o QeÛ ã@s„dZddlmZddlmZddlmZddlmZddlmZddlmZddlmZdd lm Z dd lm Z dd lm Z gZ d S) a· At training and testing time, PaddlePaddle programs need to read data. To ease the users' work to write data reading code, we define that - A *reader* is a function that reads data (from file, network, random number generator, etc) and yields data items. - A *reader creator* is a function that returns a reader function. - A *reader decorator* is a function, which accepts one or more readers, and returns a reader. - A *batch reader* is a function that reads data (from *reader*, file, network, random number generator, etc) and yields a batch of data items. ##################### Data Reader Interface ##################### Indeed, *data reader* doesn't have to be a function that reads and yields data items. It can be any function with no parameter that creates a iterable (anything can be used in :code:`for x in iterable`)\: .. code-block:: python iterable = data_reader() Element produced from the iterable should be a **single** entry of data, **not** a mini batch. That entry of data could be a single item, or a tuple of items. Item should be of supported type (e.g., numpy array or list/tuple of float or int). An example implementation for single item data reader creator: .. code-block:: python def reader_creator_random_image(width, height): def reader(): while True: yield numpy.random.uniform(-1, 1, size=width*height) return reader An example implementation for multiple item data reader creator: .. code-block:: python def reader_creator_random_image_and_label(width, height, label): def reader(): while True: yield numpy.random.uniform(-1, 1, size=width*height), label return reader é)Ú map_readers)Úshuffle)Ú xmap_readers)Úfirstn)Úbuffered)Úcompose)Úcache)ÚComposeNotAligned)Úchain)Úmultiprocess_readerN) Ú__doc__Zpaddle.reader.decoratorrrrrrrrr r r Ú__all__©rrúFD:\Projects\ConvertPro\env\Lib\site-packages\paddle/reader/__init__.pyÚs 4