text stringlengths 0 1.16k |
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torch.Size([7, 3, 448, 448]) |
[('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([5, 3, 448, 448]) knan debug pixel values shape |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
question: ['How many striped animals 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']] |
question: ['What color are the vases?'], responses:['green'] |
[('green', 0.1326115459908909), ('yellow', 0.12668030247077625), ('red', 0.12551779073733718), ('wild', 0.12324669870262604), ('orange and blue', 0.12319974118412196), ('bronze', 0.1230515752050065), ('pink', 0.12286305245049417), ('red white blue', 0.12282929325874692)] |
[['green', 'yellow', 'red', 'wild', 'orange and blue', 'bronze', 'pink', 'red white blue']] |
torch.Size([7, 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 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398 |
tensor([7.5867e-01, 1.3153e-01, 3.5402e-02, 5.4936e-02, 1.3025e-02, 3.2994e-03, |
2.9108e-03, 2.3080e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([7.5867e-01, 1.3153e-01, 3.5402e-02, 5.4936e-02, 1.3025e-02, 3.2994e-03, |
2.9108e-03, 2.3080e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7587, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.2413, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many trains 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 |
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([9.3517e-01, 5.4534e-03, 6.6178e-03, 8.8892e-04, 7.4647e-03, 1.7699e-02, |
2.4815e-02, 1.8915e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
green ************* |
['green', 'yellow', 'red', 'wild', 'orange and blue', 'bronze', 'pink', 'red white blue'] tensor([9.3517e-01, 5.4534e-03, 6.6178e-03, 8.8892e-04, 7.4647e-03, 1.7699e-02, |
2.4815e-02, 1.8915e-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: ['How many trains 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: 3398 |
tensor([8.6995e-01, 2.8220e-02, 9.7606e-02, 1.6825e-03, 1.8305e-04, 7.6259e-04, |
9.6310e-05, 1.4989e-03], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.6995e-01, 2.8220e-02, 9.7606e-02, 1.6825e-03, 1.8305e-04, 7.6259e-04, |
9.6310e-05, 1.4989e-03], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8700, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.0976, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0324, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Is the dog wearing a collar?') |
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 |
tensor([7.7226e-01, 4.9382e-02, 2.4779e-02, 9.1145e-03, 1.1726e-02, 5.8950e-03, |
1.2610e-01, 7.4362e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([7.7226e-01, 4.9382e-02, 2.4779e-02, 9.1145e-03, 1.1726e-02, 5.8950e-03, |
1.2610e-01, 7.4362e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.7723, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.2277, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='Is the dog wearing a collar?') |
FINAL_ANSWER=RESULT(var=ANSWER0) |
torch.Size([7, 3, 448, 448]) |
Encountered ExecuteError: CUDA out of memory. Tried to allocate 5.85 GiB. GPU 2 has a total capacty of 44.34 GiB of which 4.60 GiB is free. Including non-PyTorch memory, this process has 39.73 GiB memory in use. Of the allocated memory 36.88 GiB is allocated by PyTorch, and 2.22 GiB is reserved by PyTorch but unallocat... |
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str' |
ζεηζ¦ηεεΈδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998} |
question: ['Is the dog wearing a collar?'], responses:['yes'] |
ANSWER0=VQA(image=RIGHT,question='How many bottles are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 6') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('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([7, 3, 448, 448]) |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 |
question: ['How many bottles are in the image?'], responses:['6'] |
[('6', 0.12794147189263105), ('8', 0.12539492259598553), ('12', 0.12539359088927945), ('5', 0.12471292164321114), ('4', 0.12443617393590153), ('1', 0.12417386497855347), ('11', 0.12398049124372558), ('3', 0.12396656282071232)] |
[['6', '8', '12', '5', '4', '1', '11', '3']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 |
tensor([5.1310e-01, 1.7908e-01, 3.9958e-02, 2.4096e-01, 1.7558e-02, 3.7972e-03, |
5.4078e-03, 1.4406e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([5.1310e-01, 1.7908e-01, 3.9958e-02, 2.4096e-01, 1.7558e-02, 3.7972e-03, |
5.4078e-03, 1.4406e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.5131, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.4869, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
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([8.8332e-01, 1.5928e-02, 9.9107e-02, 8.5229e-04, 4.1472e-05, 1.5831e-04, |
3.5962e-05, 5.5374e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.8332e-01, 1.5928e-02, 9.9107e-02, 8.5229e-04, 4.1472e-05, 1.5831e-04, |
3.5962e-05, 5.5374e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.8833, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(0.0991, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0176, device='cuda:0', grad_fn=<SubBackward0>)} |
tensor([0.5156, 0.1897, 0.0097, 0.2419, 0.0231, 0.0018, 0.0145, 0.0037], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
6 ************* |
['6', '8', '12', '5', '4', '1', '11', '3'] tensor([0.5156, 0.1897, 0.0097, 0.2419, 0.0231, 0.0018, 0.0145, 0.0037], |
device='cuda:2', grad_fn=<SelectBackward0>) |
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