Datasets:
TMarcus
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InternVL

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FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='Is there an animal sitting on a concrete railing in the image?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='Are the golf balls in shadow?')
ANSWER1=EVAL(expr='not {ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([1, 3, 448, 448])
torch.Size([7, 3, 448, 448])
torch.Size([7, 3, 448, 448])
torch.Size([13, 3, 448, 448])
question: ['Is there an animal sitting on a concrete railing 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([1, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331
tensor([1.0000e+00, 6.8503e-10, 1.5135e-06, 3.0043e-10, 4.9654e-09, 2.9957e-07,
1.0484e-08, 1.0010e-06], device='cuda:0', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 6.8503e-10, 1.5135e-06, 3.0043e-10, 4.9654e-09, 2.9957e-07,
1.0484e-08, 1.0010e-06], device='cuda:0', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(6.8503e-10, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.8610e-06, device='cuda:0', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='Are there a mother and her pups in the image?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
question: ['Is there a dog sitting in the image?'], responses:['yes']
question: ['Are the golf balls in shadow?'], 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: ['Is wine pouring into the glass?'], responses:['yes']
question: ['Are there a mother and her pups 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']]
[('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]) knan debug pixel values shape
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864
tensor([1.0000e+00, 2.3727e-08, 1.7188e-09, 3.4823e-07, 4.9878e-08, 2.2863e-08,
1.3824e-09, 1.0554e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.3727e-08, 1.7188e-09, 3.4823e-07, 4.9878e-08, 2.2863e-08,
1.3824e-09, 1.0554e-07], device='cuda:1', grad_fn=<SelectBackward0>)
tensor([1.0000e+00, 4.3635e-09, 7.3364e-08, 2.1849e-11, 4.9411e-11, 1.7376e-09,
1.2431e-10, 1.7420e-07], device='cuda:3', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 4.3635e-09, 7.3364e-08, 2.1849e-11, 4.9411e-11, 1.7376e-09,
1.2431e-10, 1.7420e-07], device='cuda:3', grad_fn=<SelectBackward0>)
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.7188e-09, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(4.7512e-07, device='cuda:1', grad_fn=<DivBackward0>)}
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(4.3635e-09, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(3.5763e-07, device='cuda:3', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many sea lions are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 1')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=LEFT,question='Are all dogs wearing blue harnesses?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
torch.Size([7, 3, 448, 448])
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865
tensor([1.0000e+00, 8.3400e-09, 5.2617e-11, 9.3494e-08, 1.5518e-10, 1.0861e-09,
1.5775e-10, 1.5984e-08], device='cuda:0', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 8.3400e-09, 5.2617e-11, 9.3494e-08, 1.5518e-10, 1.0861e-09,
1.5775e-10, 1.5984e-08], device='cuda:0', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(5.2617e-11, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1916e-07, device='cuda:0', grad_fn=<DivBackward0>)}
question: ['How many sea lions are in the image?'], responses:['1']
question: ['Are all dogs wearing blue harnesses?'], responses:['no']
[('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']]
[('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
tensor([1.0000e+00, 2.6589e-08, 5.5793e-11, 3.3867e-08, 1.4157e-09, 7.0127e-10,
6.6376e-11, 1.0591e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.6589e-08, 5.5793e-11, 3.3867e-08, 1.4157e-09, 7.0127e-10,
6.6376e-11, 1.0591e-08], device='cuda:2', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(5.5793e-11, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1915e-07, device='cuda:2', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=RIGHT,question='Does the image contain food inside of a bowl?')
FINAL_ANSWER=RESULT(var=ANSWER0)
torch.Size([13, 3, 448, 448])