New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Make all tensorflow datasets available from a single class. #20

Open

SamTov opened this issue Apr 21, 2022 · 0 comments

Member

SamTov commented Apr 21, 2022

Currently we have an MNIST generator and a CIFAR10 data generator. They are called the same way through:

self.ds_train, self.ds_test = tfds.as_numpy(
            tfds.load(
                'cifar10:3.*.*',
                split=['train[:%d]' % 500, 'test[:%d]' % 500],
                batch_size=-1
            )
        )
        self.data_pool = self.ds_train['image'].astype(float)

We could in this case support all tensorflow datasets and add a parent class for this.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment