Datasets:
TMarcus
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InternVL

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ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([1, 3, 448, 448])
torch.Size([7, 3, 448, 448])
torch.Size([13, 3, 448, 448])
torch.Size([13, 3, 448, 448])
question: ['Is the dog'], 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
tensor([9.9999e-01, 1.6836e-07, 3.9670e-06, 6.8620e-07, 8.9530e-09, 7.1941e-09,
1.8758e-07, 7.3155e-07], device='cuda:1', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.9999e-01, 1.6836e-07, 3.9670e-06, 6.8620e-07, 8.9530e-09, 7.1941e-09,
1.8758e-07, 7.3155e-07], device='cuda:1', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(3.9670e-06, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.7551e-06, device='cuda:1', grad_fn=<DivBackward0>)}
question: ['How many wine bottles are in the image?'], responses:['six']
ANSWER0=VQA(image=RIGHT,question='Does the vase have a bulb shaped neck?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
[('7 eleven', 0.1258716720461554), ('dusk', 0.12512990238684168), ('blue', 0.12502287564185594), ('rose', 0.12495109740026594), ('peach', 0.12486403486105606), ('kitten', 0.12474151468778871), ('laundry', 0.12473504457146048), ('sunrise', 0.12468385840457588)]
[['7 eleven', 'dusk', 'blue', 'rose', 'peach', 'kitten', 'laundry', 'sunrise']]
torch.Size([13, 3, 448, 448])
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
question: ['Is someone holding the crab?'], responses:['no']
question: ['How many yellowish anemone are in the image?'], responses:['11']
[('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']]
[('11', 0.12740768001087358), ('10', 0.12548679249075975), ('12', 0.12538137681693887), ('9', 0.12485855662563465), ('8', 0.12469919178932766), ('13', 0.12431757055023795), ('7', 0.12396146028399917), ('14', 0.1238873714322284)]
[['11', '10', '12', '9', '8', '13', '7', '14']]
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: 3400
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
question: ['Does the vase have a bulb shaped neck?'], 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: 3400
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
tensor([9.7082e-05, 1.8231e-03, 6.2095e-04, 1.4057e-01, 6.1083e-01, 1.3403e-04,
7.9731e-02, 1.6620e-01], device='cuda:3', grad_fn=<SoftmaxBackward0>)
peach *************
['7 eleven', 'dusk', 'blue', 'rose', 'peach', 'kitten', 'laundry', 'sunrise'] tensor([9.7082e-05, 1.8231e-03, 6.2095e-04, 1.4057e-01, 6.1083e-01, 1.3403e-04,
7.9731e-02, 1.6620e-01], device='cuda:3', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {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>)}
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([5, 3, 448, 448])
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
question: ['How many 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']]
torch.Size([5, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
tensor([0.6070, 0.0821, 0.0256, 0.0116, 0.0012, 0.0387, 0.2252, 0.0086],
device='cuda:0', grad_fn=<SoftmaxBackward0>)
11 *************
['11', '10', '12', '9', '8', '13', '7', '14'] tensor([0.6070, 0.0821, 0.0256, 0.0116, 0.0012, 0.0387, 0.2252, 0.0086],
device='cuda:0', grad_fn=<SelectBackward0>)
tensor([1.0000e+00, 6.5878e-10, 5.2013e-07, 4.8854e-11, 6.9781e-10, 2.5005e-08,
1.1503e-09, 3.1061e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 6.5878e-10, 5.2013e-07, 4.8854e-11, 6.9781e-10, 2.5005e-08,
1.1503e-09, 3.1061e-07], device='cuda:2', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0.7748, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.2252, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=RIGHT,question='Is the sky cloudless in the image?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(6.5878e-10, device='cuda:2', grad_fn=<UnbindBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(8.3447e-07, device='cuda:2', grad_fn=<SubBackward0>)}
ANSWER0=VQA(image=LEFT,question='Is the full body of a dog facing right in the image?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
tensor([1.0000e+00, 1.6433e-09, 4.5277e-10, 4.3203e-10, 3.8714e-10, 5.1474e-08,
8.7801e-09, 3.5541e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 1.6433e-09, 4.5277e-10, 4.3203e-10, 3.8714e-10, 5.1474e-08,
8.7801e-09, 3.5541e-09], device='cuda:3', grad_fn=<SelectBackward0>)
torch.Size([3, 3, 448, 448])
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(8.7801e-09, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)}
torch.Size([13, 3, 448, 448])
question: ['Is the full body of a dog facing right 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']]
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
tensor([1.0000e+00, 2.4389e-09, 3.6174e-09, 2.3975e-09, 1.5454e-11, 1.3252e-11,
1.5899e-11, 1.6218e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.4389e-09, 3.6174e-09, 2.3975e-09, 1.5454e-11, 1.3252e-11,
1.5899e-11, 1.6218e-09], device='cuda:1', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), False: tensor(3.6174e-09, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(-3.6174e-09, device='cuda:1', grad_fn=<DivBackward0>)}
tensor([9.9999e-01, 2.0141e-09, 6.1442e-06, 5.4059e-10, 8.1320e-12, 8.0716e-10,
4.3323e-11, 1.0394e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.9999e-01, 2.0141e-09, 6.1442e-06, 5.4059e-10, 8.1320e-12, 8.0716e-10,
4.3323e-11, 1.0394e-09], device='cuda:2', grad_fn=<SelectBackward0>)
question: ['Is the sky cloudless in the image?'], responses:['yes']