Module Expr Str ImportFrom alias ImportFrom alias ImportFrom alias ImportFrom alias Import alias identifier ImportFrom alias Import alias FunctionDef arguments args defaults body Assign NameStore Call AttributeLoad NameLoad attr Str Expr Call NameLoad Str Assign NameStore Call NameLoad keyword Str Expr Call NameLoad Str Assign NameStore BinOpAdd NameLoad Str Expr Call AttributeLoad NameLoad attr NameLoad Assign NameStore Call NameLoad BinOpAdd NameLoad Str Str Expr Call AttributeLoad NameLoad attr Call AttributeLoad NameLoad attr Str Expr Call AttributeLoad NameLoad attr Expr Call NameLoad Str Assign NameStore Call AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr keyword NameLoad keyword NameLoad Expr Call NameLoad Str Expr Call AttributeLoad NameLoad attr BinOpAdd NameLoad Str Expr Call AttributeLoad NameLoad attr BinOpAdd NameLoad Str NameLoad Expr Call NameLoad Str Assign NameStore Call NameLoad keyword Str Expr Call NameLoad Str Expr Call AttributeLoad NameLoad attr keyword NameLoad keyword NameLoad Expr Call NameLoad Str Expr Call AttributeLoad NameLoad attr BinOpAdd NameLoad Str Expr Call AttributeLoad NameLoad attr BinOpAdd NameLoad Str NameLoad Expr Call AttributeLoad NameLoad attr BinOpAdd NameLoad Str NameLoad decorator_list If CompareEq NameLoad Str body Expr Call NameLoad
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This script makes a dataset of 32x32 approximately whitened CIFAR-10 images.

 __future__ print_function pylearn2.utils serial pylearn2.datasets preprocessing pylearn2.utils string_utils N/A numpy np pylearn2.datasets.cifar10 CIFAR10 N/A textwrap main N/A N/A N/A N/A N/A data_dir N/A N/A string_utils preprocess ${PYLEARN2_DATA_PATH}/cifar10 N/A N/A print Loading CIFAR-10 train dataset... N/A train N/A CIFAR10 which_set train N/A N/A print Preparing output directory... N/A output_dir N/A data_dir /pylearn2_whitened N/A N/A N/A serial mkdir output_dir N/A README N/A open N/A output_dir /README w N/A N/A N/A README write N/A N/A textwrap dedent 
    The .pkl files in this directory may be opened in python using
    cPickle, pickle, or pylearn2.serial.load.

    train.pkl, and test.pkl each contain
    a pylearn2 Dataset object defining a labeled
    dataset of a 32x32 approximately whitened version of the STL-10
    dataset. train.pkl contains labeled train examples. test.pkl
    contains labeled test examples.

    preprocessor.pkl contains a pylearn2 ZCA object that was used
    to approximately whiten the images. You may want to use this
    object later to preprocess other images.

    They were created with the pylearn2 script make_cifar10_whitened.py.

    All other files in this directory, including this README, were
    created by the same script and are necessary for the other files
    to function correctly.
     N/A N/A N/A README close N/A N/A print Learning the preprocessor and preprocessing           the unsupervised train data... N/A preprocessor N/A N/A preprocessing ZCA N/A N/A N/A train apply_preprocessor preprocessor preprocessor can_fit True N/A N/A print Saving the unsupervised data N/A N/A N/A train use_design_loc N/A output_dir /train.npy N/A N/A N/A serial save N/A output_dir /train.pkl train N/A N/A print Loading the test data N/A test N/A CIFAR10 which_set test N/A N/A print Preprocessing the test data N/A N/A N/A test apply_preprocessor preprocessor preprocessor can_fit False N/A N/A print Saving the test data N/A N/A N/A test use_design_loc N/A output_dir /test.npy N/A N/A N/A serial save N/A output_dir /test.pkl test N/A N/A N/A serial save N/A output_dir /preprocessor.pkl preprocessor N/A N/A N/A __name__ __main__ N/A N/A N/A main