torch_concepts.data.datasets.mnist.ColorMNISTDataset¶

class ColorMNISTDataset(root: str, train: bool = False, transform=None, target_transform=None, download: bool = False, random: bool = True)[source]¶

The color MNIST dataset is a modified version of the MNIST dataset where each digit is colored either red or green. The concept labels are the digit and the color of the digit. The task is to predict whether the digit is even or odd.

root¶: The root directory where the dataset is stored.

train¶: Whether to load the training or test split. Default is False.

transform¶: The transformations to apply to the images. Default is None.

target_transform¶: The transformations to apply to the target labels. Default is None.

download¶: Whether to download the dataset if it does not exist. Default is False.

random¶: Whether to colorize the digits randomly. Default is True.

__init__(root: str, train: bool = False, transform=None, target_transform=None, download: bool = False, random: bool = True)[source]¶

Methods

`__init__`(root[, train, transform, ...])
`download`()	Download the MNIST data if it doesn't exist already.
`extra_repr`()

Attributes

`class_to_idx`
`classes`
`mirrors`
`processed_folder`
`raw_folder`
`resources`
`test_data`
`test_file`
`test_labels`
`train_data`
`train_labels`
`training_file`