Mercurial > pylearn
view datasets/MNIST.py @ 470:bd937e845bbb
new stuff: algorithms/logistic_regression, datasets/MNIST
author | James Bergstra <bergstrj@iro.umontreal.ca> |
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date | Wed, 22 Oct 2008 15:56:53 -0400 |
parents | |
children | 45b3eb429c15 |
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""" Various routines to load/access MNIST data. """ from __future__ import absolute_import import numpy from ..amat import AMat default_path = '/u/bergstrj/pub/data/mnist.amat' """the location of a file containing mnist data in .amat format""" def head(n=10, path=None): """Load the first MNIST examples. Returns two matrices: x, y. x has N rows of 784 columns. Each row of x represents the 28x28 grey-scale pixels in raster order. y is a vector of N integers. Each element y[i] is the label of the i'th row of x. """ path = path if path is not None else default_path dat = AMat(path=path, head=n) return dat.input, numpy.asarray(dat.target, dtype='int64').reshape(dat.target.shape[0]) def all(path=None): return head(n=None, path=path)