Datasets:
TMarcus
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InternVL

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Registering EVAL step
Registering RESULT step
Registering VQA_lavis step
Registering EVAL step
Registering RESULT step
ANSWER0=VQA(image=RIGHT,question='Is there a stingray facing right in the image?')
ANSWER1=RESULT(var=ANSWER0)
ANSWER0=VQA(image=RIGHT,question='Are the animals on a snowy rocky cliff?')
FINAL_ANSWER=RESULT(var=ANSWER0)
ANSWER0=VQA(image=RIGHT,question='How many adults are paddling a canoe in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 3')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([3, 3, 448, 448])
ANSWER0=VQA(image=LEFT,question='Is the bird in the left image looking towards the left?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
torch.Size([7, 3, 448, 448])
torch.Size([7, 3, 448, 448])
question: ['Are the animals on a snowy rocky cliff?'], 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
question: ['Is there a stingray facing right in the image?'], responses:['yes']
question: ['How many adults are paddling a canoe in the image?'], responses:['3']
question: ['Is the bird in the left image looking towards the left?'], 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']]
[('3', 0.12809209985493852), ('4', 0.12520382509374006), ('1', 0.1251059160028928), ('5', 0.12483070991268265), ('8', 0.12458076282181878), ('2', 0.12413212281858195), ('6', 0.1241125313968017), ('12', 0.12394203209854344)]
[['3', '4', '1', '5', '8', '2', '6', '12']]
[('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
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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, 4.0774e-09, 7.1639e-11, 1.0041e-08, 1.2843e-11, 1.7456e-10,
1.1703e-11, 5.8925e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 4.0774e-09, 7.1639e-11, 1.0041e-08, 1.2843e-11, 1.7456e-10,
1.1703e-11, 5.8925e-09], device='cuda:1', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1., device='cuda:1', grad_fn=<UnbindBackward0>), False: tensor(7.1639e-11, device='cuda:1', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(-7.1639e-11, device='cuda:1', grad_fn=<SubBackward0>)}
ANSWER0=VQA(image=RIGHT,question='How many snow plows are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 1')
FINAL_ANSWER=RESULT(var=ANSWER1)
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
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
question: ['How many snow plows 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: 7, images per sample: 7.0, dynamic token length: 1865
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865
tensor([1.0000e+00, 1.1979e-07, 1.0093e-07, 1.0986e-11, 1.5569e-10, 1.9806e-09,
2.6645e-10, 3.5025e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.1979e-07, 1.0093e-07, 1.0986e-11, 1.5569e-10, 1.9806e-09,
2.6645e-10, 3.5025e-07], device='cuda:2', grad_fn=<SelectBackward0>)
tensor([9.9988e-01, 3.6109e-06, 1.0675e-06, 3.6659e-10, 4.9508e-12, 1.1591e-04,
1.7828e-11, 8.2434e-11], device='cuda:0', grad_fn=<SoftmaxBackward0>)
3 *************
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([9.9988e-01, 3.6109e-06, 1.0675e-06, 3.6659e-10, 4.9508e-12, 1.1591e-04,
1.7828e-11, 8.2434e-11], device='cuda:0', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1.1979e-07, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(4.7684e-07, device='cuda:2', grad_fn=<DivBackward0>)}
tensor([2.1827e-03, 5.7921e-09, 9.9782e-01, 1.8922e-09, 1.2968e-11, 6.4947e-12,
4.5445e-10, 2.9065e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>)
no *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([2.1827e-03, 5.7921e-09, 9.9782e-01, 1.8922e-09, 1.2968e-11, 6.4947e-12,
4.5445e-10, 2.9065e-09], device='cuda:3', grad_fn=<SelectBackward0>)
ANSWER0=VQA(image=LEFT,question='How many humans are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0.9999, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)}
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0.0022, device='cuda:3', grad_fn=<UnbindBackward0>), False: tensor(0.9978, device='cuda:3', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<SubBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many parrots are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='Are the sails furled in the image?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
torch.Size([7, 3, 448, 448])
torch.Size([13, 3, 448, 448])
question: ['How many humans are in the image?'], responses:['1']
question: ['How many parrots 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']]
[('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
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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: 1862
tensor([9.9999e-01, 1.0130e-05, 2.7578e-08, 2.4061e-06, 1.1032e-09, 1.2091e-10,
1.3101e-09, 2.5737e-11], device='cuda:1', grad_fn=<SoftmaxBackward0>)
2 *************