:py:mod:`neural_compressor.experimental.data.datasets` ====================================================== .. py:module:: neural_compressor.experimental.data.datasets .. autoapi-nested-parse:: Built-in datasets class for multiple framework backends. Submodules ---------- .. toctree:: :titlesonly: :maxdepth: 1 bert_dataset/index.rst coco_dataset/index.rst dataset/index.rst dummy_dataset/index.rst dummy_dataset_v2/index.rst imagenet_dataset/index.rst style_transfer_dataset/index.rst Package Contents ---------------- Classes ~~~~~~~ .. autoapisummary:: neural_compressor.experimental.data.datasets.Datasets neural_compressor.experimental.data.datasets.Dataset neural_compressor.experimental.data.datasets.IterableDataset Functions ~~~~~~~~~ .. autoapisummary:: neural_compressor.experimental.data.datasets.dataset_registry .. py:class:: Datasets(framework) Bases: :py:obj:`object` A base class for all framework datasets. :param framework: framework name, like:"tensorflow", "tensorflow_itex", "mxnet", "onnxrt_qdq", "onnxrt_qlinearops", "onnxrt_integerops", "pytorch", "pytorch_ipex", "pytorch_fx", "onnxrt_qoperator". :type framework: str .. py:class:: Dataset Bases: :py:obj:`object` The base class of dataset. Subclass datasets should overwrite two methods: `__getitem__` for indexing to data sample and `__len__`for the size of the dataset .. py:class:: IterableDataset Bases: :py:obj:`object` An iterable Dataset. Subclass iterable dataset should also implement a method: `__iter__` for interating over the samples of the dataset. .. py:function:: dataset_registry(dataset_type, framework, dataset_format='') Register dataset subclasses. :param cls: The class of register. :type cls: class :param dataset_type: The dataset registration name :type dataset_type: str :param framework: support 3 framework including 'tensorflow', 'pytorch', 'mxnet' :type framework: str :param data_format: The format dataset saved, eg 'raw_image', 'tfrecord' :type data_format: str :returns: The class of register. :rtype: cls