text
stringlengths 0
1.16k
|
|---|
question: ['How many hairless chimps are in the image?'], responses:['2']
|
question: ['How many pieces of food are on the dish?'], responses:['7']
|
question: ['How many whole pizzas are in the image?'], responses:['1']
|
[('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']]
|
[('7', 0.12828776251745355), ('8', 0.1258361832781132), ('11', 0.12481772898325143), ('5', 0.124759881092759), ('9', 0.12447036165452931), ('10', 0.1239759375399529), ('6', 0.12393017600998846), ('12', 0.12392196892395223)]
|
[['7', '8', '11', '5', '9', '10', '6', '12']]
|
[('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([1, 3, 448, 448]) knan debug pixel values shape
|
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
|
torch.Size([7, 3, 448, 448]) knan debug pixel values shape
|
tensor([9.9753e-01, 2.1181e-06, 1.9096e-07, 4.8456e-10, 8.7742e-10, 1.8325e-08,
|
2.4726e-03, 1.0367e-10], device='cuda:3', grad_fn=<SoftmaxBackward0>)
|
1 *************
|
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.9753e-01, 2.1181e-06, 1.9096e-07, 4.8456e-10, 8.7742e-10, 1.8325e-08,
|
2.4726e-03, 1.0367e-10], device='cuda:3', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.9975, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.0025, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)}
|
question: ['How many dogs are lying on the ground?'], responses:['0']
|
[('0', 0.13077743594303964), ('circles', 0.12449813349255197), ('maroon', 0.12428926693968681), ('large', 0.1242263466991631), ('rooster', 0.12409315512763705), ('nuts', 0.12408018414184876), ('beige', 0.1240288472550799), ('bottle', 0.12400663040099273)]
|
[['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle']]
|
torch.Size([13, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
|
tensor([1.0000e+00, 5.3995e-08, 2.8008e-09, 2.1478e-08, 1.5879e-10, 6.5246e-10,
|
5.4419e-10, 5.0645e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>)
|
2 *************
|
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 5.3995e-08, 2.8008e-09, 2.1478e-08, 1.5879e-10, 6.5246e-10,
|
5.4419e-10, 5.0645e-10], device='cuda:1', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(2.1478e-08, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)}
|
tensor([0.8212, 0.0008, 0.1258, 0.0091, 0.0055, 0.0033, 0.0263, 0.0080],
|
device='cuda:2', grad_fn=<SoftmaxBackward0>)
|
7 *************
|
['7', '8', '11', '5', '9', '10', '6', '12'] tensor([0.8212, 0.0008, 0.1258, 0.0091, 0.0055, 0.0033, 0.0263, 0.0080],
|
device='cuda:2', grad_fn=<SelectBackward0>)
|
ANSWER0=VQA(image=RIGHT,question='How many pug dogs are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} == 3')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.7881e-07, device='cuda:2', grad_fn=<DivBackward0>)}
|
torch.Size([3, 3, 448, 448])
|
ANSWER0=VQA(image=RIGHT,question='How many dogs are in the image?')
|
ANSWER1=EVAL(expr='{ANSWER0} <= 2')
|
FINAL_ANSWER=RESULT(var=ANSWER1)
|
torch.Size([3, 3, 448, 448])
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3397
|
question: ['How many pug dogs 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']]
|
question: ['How many dogs are in the image?'], responses:['11']
|
torch.Size([3, 3, 448, 448]) knan debug pixel values shape
|
[('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([3, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
|
tensor([1.0000e+00, 1.8582e-10, 7.8681e-11, 1.5285e-10, 1.4353e-10, 1.1469e-08,
|
2.2994e-09, 1.5407e-10], device='cuda:1', grad_fn=<SoftmaxBackward0>)
|
1 *************
|
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([1.0000e+00, 1.8582e-10, 7.8681e-11, 1.5285e-10, 1.4353e-10, 1.1469e-08,
|
2.2994e-09, 1.5407e-10], device='cuda:1', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.8582e-10, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(1., device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)}
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3398
|
tensor([9.4872e-01, 1.3533e-02, 5.9452e-04, 1.1941e-02, 1.1104e-03, 3.1823e-04,
|
2.3749e-02, 3.2512e-05], device='cuda:2', grad_fn=<SoftmaxBackward0>)
|
11 *************
|
['11', '10', '12', '9', '8', '13', '7', '14'] tensor([9.4872e-01, 1.3533e-02, 5.9452e-04, 1.1941e-02, 1.1104e-03, 3.1823e-04,
|
2.3749e-02, 3.2512e-05], device='cuda:2', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:2', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.1921e-07, device='cuda:2', grad_fn=<DivBackward0>)}
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3399
|
tensor([1.0000e+00, 2.3428e-08, 5.0922e-08, 1.4798e-10, 4.3419e-07, 6.0942e-09,
|
1.2974e-07, 6.5558e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>)
|
0 *************
|
['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle'] tensor([1.0000e+00, 2.3428e-08, 5.0922e-08, 1.4798e-10, 4.3419e-07, 6.0942e-09,
|
1.2974e-07, 6.5558e-07], device='cuda:0', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0., device='cuda:0', grad_fn=<MulBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(1.4305e-06, device='cuda:0', grad_fn=<DivBackward0>)}
|
ANSWER0=VQA(image=RIGHT,question='Does the dog on the right have its tongue sticking out?')
|
ANSWER1=RESULT(var=ANSWER0)
|
torch.Size([13, 3, 448, 448])
|
question: ['Does the dog on the right have its tongue sticking out?'], 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([13, 3, 448, 448]) knan debug pixel values shape
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
|
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: 3400
|
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3400
|
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
|
tensor([1.0000e+00, 2.4240e-08, 9.3435e-11, 3.4259e-08, 1.7602e-10, 1.5803e-09,
|
6.8206e-11, 1.7090e-08], device='cuda:0', grad_fn=<SoftmaxBackward0>)
|
yes *************
|
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 2.4240e-08, 9.3435e-11, 3.4259e-08, 1.7602e-10, 1.5803e-09,
|
6.8206e-11, 1.7090e-08], device='cuda:0', grad_fn=<SelectBackward0>)
|
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(9.3435e-11, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(1.1912e-07, device='cuda:0', grad_fn=<SubBackward0>)}
|
[2024-10-24 10:33:15,343] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.45 | optimizer_gradients: 0.26 | optimizer_step: 0.32
|
[2024-10-24 10:33:15,343] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 9032.86 | backward_microstep: 8767.06 | backward_inner_microstep: 8761.12 | backward_allreduce_microstep: 5.87 | step_microstep: 7.39
|
[2024-10-24 10:33:15,343] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 9032.88 | backward: 8767.05 | backward_inner: 8761.14 | backward_allreduce: 5.83 | step: 7.40
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.