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ANSWER1=EVAL(expr='{ANSWER0} == 1')
FINAL_ANSWER=RESULT(var=ANSWER1)
[('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']]
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396
torch.Size([13, 3, 448, 448])
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
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396
tensor([8.9588e-01, 5.0532e-02, 1.2006e-02, 3.4728e-02, 3.8965e-03, 1.4326e-03,
1.4333e-03, 9.4915e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>)
2 *************
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([8.9588e-01, 5.0532e-02, 1.2006e-02, 3.4728e-02, 3.8965e-03, 1.4326e-03,
1.4333e-03, 9.4915e-05], device='cuda:0', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.8959, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 3')
FINAL_ANSWER=RESULT(var=ANSWER1)
tensor([8.0848e-01, 1.8550e-02, 1.6947e-01, 1.7900e-03, 1.1646e-04, 4.5044e-04,
7.3459e-05, 1.0676e-03], device='cuda:3', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([8.0848e-01, 1.8550e-02, 1.6947e-01, 1.7900e-03, 1.1646e-04, 4.5044e-04,
7.3459e-05, 1.0676e-03], device='cuda:3', grad_fn=<SelectBackward0>)
torch.Size([13, 3, 448, 448])
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.8085, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.1695, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0220, device='cuda:3', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many antelopes are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 3')
FINAL_ANSWER=RESULT(var=ANSWER1)
question: ['How many animals are on the rock?'], responses:['1']
torch.Size([3, 3, 448, 448])
[('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']]
question: ['How many antelopes are in the image?'], responses:['1']
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
[('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([3, 3, 448, 448]) knan debug pixel values shape
tensor([0.5994, 0.0864, 0.0408, 0.0232, 0.0036, 0.2346, 0.0103, 0.0016],
device='cuda:2', grad_fn=<SoftmaxBackward0>)
3 *************
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([0.5994, 0.0864, 0.0408, 0.0232, 0.0036, 0.2346, 0.0103, 0.0016],
device='cuda:2', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.2346, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.7654, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:2', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many ferrets are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([13, 3, 448, 448])
question: ['How many dogs are in the image?'], responses:['2']
tensor([8.9374e-01, 1.9745e-02, 7.9772e-03, 3.0243e-03, 4.0107e-03, 2.4213e-03,
6.8918e-02, 1.5978e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([8.9374e-01, 1.9745e-02, 7.9772e-03, 3.0243e-03, 4.0107e-03, 2.4213e-03,
6.8918e-02, 1.5978e-04], device='cuda:3', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.0373, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9627, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)}
[('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']]
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 3')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([13, 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: 3396
question: ['How many ferrets are in the image?'], responses:['1']
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396
[('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
question: ['How many dogs are in the image?'], responses:['3']
[('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']]
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396
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([9.3829e-01, 1.1449e-02, 5.0794e-03, 1.6970e-03, 2.9850e-03, 1.5882e-03,
3.8733e-02, 1.8080e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.3829e-01, 1.1449e-02, 5.0794e-03, 1.6970e-03, 2.9850e-03, 1.5882e-03,
3.8733e-02, 1.8080e-04], device='cuda:1', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.9383, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.0617, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many parrots are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([7, 3, 448, 448])
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
question: ['How many parrots are in the image?'], responses:['1']
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3396
[('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
tensor([9.3865e-01, 1.4250e-02, 3.4922e-03, 4.1241e-02, 1.2062e-03, 6.2316e-04,
4.8606e-04, 5.5098e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>)
2 *************
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([9.3865e-01, 1.4250e-02, 3.4922e-03, 4.1241e-02, 1.2062e-03, 6.2316e-04,
4.8606e-04, 5.5098e-05], device='cuda:0', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.9857, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:0', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many beetles are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 2')
FINAL_ANSWER=RESULT(var=ANSWER1)