mxnet.io¶

Data iterators for common data formats and utility functions.

Iterators¶

`NDArrayIter`(data[, label, batch_size, …])	Returns an iterator for `mx.nd.NDArray`, `numpy.ndarray`, `h5py.Dataset` `mx.nd.sparse.CSRNDArray` or `scipy.sparse.csr_matrix`.
`CSVIter`(args, *kwargs)	b”Returns the CSV file iterator.nnIn this function, the data_shape parameter is used to set the shape of each line of the input data.nIf a row in an input file is 1,2,3,4,5,6` and data_shape is (3,2), that rownwill be reshaped, yielding the array [[1,2],[3,4],[5,6]] of shape (3,2).nnBy default, the CSVIter has round_batch parameter set to `True`.
`LibSVMIter`(args, *kwargs)	b”Returns the LibSVM iterator which returns data with csrnstorage type.
`MNISTIter`(args, *kwargs)	b’Iterating on the MNIST dataset.nnOne can download the dataset from http://yann.lecun.com/exdb/mnist/nnnnDefined in src/io/iter_mnist.cc:L265’
`ImageDetRecordIter`(args, *kwargs)	b’Create iterator for image detection dataset packed in recordio.’
`ImageRecordIter`(args, *kwargs)	b’Iterates on image RecordIO filesnnReads batches of images from .rec RecordIO files.
`ImageRecordIter_v1`(args, *kwargs)	b’Iterating on image RecordIO filesnn..
`ImageRecordUInt8Iter`(args, *kwargs)	b’Iterating on image RecordIO filesnnThis iterator is identical to `ImageRecordIter` except for using `uint8` asnthe data type instead of `float`.nnnnDefined in src/io/iter_image_recordio_2.cc:L777’
`ImageRecordUInt8Iter_v1`(args, *kwargs)	b’Iterating on image RecordIO filesnn..

`DataBatch`(data[, label, pad, index, …])	A data batch.
`DataDesc`	DataDesc is used to store name, shape, type and layout information of the data or the label.
`DataIter`([batch_size])	The base class for an MXNet data iterator.
`MXDataIter`(handle[, data_name, label_name])	A python wrapper a C++ data iterator.
`PrefetchingIter`(iters[, rename_data, …])	Performs pre-fetch for other data iterators.
`ResizeIter`(data_iter, size[, reset_internal])	Resize a data iterator to a given number of batches.