Module Expr Str Import alias Import alias Import alias ImportFrom alias alias ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam NameParam defaults Num NameLoad body Assign AttributeStore NameLoad attr Call NameLoad NameLoad Assign AttributeStore NameLoad attr NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Assign NameStore Call AttributeLoad NameLoad attr BinOpDiv AttributeLoad NameLoad attr SubscriptLoad NameLoad Index Num If AttributeLoad NameLoad attr body Assign NameStore Call AttributeLoad NameLoad attr Num NameLoad keyword NameLoad orelse Assign NameStore Call AttributeLoad NameLoad attr UnaryOpUSub NameLoad NameLoad keyword NameLoad Return Call AttributeLoad NameLoad attr AttributeLoad AttributeLoad NameLoad attr attr decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam defaults vararg kwarg body Expr Call AttributeLoad Call NameLoad NameLoad NameLoad attr NameLoad NameLoad Assign AttributeStore NameLoad attr Call NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body If CompareEq Call NameLoad NameLoad Num body Return Call AttributeLoad Call NameLoad NameLoad NameLoad attr NameLoad NameLoad Assign NameStore SubscriptLoad NameLoad Index Num Assign NameStore BinOpFloorDiv SubscriptLoad NameLoad Index Num NameLoad If BoolOpAnd CompareGt NameLoad Num CompareEq Call NameLoad NameLoad Num CompareEq SubscriptLoad NameLoad Index Num BinOpMult NameLoad NameLoad body Assign NameStore ListComp Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad TupleLoad NameLoad NameLoad comprehension NameStore Call NameLoad NameLoad Return Call AttributeLoad NameLoad attr NameLoad keyword Num Return Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad NameLoad decorator_list decorator_list
N/A N/A 
This module contains classes that should be merged at some point inside blocks
 N/A copy N/A numpy N/A theano blocks.initialization NdarrayInitialization Orthogonal GlorotBengio N/A NdarrayInitialization N/A N/A Initialize parameters with Glorot-Bengio method.

    Use the following gaussian parameters: mean=0 and std=sqrt(scale/Nin).
    In some circles this method is also called Xavier weight initialization.


    Parameters
    ----------
    scale : float
        1 for linear/tanh/sigmoid. 2 for RELU
    normal : bool
        Perform sampling from normal distribution. By defaut use uniform.

    Notes
    -----
    For more information, see [GLOROT]_.

    .. [GLOROT] Glorot et al. *Understanding the difficulty of training
      deep feedforward neural networks*, International conference on
      artificial intelligence and statistics, 249-256
      http://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf
     __init__ N/A N/A self scale normal N/A 1 False N/A N/A N/A self _scale N/A float scale N/A N/A self _normal normal N/A generate N/A N/A self rng shape N/A N/A N/A w N/A N/A numpy sqrt N/A N/A self _scale N/A shape N/A -1 N/A N/A self _normal N/A N/A m N/A N/A rng normal 0.0 w size shape N/A N/A m N/A N/A rng uniform N/A w w size shape N/A N/A N/A m astype N/A N/A theano config floatX N/A N/A OrthogonalGlorot N/A GlorotBengio N/A N/A Initialize a random orthogonal matrix.


     __init__ N/A N/A self N/A args kwargs N/A N/A N/A N/A N/A super OrthogonalGlorot self __init__ args kwargs N/A N/A self orth N/A Orthogonal N/A generate N/A N/A self rng shape N/A N/A N/A N/A N/A len shape 1 N/A N/A N/A N/A N/A super OrthogonalGlorot self generate rng shape N/A N N/A shape N/A 0 N/A M N/A N/A shape N/A 1 N N/A N/A N/A M 1 N/A N/A len shape 2 N/A N/A shape N/A 1 N/A M N N/A N/A res N/A N/A N/A N/A self orth generate rng N/A N N N/A i N/A range M N/A N/A N/A numpy concatenate res axis -1 N/A N/A N/A N/A self orth generate rng shape N/A N/A