PyTorch HDF5 Dataset



A HDF5 dataset processor. Loads data from HDF5 files. :param dict params: dict containing training input parameters for creating dataset. Expects the following fields: - "data_dir" (str or list of str): Path to dataset HDF5 files - "batch_size" (int): Batch size. - "shuffle" (bool): Flag to enable data shuffling. - "shuffle_seed" (int): Shuffle seed. - "num_workers" (int): How many subprocesses to use for data loading. - "drop_last" (bool): If True and the dataset size is not divisible by the batch size, the last incomplete batch will be dropped. - "use_vsl" (bool): Flag to enable variable sequence length training. It requires the dataset to have two extra features: the attention_span of keys and the position_ids of tokens. Defaults to False.


This custom dataloader class specifies the 'state_dict', 'aggregate_state_dict', 'load_state_dict' and 'deaggregate_state_dict' methods.