TensorFlow 1 version View source on GitHub

Iterator yielding data from a Numpy array.

Inherits From: Iterator

x Numpy array of input data or tuple. If tuple, the second elements is either another numpy array or a list of numpy arrays, each of which gets passed through as an output without any modifications.
y Numpy array of targets data.
image_data_generator Instance of ImageDataGenerator to use for random transformations and normalization.
batch_size Integer, size of a batch.
shuffle Boolean, whether to shuffle the data between epochs.
sample_weight Numpy array of sample weights.
seed Random seed for data shuffling.
data_format String, one of channels_first, channels_last.
save_to_dir Optional directory where to save the pictures being yielded, in a viewable format. This is useful for visualizing the random transformations being applied, for debugging purposes.
save_prefix String prefix to use for saving sample images (if save_to_dir is set).
save_format Format to use for saving sample images (if save_to_dir is set).
subset Subset of data ("training" or "validation") if validation_split is set in ImageDataGenerator.
dtype Dtype to use for the generated arrays.



For python 2.x.


The next batch.


Method called at the end of every epoch.



Gets batch at position index.

index position of the batch in the Sequence.

A batch


Create a generator that iterate over the Sequence.


Number of batch in the Sequence.

The number of batches in the Sequence.

Class Variables

  • white_list_formats