SyntheticPILDataset

class composer.datasets.SyntheticPILDataset(*, total_dataset_size, data_shape=(64, 64, 3), num_unique_samples_to_create=100, data_type=SyntheticDataType.GAUSSIAN, label_type=SyntheticDataLabelType.CLASSIFICATION_INT, num_classes=None, label_shape=None, transform=None)

Similar to SyntheticBatchPairDataset, but yields samples of type Image and supports dataset transformations.

Parameters

• total_dataset_size (int) – The total size of the dataset to emulate.

• data_shape (List[int]) – Shape of the tensor for input samples.

• num_unique_samples_to_create (int) – The number of unique samples to allocate memory for.

• data_type (str or SyntheticDataType, optional) – Default: SyntheticDataType.GAUSSIAN.

• label_type (str or SyntheticDataLabelType, optional) – create. Default: SyntheticDataLabelType.CLASSIFICATION_INT.

• num_classes (int, optional) – Number of classes to use. Required if SyntheticDataLabelType is CLASSIFICATION_INT or CLASSIFICATION_ONE_HOT. Default: None.

• label_shape (List[int], optional) – Shape of the tensor for each sample label. Default: None.

• transform (Callable, optional) – Transform(s) to apply to data. Default: None.