Comments (5)
It seems that tensor2tensor's problem.dataset() has changed and now require the second argument data_dir
not to be left empty.
I could solve the problem by changing demogen/data_util.py
as follows:
def input_data():
"""Input function to be returned."""
prob = problems.problem(problem_name)
data_dir = '<<<MY_HOME_DIRECTORY>>>/t2t_data/';
if data == 'image_cifar100':
dataset = prob.dataset(mode, data_dir, preprocess=augmented)
if not augmented: dataset = dataset.map(map_func=standardization)
else:
dataset = prob.dataset(mode, data_dir)
dataset = dataset.map(map_func=standardization)
and I have previously downloaded the data into this directory using:
t2t-datagen --generate_data --data_dir=~/t2t_data --problem=image_cifar100
t2t-datagen --generate_data --data_dir=~/t2t_data --problem=image_cifar10
from google-research.
Same for me!
Perhaps this is a setup issue of tensorflow-datasets? I didn't configure it to download CIFAR, etc.
from google-research.
Thank you for working this out. I am working on potentially easier way to get the dataset for external users.
from google-research.
Thanks, @yidinggiang! But are you sure the data split into training/validation/test set is determenistic?
That is, that the CIFAR10/100 training set I got is the same as the one used to train the models?
from google-research.
CIFAR10 and 100 have fixed training and test sets, so I don't see any problems. (There have been some changes to the data pipeline, please pull to get them)
from google-research.
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from google-research.