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TMarcus
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InternVL

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[2024-10-24 09:40:10,827] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.42 | optimizer_gradients: 0.20 | optimizer_step: 0.30
[2024-10-24 09:40:10,827] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 7116.87 | backward_microstep: 6859.06 | backward_inner_microstep: 6789.07 | backward_allreduce_microstep: 69.92 | step_microstep: 7.46
[2024-10-24 09:40:10,827] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 7116.88 | backward: 6859.05 | backward_inner: 6789.08 | backward_allreduce: 69.90 | step: 7.47
94%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–| 4564/4844 [18:58:54<1:09:53, 14.98s/it]Registering VQA_lavis step
Registering EVAL step
Registering RESULT step
ANSWER0=VQA(image=RIGHT,question='How many men are sitting in barbers chairs in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
Registering VQA_lavis step
Registering VQA_lavis step
Registering EVAL step
Registering RESULT step
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} > 10')
FINAL_ANSWER=RESULT(var=ANSWER1)
Registering EVAL step
Registering RESULT step
ANSWER0=VQA(image=RIGHT,question='Is the train painted yellow in the front?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
Registering VQA_lavis step
Registering EVAL step
Registering RESULT step
ANSWER0=VQA(image=RIGHT,question='Does the image show a dog with a leash?')
ANSWER1=EVAL(expr='{ANSWER0}')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([1, 3, 448, 448])
torch.Size([1, 3, 448, 448])
torch.Size([7, 3, 448, 448])
torch.Size([13, 3, 448, 448])
question: ['Is the train painted yellow in the front?'], responses:['yes']
question: ['How many dogs are in the image?'], responses:['11']
[('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']]
[('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([1, 3, 448, 448]) knan debug pixel values shape
torch.Size([1, 3, 448, 448]) knan debug pixel values shape
tensor([1.0000e+00, 1.2881e-09, 2.4097e-09, 2.2153e-09, 1.8397e-11, 1.9282e-11,
9.9777e-12, 1.1318e-09], device='cuda:1', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.2881e-09, 2.4097e-09, 2.2153e-09, 1.8397e-11, 1.9282e-11,
9.9777e-12, 1.1318e-09], device='cuda:1', grad_fn=<SelectBackward0>)
tensor([9.7752e-01, 2.7185e-04, 6.5862e-03, 1.1575e-05, 1.1150e-08, 1.2302e-02,
8.7939e-08, 3.3121e-03], device='cuda:2', grad_fn=<SoftmaxBackward0>)
11 *************
['11', '10', '12', '9', '8', '13', '7', '14'] tensor([9.7752e-01, 2.7185e-04, 6.5862e-03, 1.1575e-05, 1.1150e-08, 1.2302e-02,
8.7939e-08, 3.3121e-03], device='cuda:2', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), False: tensor(2.4097e-09, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(-2.4097e-09, device='cuda:1', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many hyenas are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} == 1')
FINAL_ANSWER=RESULT(var=ANSWER1)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(0.9997, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.0003, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=LEFT,question='How many chimps are lying down in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 1')
FINAL_ANSWER=RESULT(var=ANSWER1)
torch.Size([13, 3, 448, 448])
torch.Size([3, 3, 448, 448])
question: ['Does the image show a dog with a leash?'], 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([7, 3, 448, 448]) knan debug pixel values shape
question: ['How many chimps are lying down 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([3, 3, 448, 448]) knan debug pixel values shape
question: ['How many men are sitting in barbers chairs in the image?'], responses:['5']
[('5', 0.12793059870235002), ('8', 0.12539646467821697), ('4', 0.12509737486793587), ('6', 0.12470234839853608), ('3', 0.12467331676337925), ('7', 0.12441254825093238), ('11', 0.12401867309944531), ('9', 0.12376867523920407)]
[['5', '8', '4', '6', '3', '7', '11', '9']]
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401
question: ['How many hyenas are in the image?'], responses:['1']
tensor([1.0000e+00, 2.5760e-07, 2.0699e-07, 2.1394e-08, 1.2898e-09, 4.9348e-09,
2.4669e-09, 8.0798e-10], device='cuda:2', grad_fn=<SoftmaxBackward0>)
2 *************
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 2.5760e-07, 2.0699e-07, 2.1394e-08, 1.2898e-09, 4.9348e-09,
2.4669e-09, 8.0798e-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(0., device='cuda:2', grad_fn=<MulBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', 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: 3401
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401
tensor([1.0000e+00, 1.3621e-08, 7.5079e-11, 3.3272e-08, 3.0600e-10, 5.9983e-10,
9.7650e-11, 1.0702e-08], device='cuda:3', grad_fn=<SoftmaxBackward0>)
yes *************
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.3621e-08, 7.5079e-11, 3.3272e-08, 3.0600e-10, 5.9983e-10,
9.7650e-11, 1.0702e-08], device='cuda:3', grad_fn=<SelectBackward0>)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: tensor(1., device='cuda:3', grad_fn=<DivBackward0>), False: tensor(7.5079e-11, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(-7.5079e-11, device='cuda:3', grad_fn=<DivBackward0>)}
ANSWER0=VQA(image=RIGHT,question='How many ferrets 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: 3401
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3401
question: ['How many ferrets 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']]