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torch.Size([13, 3, 448, 448])
question: ['Is the instrument broken apart into several pieces?'], 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([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: 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
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326
tensor([1.0000e+00, 5.5475e-10, 1.5806e-07, 1.9544e-12, 5.0148e-12, 1.9224e-09,
2.7935e-10, 6.3107e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 5.5475e-10, 1.5806e-07, 1.9544e-12, 5.0148e-12, 1.9224e-09,
2.7935e-10, 6.3107e-07], device='cuda:0', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็އๅˆ†ๅธƒไธบ: {True: tensor(5.5475e-10, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(7.1526e-07, device='cuda:0', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([13, 3, 448, 448])
question: ['Are there animals in the water?'], responses:['yes']
question: ['Is the item facing forward?'], responses:['no']
[('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']]
[('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
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
question: ['How many mountain goats 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']]
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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, 1.2505e-08, 4.9148e-10, 4.1135e-07, 1.2210e-09, 6.0581e-09,
4.5930e-10, 4.5308e-08], device='cuda:1', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.2505e-08, 4.9148e-10, 4.1135e-07, 1.2210e-09, 6.0581e-09,
4.5930e-10, 4.5308e-08], device='cuda:1', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็އๅˆ†ๅธƒไธบ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(4.9148e-10, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(4.7635e-07, device='cuda:1', grad_fn=<DivBackward0>)}
tensor([1.0000e+00, 2.0817e-08, 1.4115e-07, 8.0377e-12, 2.0922e-12, 3.9024e-10,
6.8158e-11, 3.9576e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 2.0817e-08, 1.4115e-07, 8.0377e-12, 2.0922e-12, 3.9024e-10,
6.8158e-11, 3.9576e-08], device='cuda:2', grad_fn=<SelectBackward0>)
ANSWER0=VQA(image=RIGHT,question='Is there a human in the image?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([3, 3, 448, 448])
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396
ๆœ€ๅŽ็š„ๆฆ‚็އๅˆ†ๅธƒไธบ: {True: tensor(2.0817e-08, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.3842e-07, device='cuda:2', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many birds are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} <= 1')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
question: ['Is there a human in the image?'], 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']]
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396
question: ['How many birds 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: 13, images per sample: 13.0, dynamic token length: 3396
tensor([1.0000e+00, 1.1427e-08, 1.2524e-10, 9.5786e-08, 1.3331e-09, 2.9006e-10,
3.8103e-10, 2.1786e-08], device='cuda:1', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.1427e-08, 1.2524e-10, 9.5786e-08, 1.3331e-09, 2.9006e-10,
3.8103e-10, 2.1786e-08], device='cuda:1', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็އๅˆ†ๅธƒไธบ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.2524e-10, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1908e-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
tensor([9.9978e-01, 2.1654e-04, 1.1608e-07, 2.1811e-08, 7.3631e-09, 5.2511e-10,
4.5541e-09, 1.1926e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>)
2 *************
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.9978e-01, 2.1654e-04, 1.1608e-07, 2.1811e-08, 7.3631e-09, 5.2511e-10,
4.5541e-09, 1.1926e-09], device='cuda:3', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็އๅˆ†ๅธƒไธบ: {True: tensor(0.9998, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0002, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=RIGHT,question='Is Nikki Minaj in the image?')
ANSWER1=EVAL(expr='not {ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([3, 3, 448, 448])
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396
question: ['Is Nikki Minaj 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']]
tensor([1.0000e+00, 2.9926e-10, 8.1178e-11, 1.3175e-10, 9.7850e-11, 1.1479e-08,
2.4381e-09, 2.3586e-10], device='cuda:0', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 2.9926e-10, 8.1178e-11, 1.3175e-10, 9.7850e-11, 1.1479e-08,
2.4381e-09, 2.3586e-10], device='cuda:0', grad_fn=<SelectBackward0>)
torch.Size([3, 3, 448, 448]) knan debug pixel values shape