text stringlengths 0 1.16k |
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torch.Size([3, 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']] |
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 |
question: ['How many beetles 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([3, 3, 448, 448]) knan debug pixel values shape |
tensor([9.6785e-01, 5.2399e-03, 1.7010e-03, 6.8597e-04, 1.0315e-03, 6.7908e-04, |
2.2763e-02, 5.4177e-05], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.6785e-01, 5.2399e-03, 1.7010e-03, 6.8597e-04, 1.0315e-03, 6.7908e-04, |
2.2763e-02, 5.4177e-05], device='cuda:2', grad_fn=<SelectBackward0>) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0017, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.9983, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many dogs are standing on all fours in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
tensor([9.3690e-01, 8.6286e-03, 3.2748e-03, 1.4516e-03, 1.8656e-03, 1.1524e-03, |
4.6646e-02, 8.0023e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.3690e-01, 8.6286e-03, 3.2748e-03, 1.4516e-03, 1.8656e-03, 1.1524e-03, |
4.6646e-02, 8.0023e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0466, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9534, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([8.9268e-01, 1.5360e-02, 5.8298e-03, 2.5849e-03, 3.4268e-03, 1.9424e-03, |
7.8006e-02, 1.6705e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([8.9268e-01, 1.5360e-02, 5.8298e-03, 2.5849e-03, 3.4268e-03, 1.9424e-03, |
7.8006e-02, 1.6705e-04], device='cuda:3', grad_fn=<SelectBackward0>) |
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0780, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9220, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Are the dogs lined up?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([3, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
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 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
question: ['How many dogs are standing on all fours in the image?'], responses:['0'] |
[('0', 0.13077743594303964), ('circles', 0.12449813349255197), ('maroon', 0.12428926693968681), ('large', 0.1242263466991631), ('rooster', 0.12409315512763705), ('nuts', 0.12408018414184876), ('beige', 0.1240288472550799), ('bottle', 0.12400663040099273)] |
[['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle']] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([7.9628e-01, 2.3042e-02, 1.7767e-01, 1.0675e-03, 1.2033e-04, 4.1320e-04, |
9.3783e-05, 1.3091e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([7.9628e-01, 2.3042e-02, 1.7767e-01, 1.0675e-03, 1.2033e-04, 4.1320e-04, |
9.3783e-05, 1.3091e-03], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7963, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.1777, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0260, device='cuda:3', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
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: 3399 |
tensor([5.8651e-01, 4.1161e-01, 7.3392e-05, 1.9524e-04, 3.1120e-04, 8.3735e-04, |
4.2304e-04, 3.9016e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([5.8651e-01, 4.1161e-01, 7.3392e-05, 1.9524e-04, 3.1120e-04, 8.3735e-04, |
4.2304e-04, 3.9016e-05], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.4116, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.5865, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Does the image contain a potted plant?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
question: ['Does the image contain a potted plant?'], 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([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 |
tensor([8.8984e-01, 1.4861e-02, 9.3723e-02, 7.8641e-04, 4.5999e-05, 1.8836e-04, |
2.7150e-05, 5.2993e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.8984e-01, 1.4861e-02, 9.3723e-02, 7.8641e-04, 4.5999e-05, 1.8836e-04, |
2.7150e-05, 5.2993e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8898, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0937, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is there a female in the image?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['Is there a female 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([7, 3, 448, 448]) knan debug pixel values shape |
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