 3.3647e-10, 1.4412e-11, 2.9431e-08, |
1.8673e-09, 8.0749e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 9.1463e-10, 3.5948e-07, 3.3647e-10, 1.4412e-11, 2.9431e-08, |
1.8673e-09, 8.0749e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(9.1463e-10, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-06, device='cuda:0', grad_fn=<DivBackward0>)} |
tensor([1.0000e+00, 3.1733e-10, 1.3176e-10, 2.7943e-10, 1.4019e-10, 1.4050e-08, |
4.2292e-09, 2.3855e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 3.1733e-10, 1.3176e-10, 2.7943e-10, 1.4019e-10, 1.4050e-08, |
4.2292e-09, 2.3855e-10], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.9386e-08, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Does a dog have a leash on in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
tensor([3.2325e-04, 6.5247e-03, 6.9651e-02, 7.1471e-01, 1.3027e-01, 5.7734e-02, |
1.1541e-02, 9.2491e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
bulldog ************* |
['biking', 'geese', 'cushion', 'bulldog', 'striped', 'floral', 'stove', 'dodgers'] tensor([3.2325e-04, 6.5247e-03, 6.9651e-02, 7.1471e-01, 1.3027e-01, 5.7734e-02, |
1.1541e-02, 9.2491e-03], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), False: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), 'Execute Error': tensor(1., device='cuda:3', grad_fn=<DivBackward0>)} |
question: ['Does a dog have a leash on 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([13, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 1.9401e-09, 2.6991e-07, 8.2159e-09, 1.1552e-08, 5.2567e-07, |
1.1496e-08, 2.4406e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.9401e-09, 2.6991e-07, 8.2159e-09, 1.1552e-08, 5.2567e-07, |
1.1496e-08, 2.4406e-07], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.9401e-09, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.0729e-06, device='cuda:2', grad_fn=<DivBackward0>)} |
[2024-10-24 09:38:30,743] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.34 | optimizer_gradients: 0.31 | optimizer_step: 0.32 |
[2024-10-24 09:38:30,744] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 3832.14 | backward_microstep: 14049.95 | backward_inner_microstep: 3505.64 | backward_allreduce_microstep: 10544.15 | step_microstep: 7.64 |
[2024-10-24 09:38:30,744] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 3832.14 | backward: 14049.94 | backward_inner: 3505.66 | backward_allreduce: 10544.13 | step: 7.66 |
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