Datasets:
TMarcus
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InternVL

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Registering RESULT step
Registering VQA_lavis step
Registering EVAL step
Registering RESULT step
Registering VQA_lavis step
Registering EVAL step
Registering RESULT step
ANSWER0=VQA(image=RIGHT,question='How many dogs are laying down on a couch?')
ANSWER1=EVAL(expr='{ANSWER0} >= 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=LEFT,question='How many people are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='How many vultures are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 5')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
torch.Size([3, 3, 448, 448])
torch.Size([3, 3, 448, 448])
torch.Size([13, 3, 448, 448])
question: ['How many vultures are in the image?'], responses:['37']
question: ['How many people 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']]
[('37', 0.12602601760154822), ('38', 0.12520142583637134), ('39', 0.12518201874785773), ('36', 0.12516664760231044), ('47', 0.12478763564484581), ('42', 0.12462790950563608), ('41', 0.12453088059191597), ('46', 0.12447746446951438)]
[['37', '38', '39', '36', '47', '42', '41', '46']]
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
question: ['How many animals are in the image?'], responses:['4']
[('4', 0.12804651361935848), ('5', 0.12521071898947128), ('3', 0.12515925906184908), ('8', 0.12489091845155219), ('6', 0.1245383468146311), ('1', 0.12441141527606933), ('2', 0.12403713327181662), ('11', 0.12370569451525179)]
[['4', '5', '3', '8', '6', '1', '2', '11']]
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
tensor([0.5649, 0.0321, 0.1046, 0.0215, 0.1570, 0.0118, 0.0587, 0.0495],
device='cuda:1', grad_fn=<SoftmaxBackward0>)
37 *************
['37', '38', '39', '36', '47', '42', '41', '46'] tensor([0.5649, 0.0321, 0.1046, 0.0215, 0.1570, 0.0118, 0.0587, 0.0495],
device='cuda:1', grad_fn=<SelectBackward0>)
tensor([1.0000e+00, 2.1585e-09, 5.4615e-10, 2.6271e-09, 9.4339e-10, 4.9897e-08,
4.6912e-08, 2.1011e-09], device='cuda:3', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 2.1585e-09, 5.4615e-10, 2.6271e-09, 9.4339e-10, 4.9897e-08,
4.6912e-08, 2.1011e-09], device='cuda:3', grad_fn=<SelectBackward0>)
question: ['How many dogs are laying down on a couch?'], responses:['1']
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)}
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(4.6912e-08, 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>)}
ANSWER0=VQA(image=LEFT,question='Is there a Basset Hound in the image?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([3, 3, 448, 448])
ANSWER0=VQA(image=RIGHT,question='How many seals are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
[('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])
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
question: ['Is there a Basset Hound 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
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
question: ['How many seals are in the image?'], responses:['11']
[('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([7, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
tensor([9.3173e-01, 1.6797e-04, 6.8100e-02, 1.9010e-10, 8.4513e-09, 8.0187e-08,
1.1988e-07, 9.3148e-09], device='cuda:2', grad_fn=<SoftmaxBackward0>)
4 *************
['4', '5', '3', '8', '6', '1', '2', '11'] tensor([9.3173e-01, 1.6797e-04, 6.8100e-02, 1.9010e-10, 8.4513e-09, 8.0187e-08,
1.1988e-07, 9.3148e-09], device='cuda:2', grad_fn=<SelectBackward0>)
tensor([1.0000e+00, 6.5062e-09, 2.5653e-09, 2.2470e-08, 3.6967e-10, 6.1276e-11,
3.7823e-10, 7.8344e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 6.5062e-09, 2.5653e-09, 2.2470e-08, 3.6967e-10, 6.1276e-11,
3.7823e-10, 7.8344e-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(2.5653e-09, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(-2.5653e-09, device='cuda:1', grad_fn=<DivBackward0>)}
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(1.1988e-07, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=RIGHT,question='How many zebras are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 1')
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
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
question: ['How many zebras are in the image?'], responses:['1']
tensor([9.4595e-01, 1.7326e-02, 1.3494e-02, 7.1505e-04, 2.5247e-05, 1.6279e-02,
3.0105e-03, 3.2050e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>)
11 *************
['11', '10', '12', '9', '8', '13', '7', '14'] tensor([9.4595e-01, 1.7326e-02, 1.3494e-02, 7.1505e-04, 2.5247e-05, 1.6279e-02,
3.0105e-03, 3.2050e-03], device='cuda:3', grad_fn=<SelectBackward0>)
ๆœ€ๅŽ็š„ๆฆ‚็Ž‡ๅˆ†ๅธƒไธบ: {True: tensor(0., device='cuda:3', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:3', grad_fn=<DivBackward0>)}
[('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']]
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
tensor([1.0000e+00, 2.8556e-10, 3.8346e-11, 3.1541e-11, 3.1050e-11, 3.8494e-09,
1.7258e-08, 3.8547e-11], device='cuda:0', grad_fn=<SoftmaxBackward0>)