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question: ['How many power poles are in the image?'], responses:['1']
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question: ['How many elephants are in the image?'], responses:['6']
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[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)]
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[['1', '3', '4', '8', '6', '12', '2', '47']]
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[('6', 0.12794147189263105), ('8', 0.12539492259598553), ('12', 0.12539359088927945), ('5', 0.12471292164321114), ('4', 0.12443617393590153), ('1', 0.12417386497855347), ('11', 0.12398049124372558), ('3', 0.12396656282071232)]
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[['6', '8', '12', '5', '4', '1', '11', '3']]
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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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tensor([5.2392e-01, 4.3046e-02, 1.3975e-02, 2.8368e-03, 5.1374e-03, 2.6386e-03,
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4.0824e-01, 2.0605e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>)
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1 *************
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['1', '3', '4', '8', '6', '12', '2', '47'] tensor([5.2392e-01, 4.3046e-02, 1.3975e-02, 2.8368e-03, 5.1374e-03, 2.6386e-03,
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4.0824e-01, 2.0605e-04], device='cuda:1', grad_fn=<SelectBackward0>)
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
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ๆๅ็ๆฆ็ๅๅธไธบ: {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>)}
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ANSWER0=VQA(image=LEFT,question='How many animals are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} == 2')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([13, 3, 448, 448])
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
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question: ['How many animals are in the image?'], responses:['2']
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[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)]
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[['2', '3', '4', '1', '5', '8', '7', '29']]
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
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tensor([0.3268, 0.1864, 0.1204, 0.0302, 0.0502, 0.0141, 0.2713, 0.0006],
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device='cuda:2', grad_fn=<SoftmaxBackward0>)
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1 *************
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['1', '3', '4', '8', '6', '12', '2', '47'] tensor([0.3268, 0.1864, 0.1204, 0.0302, 0.0502, 0.0141, 0.2713, 0.0006],
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device='cuda:2', grad_fn=<SelectBackward0>)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.0950, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.9050, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)}
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tensor([0.4105, 0.1689, 0.0075, 0.3009, 0.0759, 0.0039, 0.0150, 0.0175],
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device='cuda:3', grad_fn=<SoftmaxBackward0>)
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6 *************
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['6', '8', '12', '5', '4', '1', '11', '3'] tensor([0.4105, 0.1689, 0.0075, 0.3009, 0.0759, 0.0039, 0.0150, 0.0175],
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device='cuda:3', grad_fn=<SelectBackward0>)
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ANSWER0=VQA(image=LEFT,question='How many people are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} == 2')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.0214, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9786, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=LEFT,question='How many shoes are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} == 1')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([13, 3, 448, 448])
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torch.Size([13, 3, 448, 448])
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torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
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tensor([8.2118e-01, 2.3295e-02, 6.6737e-03, 2.0332e-03, 2.6076e-03, 1.4390e-03,
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1.4270e-01, 6.3555e-05], device='cuda:0', grad_fn=<SoftmaxBackward0>)
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1 *************
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['1', '3', '4', '8', '6', '12', '2', '47'] tensor([8.2118e-01, 2.3295e-02, 6.6737e-03, 2.0332e-03, 2.6076e-03, 1.4390e-03,
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1.4270e-01, 6.3555e-05], device='cuda:0', grad_fn=<SelectBackward0>)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.8212, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.1788, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:0', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=LEFT,question='Are all of the bottles the same size?')
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ANSWER1=EVAL(expr='{ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([1, 3, 448, 448])
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question: ['Are all of the bottles the same size?'], responses:['yes']
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[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)]
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[['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate']]
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torch.Size([1, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326
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dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326
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tensor([5.9010e-01, 2.5651e-02, 3.8100e-01, 1.2787e-03, 2.0411e-04, 5.0560e-04,
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3.4442e-05, 1.2267e-03], device='cuda:0', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([5.9010e-01, 2.5651e-02, 3.8100e-01, 1.2787e-03, 2.0411e-04, 5.0560e-04,
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3.4442e-05, 1.2267e-03], device='cuda:0', grad_fn=<SelectBackward0>)
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question: ['How many people are in the image?'], responses:['2']
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0.5901, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(0.3810, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)}
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question: ['How many shoes are in the image?'], responses:['1']
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ANSWER0=VQA(image=LEFT,question='How many gorillas are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} == 4')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([3, 3, 448, 448])
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[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)]
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[['2', '3', '4', '1', '5', '8', '7', '29']]
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[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)]
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[['1', '3', '4', '8', '6', '12', '2', '47']]
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torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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question: ['How many gorillas are in the image?'], responses:['15']
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[('15', 0.12850265658859292), ('14', 0.12554598114685298), ('13', 0.12491622450863256), ('16', 0.12450938797787274), ('29', 0.12444750181633149), ('35', 0.12413627702798803), ('22', 0.12400388658176363), ('21', 0.12393808435196574)]
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[['15', '14', '13', '16', '29', '35', '22', '21']]
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torch.Size([3, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837
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dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837
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