text stringlengths 0 1.16k |
|---|
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
question: ['Does the duck in the image have its beak on the ground?'], 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 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 |
tensor([9.8247e-01, 3.7704e-03, 1.6202e-03, 7.6065e-04, 8.6456e-04, 1.1140e-03, |
9.3346e-03, 6.2338e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([9.8247e-01, 3.7704e-03, 1.6202e-03, 7.6065e-04, 8.6456e-04, 1.1140e-03, |
9.3346e-03, 6.2338e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0175, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9825, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many towels are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 6') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
question: ['How many towels are in the image?'], responses:['6'] |
question: ['Does the image have a white background?'], responses:['yes'] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 |
[('6', 0.12794147189263105), ('8', 0.12539492259598553), ('12', 0.12539359088927945), ('5', 0.12471292164321114), ('4', 0.12443617393590153), ('1', 0.12417386497855347), ('11', 0.12398049124372558), ('3', 0.12396656282071232)] |
[['6', '8', '12', '5', '4', '1', '11', '3']] |
torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
[('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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([0.2282, 0.1921, 0.0814, 0.2270, 0.1385, 0.0176, 0.0539, 0.0614], |
device='cuda:1', grad_fn=<SoftmaxBackward0>) |
6 ************* |
['6', '8', '12', '5', '4', '1', '11', '3'] tensor([0.2282, 0.1921, 0.0814, 0.2270, 0.1385, 0.0176, 0.0539, 0.0614], |
device='cuda:1', grad_fn=<SelectBackward0>) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.2282, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.7718, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='Does an animal in the image have wheels?') |
ANSWER1=EVAL(expr='{ANSWER0}') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
tensor([6.0290e-01, 4.7907e-02, 2.2657e-02, 6.6717e-03, 1.0039e-02, 6.2100e-03, |
3.0321e-01, 4.0836e-04], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
1 ************* |
['1', '3', '4', '8', '6', '12', '2', '47'] tensor([6.0290e-01, 4.7907e-02, 2.2657e-02, 6.6717e-03, 1.0039e-02, 6.2100e-03, |
3.0321e-01, 4.0836e-04], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.3032, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.6968, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many animals are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 3') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([1, 3, 448, 448]) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 |
question: ['How many animals are in the image?'], responses:['3'] |
[('3', 0.12809209985493852), ('4', 0.12520382509374006), ('1', 0.1251059160028928), ('5', 0.12483070991268265), ('8', 0.12458076282181878), ('2', 0.12413212281858195), ('6', 0.1241125313968017), ('12', 0.12394203209854344)] |
[['3', '4', '1', '5', '8', '2', '6', '12']] |
torch.Size([1, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
question: ['Does an animal in the image have wheels?'], responses:['no'] |
tensor([0.6352, 0.1514, 0.0358, 0.0407, 0.0033, 0.1179, 0.0141, 0.0016], |
device='cuda:2', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([0.6352, 0.1514, 0.0358, 0.0407, 0.0033, 0.1179, 0.0141, 0.0016], |
device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6352, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(0.3648, 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 dogs are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('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)] |
[['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock']] |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
tensor([6.2613e-01, 1.9515e-02, 3.5159e-01, 1.4983e-03, 8.3435e-05, 4.0385e-04, |
8.0078e-05, 7.0021e-04], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([6.2613e-01, 1.9515e-02, 3.5159e-01, 1.4983e-03, 8.3435e-05, 4.0385e-04, |
8.0078e-05, 7.0021e-04], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.6261, device='cuda:0', grad_fn=<UnbindBackward0>), False: tensor(0.3516, device='cuda:0', grad_fn=<UnbindBackward0>), 'Execute Error': tensor(0.0223, device='cuda:0', grad_fn=<SubBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many zebras are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
question: ['How many zebras 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']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
question: ['How many 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']] |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
tensor([9.0915e-01, 9.0018e-02, 7.6229e-05, 7.9413e-05, 1.2794e-04, 3.2205e-04, |
1.5452e-04, 6.7771e-05], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([9.0915e-01, 9.0018e-02, 7.6229e-05, 7.9413e-05, 1.2794e-04, 3.2205e-04, |
1.5452e-04, 6.7771e-05], device='cuda:1', grad_fn=<SelectBackward0>) |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(0.0900, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0.9092, device='cuda:1', grad_fn=<DivBackward0>), 'Execute Error': tensor(0.0008, device='cuda:1', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 |
tensor([8.9755e-01, 1.2301e-02, 8.8873e-02, 3.2378e-04, 6.1256e-05, 1.6077e-04, |
1.2779e-05, 7.2216e-04], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.