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ANSWER0=VQA(image=RIGHT,question='How many syringes are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
question: ['How many syringes are in the image?'], responses:['four'] |
[('7 eleven', 0.12650899275575006), ('4', 0.125210025275264), ('first', 0.12483048280083887), ('3', 0.12473532336671392), ('5', 0.1247268629491862), ('dark', 0.12470563072493092), ('forward', 0.12466964370422237), ('bag', 0.12461303842309367)] |
[['7 eleven', '4', 'first', '3', '5', 'dark', 'forward', 'bag']] |
torch.Size([3, 3, 448, 448]) knan debug pixel values shape |
question: ['How many cups of dessert are in the image?'], responses:['1'] |
question: ['How many glass panels does the furniture piece have?'], responses:['2'] |
[('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']] |
[('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 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
tensor([9.9999e-01, 1.0130e-05, 4.1003e-07, 3.6589e-11, 9.5741e-10, 1.6082e-09, |
2.1231e-10, 1.7956e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.9999e-01, 1.0130e-05, 4.1003e-07, 3.6589e-11, 9.5741e-10, 1.6082e-09, |
2.1231e-10, 1.7956e-07], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([3.1085e-14, 9.9988e-01, 4.6454e-06, 7.0174e-05, 4.5482e-05, 1.5050e-06, |
1.7336e-06, 5.9794e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
4 ************* |
['7 eleven', '4', 'first', '3', '5', 'dark', 'forward', 'bag'] tensor([3.1085e-14, 9.9988e-01, 4.6454e-06, 7.0174e-05, 4.5482e-05, 1.5050e-06, |
1.7336e-06, 5.9794e-07], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(8.5831e-06, device='cuda:3', grad_fn=<DivBackward0>)} |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0130e-05, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(4.7684e-07, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Can windows be seen in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
question: ['Can windows be seen 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']] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
tensor([1.0000e+00, 4.9444e-09, 5.4615e-10, 8.1815e-11, 2.9927e-10, 5.2632e-09, |
6.0236e-08, 8.1316e-11], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 4.9444e-09, 5.4615e-10, 8.1815e-11, 2.9927e-10, 5.2632e-09, |
6.0236e-08, 8.1316e-11], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(4.9444e-09, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
tensor([9.9995e-01, 3.1874e-06, 4.5397e-05, 5.2033e-07, 1.6275e-08, 5.4219e-06, |
6.3123e-08, 2.6007e-08], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9995e-01, 3.1874e-06, 4.5397e-05, 5.2033e-07, 1.6275e-08, 5.4219e-06, |
6.3123e-08, 2.6007e-08], device='cuda:0', grad_fn=<SelectBackward0>) |
ANSWER0=VQA(image=LEFT,question='Are there baby antelope in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(5.4112e-05, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.9999, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
question: ['Are there baby antelope 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([3, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 1.2099e-06, 1.9750e-07, 4.1875e-10, 2.3108e-10, 8.7811e-09, |
7.4229e-11, 2.0650e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.2099e-06, 1.9750e-07, 4.1875e-10, 2.3108e-10, 8.7811e-09, |
7.4229e-11, 2.0650e-07], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.2099e-06, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(4.7684e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
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 |
tensor([1.0000e+00, 1.5713e-08, 5.3124e-07, 5.0404e-11, 3.1301e-10, 4.2673e-09, |
2.3608e-09, 3.0115e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.5713e-08, 5.3124e-07, 5.0404e-11, 3.1301e-10, 4.2673e-09, |
2.3608e-09, 3.0115e-07], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.5713e-08, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(8.3447e-07, 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 |
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([1.0000e+00, 1.8728e-10, 2.3349e-11, 3.4777e-11, 6.8895e-11, 4.0954e-09, |
1.1611e-07, 2.1081e-11], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 1.8728e-10, 2.3349e-11, 3.4777e-11, 6.8895e-11, 4.0954e-09, |
1.1611e-07, 2.1081e-11], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.2054e-07, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)} |
[2024-10-24 10:20:50,342] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.45 | optimizer_gradients: 0.26 | optimizer_step: 0.32 |
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