CIFAR-100 Data Set

class deepobs.tensorflow.datasets.cifar100.cifar100(batch_size, data_augmentation=True, train_eval_size=10000)[source]

DeepOBS data set class for the CIFAR-100 data set.

  • batch_size (int) -- The mini-batch size to use. Note that, if batch_size is not a divider of the dataset size (50 000 for train, 10 000 for test) the remainder is dropped in each epoch (after shuffling).
  • data_augmentation (bool) -- If True some data augmentation operations (random crop window, horizontal flipping, lighting augmentation) are applied to the training data (but not the test data).
  • train_eval_size (int) -- Size of the train eval data set. Defaults to 10 000 the size of the test set.

A tuple (x, y) of tensors, yielding batches of CIFAR-100 images (x with shape (batch_size, 32, 32, 3)) and corresponding one-hot label vectors (y with shape (batch_size, 100)). Executing these tensors raises a tf.errors.OutOfRangeError after one epoch.


A tensorflow operation initializing the dataset for the training phase.


A tensorflow operation initializing the testproblem for evaluating on training data.


A tensorflow operation initializing the testproblem for evaluating on test data.


A string-value tf.Variable that is set to train, train_eval or test, depending on the current phase. This can be used by testproblems to adapt their behavior to this phase.