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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321
dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321
question: ['How many layered dessert portions are in the image?'], responses:['2']
tensor([9.9770e-01, 1.5959e-07, 2.2924e-03, 4.0112e-07, 3.6370e-08, 4.0897e-09,
5.7718e-08, 2.3126e-06], device='cuda:0', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.9770e-01, 1.5959e-07, 2.2924e-03, 4.0112e-07, 3.6370e-08, 4.0897e-09,
5.7718e-08, 2.3126e-06], device='cuda:0', grad_fn=<SelectBackward0>)
[('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']]
tensor([1.0000e+00, 4.7450e-10, 4.4849e-07, 2.1132e-12, 2.3683e-12, 1.9429e-09,
8.7748e-11, 1.0030e-06], device='cuda:3', grad_fn=<SoftmaxBackward0>)
no *************
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 4.7450e-10, 4.4849e-07, 2.1132e-12, 2.3683e-12, 1.9429e-09,
8.7748e-11, 1.0030e-06], device='cuda:3', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.9977, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(2.9218e-06, device='cuda:0', grad_fn=<DivBackward0>)}
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(4.7450e-10, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.4305e-06, device='cuda:3', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many fish are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 0')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 1')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([5, 3, 448, 448]) knan debug pixel values shape
torch.Size([13, 3, 448, 448])
torch.Size([13, 3, 448, 448])
question: ['How many people 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']]
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
tensor([1.0000e+00, 1.2483e-06, 1.6990e-08, 3.3597e-07, 1.4138e-09, 5.3349e-10,
1.8914e-09, 5.8808e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>)
2 *************
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 1.2483e-06, 1.6990e-08, 3.3597e-07, 1.4138e-09, 5.3349e-10,
1.8914e-09, 5.8808e-10], device='cuda:2', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.6056e-06, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many human scuba divers are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 1')
FINAL_ANSWER=RESULT(var=ANSWER1)
question: ['How many fish are in the image?'], responses:['1']
question: ['How many animals are in the image?'], responses:['1']
torch.Size([13, 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']]
[('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
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
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 human scuba divers 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']]
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
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([1.0000e+00, 3.3921e-08, 1.3260e-07, 6.1056e-09, 6.9037e-10, 1.2618e-08,
1.0180e-09, 6.2864e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>)
2 *************
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 3.3921e-08, 1.3260e-07, 6.1056e-09, 6.9037e-10, 1.2618e-08,
1.0180e-09, 6.2864e-09], device='cuda:1', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.8713e-07, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(-1.1921e-07, device='cuda:1', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many elephants 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
tensor([1.0000e+00, 5.7357e-09, 9.1821e-10, 1.9212e-09, 6.0928e-10, 7.7333e-08,
2.5360e-07, 9.5876e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 5.7357e-09, 9.1821e-10, 1.9212e-09, 6.0928e-10, 7.7333e-08,
2.5360e-07, 9.5876e-10], device='cuda:3', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: tensor([1.0000e+00, 3.2242e-08, 2.4862e-09, 1.3489e-10, 2.2590e-10, 2.2994e-09,
7.9799e-08, 1.5767e-10], device='cuda:0', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] {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>)}
tensor([1.0000e+00, 3.2242e-08, 2.4862e-09, 1.3489e-10, 2.2590e-10, 2.2994e-09,
7.9799e-08, 1.5767e-10], device='cuda:0', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.1735e-07, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)}
question: ['How many elephants 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']]
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
tensor([1.0000e+00, 3.6417e-10, 3.1297e-11, 5.3238e-11, 3.0812e-11, 9.3827e-09,
1.1366e-06, 6.5370e-11], device='cuda:2', grad_fn=<SoftmaxBackward0>)
1 *************
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 3.6417e-10, 3.1297e-11, 5.3238e-11, 3.0812e-11, 9.3827e-09,
1.1366e-06, 6.5370e-11], device='cuda:2', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.1465e-06, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)}
tensor([1.0000e+00, 9.1326e-07, 3.0225e-09, 1.3867e-08, 1.2575e-09, 4.0745e-10,
2.8393e-09, 7.6603e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>)
2 *************
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 9.1326e-07, 3.0225e-09, 1.3867e-08, 1.2575e-09, 4.0745e-10,
2.8393e-09, 7.6603e-10], device='cuda:1', grad_fn=<SelectBackward0>)