text stringlengths 0 1.16k |
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torch.Size([13, 3, 448, 448]) |
question: ['How many dogs are sitting in the grass?'], responses:['0'] |
question: ['How many wine glasses are in the image?'], responses:['1'] |
[('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']] |
[('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([5, 3, 448, 448]) knan debug pixel values shape |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
question: ['Does the image have a white background?'], responses:['yes'] |
question: ['Does the image contain a saxophone?'], 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']] |
[('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([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([9.8578e-01, 1.2691e-03, 2.1449e-03, 2.7401e-04, 1.7532e-03, 3.0841e-04, |
1.8610e-03, 6.6143e-03], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
0 ************* |
['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle'] tensor([9.8578e-01, 1.2691e-03, 2.1449e-03, 2.7401e-04, 1.7532e-03, 3.0841e-04, |
1.8610e-03, 6.6143e-03], device='cuda:1', grad_fn=<SelectBackward0>) |
tensor([9.9345e-01, 1.2769e-03, 5.3181e-04, 2.7351e-04, 3.0167e-04, 5.6374e-04, |
3.5827e-03, 2.4450e-05], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.9345e-01, 1.2769e-03, 5.3181e-04, 2.7351e-04, 3.0167e-04, 5.6374e-04, |
3.5827e-03, 2.4450e-05], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), False: tensor(0.9858, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0142, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Is the girl wearing primarily gray pajamas?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401 |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0066, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9934, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many rodents are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} >= 2') |
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 |
question: ['Is the girl wearing primarily gray pajamas?'], 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: 3399 |
torch.Size([7, 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 rodents 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']] |
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: 3399 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399 |
tensor([5.6163e-01, 4.3740e-01, 2.8598e-05, 8.0734e-05, 2.7992e-04, 3.4574e-04, |
2.1625e-04, 1.5113e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([5.6163e-01, 4.3740e-01, 2.8598e-05, 8.0734e-05, 2.7992e-04, 3.4574e-04, |
2.1625e-04, 1.5113e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.4374, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.5616, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0010, device='cuda:1', grad_fn=<DivBackward0>)} |
tensor([9.2431e-01, 7.7906e-03, 6.6957e-02, 2.3671e-04, 4.2686e-05, 1.0364e-04, |
8.1538e-06, 5.5465e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.2431e-01, 7.7906e-03, 6.6957e-02, 2.3671e-04, 4.2686e-05, 1.0364e-04, |
8.1538e-06, 5.5465e-04], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0670, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.9243, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0087, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many towels are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 6') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
tensor([6.0595e-01, 2.1779e-02, 3.6745e-01, 2.6079e-03, 1.9825e-04, 6.8421e-04, |
1.6522e-04, 1.1669e-03], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.0595e-01, 2.1779e-02, 3.6745e-01, 2.6079e-03, 1.9825e-04, 6.8421e-04, |
1.6522e-04, 1.1669e-03], device='cuda:0', grad_fn=<SelectBackward0>) |
torch.Size([1, 3, 448, 448]) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6059, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.3675, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many seals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['How many towels 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([1, 3, 448, 448]) knan debug pixel values shape |
tensor([0.1962, 0.1536, 0.1128, 0.1970, 0.0442, 0.1464, 0.0360, 0.1138], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
6 ************* |
['5', '8', '4', '6', '3', '7', '11', '9'] tensor([0.1962, 0.1536, 0.1128, 0.1970, 0.0442, 0.1464, 0.0360, 0.1138], |
device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.1970, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.8030, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
question: ['How many seals 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: 1860 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
tensor([9.2772e-01, 2.9821e-02, 7.5411e-03, 3.1749e-02, 1.7360e-03, 7.4594e-04, |
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