cerebras.modelzoo.data.nlp.gpt.DummyIterableDataProcessor.DummyTinyIterableDataProcessor#
- class cerebras.modelzoo.data.nlp.gpt.DummyIterableDataProcessor.DummyTinyIterableDataProcessor[source]#
Bases:
cerebras.modelzoo.data.common.GenericDataProcessor.GenericDataProcessorA Generic PyTorch Data Processor. :param dict params: dict containing training
input parameters for creating dataset.
Expects the following fields: - “batch_size” (int): Batch size. - “shuffle” (bool): Flag to enable data shuffling. - “shuffle_seed” (int): Shuffle seed. - “shuffle_buffer” (int): Size of shuffle buffer in samples. - “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.
“prefetch_factor” (int): Number of batches loaded in advance by each worker.
- “persistent_workers” (bool): If True, the data loader will not shutdown
the worker processes after a dataset has been consumed once.
Methods
Classmethod to create the dataloader object.
- create_dataloader()#
Classmethod to create the dataloader object.