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Registering EVAL step
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Registering RESULT step
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Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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ANSWER0=VQA(image=LEFT,question='Is the primate in the image on the left with its mouth wide open?')
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ANSWER1=EVAL(expr='{ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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ANSWER0=VQA(image=RIGHT,question='Is the gorilla resting its hand against part of its own body?')
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ANSWER1=EVAL(expr='{ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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ANSWER0=VQA(image=RIGHT,question='How many fish 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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ANSWER0=VQA(image=RIGHT,question='Is the dog in the image being held on a leash?')
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ANSWER1=EVAL(expr='{ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([11, 3, 448, 448])
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torch.Size([7, 3, 448, 448])
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torch.Size([3, 3, 448, 448])
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torch.Size([13, 3, 448, 448])
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question: ['Is the dog in the image being held on a leash?'], responses:['no']
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[('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)]
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[['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock']]
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torch.Size([3, 3, 448, 448]) knan debug pixel values shape
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question: ['Is the primate in the image on the left with its mouth wide open?'], 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([7, 3, 448, 448]) knan debug pixel values shape
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question: ['Is the gorilla resting its hand against part of its own body?'], 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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tensor([1.0000e+00, 2.5398e-10, 4.2665e-07, 1.0816e-11, 3.5698e-11, 1.6525e-09,
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9.3256e-11, 2.9005e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>)
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no *************
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['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 2.5398e-10, 4.2665e-07, 1.0816e-11, 3.5698e-11, 1.6525e-09,
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9.3256e-11, 2.9005e-07], device='cuda:2', grad_fn=<SelectBackward0>)
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question: ['How many fish are in the image?'], responses:['1']
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(2.5398e-10, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(7.1526e-07, device='cuda:2', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='How many beds 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([7, 3, 448, 448])
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torch.Size([11, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 11, images per sample: 11.0, dynamic token length: 2890
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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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dynamic ViT batch size: 11, images per sample: 11.0, dynamic token length: 2893
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dynamic ViT batch size: 11, images per sample: 11.0, dynamic token length: 2890
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question: ['How many beds are in the image?'], responses:['0']
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[('0', 0.13077743594303964), ('circles', 0.12449813349255197), ('maroon', 0.12428926693968681), ('large', 0.1242263466991631), ('rooster', 0.12409315512763705), ('nuts', 0.12408018414184876), ('beige', 0.1240288472550799), ('bottle', 0.12400663040099273)]
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[['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle']]
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torch.Size([7, 3, 448, 448]) knan debug pixel values shape
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dynamic ViT batch size: 11, images per sample: 11.0, dynamic token length: 2891
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tensor([1.0000e+00, 3.6179e-09, 2.0930e-11, 1.1016e-08, 3.9777e-10, 8.3277e-10,
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3.1054e-11, 8.8325e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 3.6179e-09, 2.0930e-11, 1.1016e-08, 3.9777e-10, 8.3277e-10,
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3.1054e-11, 8.8325e-09], device='cuda:1', grad_fn=<SelectBackward0>)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), False: tensor(2.0930e-11, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(-2.0930e-11, device='cuda:1', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=LEFT,question='How many water buffaloes 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: 11, images per sample: 11.0, dynamic token length: 2890
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dynamic ViT batch size: 11, images per sample: 11.0, dynamic token length: 2890
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dynamic ViT batch size: 11, images per sample: 11.0, dynamic token length: 2891
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dynamic ViT batch size: 11, images per sample: 11.0, dynamic token length: 2891
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question: ['How many water buffaloes are in the image?'], responses:['2']
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tensor([1.0000e+00, 2.2328e-07, 2.6095e-08, 1.7694e-10, 9.6764e-07, 4.3700e-08,
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1.8010e-07, 1.5747e-07], device='cuda:2', grad_fn=<SoftmaxBackward0>)
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0 *************
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['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle'] tensor([1.0000e+00, 2.2328e-07, 2.6095e-08, 1.7694e-10, 9.6764e-07, 4.3700e-08,
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1.8010e-07, 1.5747e-07], device='cuda:2', grad_fn=<SelectBackward0>)
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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.6689e-06, device='cuda:2', grad_fn=<DivBackward0>)}
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tensor([9.9999e-01, 7.9426e-09, 5.4222e-06, 2.9163e-08, 2.0704e-11, 1.8688e-11,
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7.2938e-10, 4.5067e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>)
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yes *************
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['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([9.9999e-01, 7.9426e-09, 5.4222e-06, 2.9163e-08, 2.0704e-11, 1.8688e-11,
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7.2938e-10, 4.5067e-09], device='cuda:0', grad_fn=<SelectBackward0>)
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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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ๆๅ็ๆฆ็ๅๅธไธบ: {True: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(5.4222e-06, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(-5.7796e-08, device='cuda:0', grad_fn=<DivBackward0>)}
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ANSWER0=VQA(image=RIGHT,question='How many cheetas are in the image?')
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ANSWER1=EVAL(expr='{ANSWER0} == 3')
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FINAL_ANSWER=RESULT(var=ANSWER1)
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torch.Size([3, 3, 448, 448])
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torch.Size([13, 3, 448, 448]) knan debug pixel values shape
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question: ['How many cheetas are in the image?'], responses:['1']
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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([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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tensor([1.0000e+00, 4.1957e-10, 1.4472e-10, 2.9810e-10, 2.2414e-10, 2.4337e-08,
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