Module Expr Str ImportFrom alias Import alias Import alias ImportFrom alias Assign NameStore NameLoad ImportFrom alias Assign AttributeStore AttributeLoad AttributeLoad NameLoad attr attr attr NameLoad If Num body Expr Call NameLoad Str Assign NameStore AttributeLoad AttributeLoad NameLoad attr attr orelse Import alias Assign NameStore AttributeLoad AttributeLoad AttributeLoad NameLoad attr attr attr ImportFrom alias ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam NameParam defaults Num body Assign NameStore Call NameLoad NameLoad keyword ListLoad Str Str Assign NameStore Call NameLoad Call AttributeLoad NameLoad attr BinOpPow Num Num Assign AttributeStore NameLoad attr Call NameLoad NameLoad Assign AttributeStore NameLoad attr NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Expr Str If Call NameLoad NameLoad AttributeLoad NameLoad attr body Return Call AttributeLoad NameLoad attr NameLoad orelse Return ListComp Call AttributeLoad NameLoad attr NameLoad comprehension NameStore NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Expr Str Raise Call NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Expr Str Raise Call NameLoad decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam defaults body Expr Str Return NameLoad decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam defaults body Expr Str Return BinOpMult Call AttributeLoad AttributeLoad NameLoad attr attr keyword AttributeLoad NameLoad attr keyword Num keyword BinOpSub Num AttributeLoad NameLoad attr keyword AttributeLoad AttributeLoad NameLoad attr attr NameLoad decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam defaults body Expr Str If CompareLt AttributeLoad NameLoad attr Num body Return NameLoad Assign NameStore Call AttributeLoad Call NameLoad NameLoad NameLoad attr NameLoad Return BinOpMult BinOpDiv Num BinOpSub Num AttributeLoad NameLoad attr NameLoad decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam NameParam defaults Num body Expr Call AttributeLoad Call NameLoad NameLoad NameLoad attr keyword NameLoad keyword NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Expr Str Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr keyword AttributeLoad NameLoad attr keyword Num keyword AttributeLoad NameLoad attr keyword AttributeLoad AttributeLoad NameLoad attr attr Return BinOpAdd NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Expr Str Assign NameStore Call NameLoad Num Call NameLoad AttributeLoad AttributeLoad NameLoad attr attr Assign NameStore BinOpDiv Call AttributeLoad NameLoad attr Call AttributeLoad NameLoad attr BinOpSub NameLoad NameLoad keyword NameLoad BinOpMult Num BinOpPow AttributeLoad NameLoad attr Num Assert CompareEq Call NameLoad AttributeLoad AttributeLoad NameLoad attr attr Num Return NameLoad decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam defaults body Expr Str Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr keyword AttributeLoad NameLoad attr keyword BinOpSub Num AttributeLoad NameLoad attr keyword AttributeLoad AttributeLoad NameLoad attr attr Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr keyword AttributeLoad NameLoad attr keyword Num keyword AttributeLoad AttributeLoad NameLoad attr attr Assign NameStore BinOpMult Call AttributeLoad NameLoad attr NameLoad Num NameLoad Return BinOpAdd BinOpMult NameLoad NameLoad NameLoad decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam defaults body Expr Str Assign NameStore SubscriptLoad AttributeLoad NameLoad attr Index Num Assign NameStore SubscriptLoad AttributeLoad NameLoad attr Index Num Assign NameStore Call AttributeLoad NameLoad attr Call AttributeLoad AttributeLoad NameLoad attr attr keyword TupleLoad NameLoad Num keyword BinOpSub Num AttributeLoad NameLoad attr keyword Str Num Assign NameStore Call AttributeLoad NameLoad attr BinOpDiv Num NameLoad NameLoad Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr keyword TupleLoad NameLoad keyword NameLoad Return BinOpAdd BinOpMult NameLoad NameLoad BinOpMult BinOpSub Num NameLoad NameLoad decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam defaults body Expr Str Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr keyword AttributeLoad NameLoad attr keyword Num keyword AttributeLoad NameLoad attr keyword AttributeLoad AttributeLoad NameLoad attr attr Return Call NameLoad BinOpAdd NameLoad NameLoad 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 Num NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Expr Str Return Call AttributeLoad AttributeLoad NameLoad attr attr keyword AttributeLoad NameLoad attr keyword NameLoad keyword 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 Num NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Expr Str Assign NameStore BinOpDiv NameLoad Call AttributeLoad NameLoad attr keyword Num keyword NameLoad Return Call AttributeLoad AttributeLoad NameLoad attr attr keyword NameLoad keyword AttributeLoad AttributeLoad NameLoad attr attr decorator_list decorator_list ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam defaults vararg body Assert CompareGtE Call NameLoad NameLoad Num Assign AttributeStore NameLoad attr NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Expr Str Assign NameStore NameLoad For NameStore Call NameLoad AttributeLoad NameLoad attr body Assign NameStore Call NameLoad NameLoad Return NameLoad decorator_list decorator_list FunctionDef arguments args NameParam defaults body Expr Str Assign NameStore SubscriptLoad Call NameLoad Index NameLoad If Call NameLoad NameLoad NameLoad body Return NameLoad orelse Raise Call NameLoad NameLoad decorator_list
N/A N/A 
Corruptor classes: classes that encapsulate the noise process for the DAE
training criterion.
 __future__ print_function N/A numpy N/A theano theano tensor N/A T tensor pylearn2.utils.rng make_np_rng N/A N/A N/A N/A theano config warn sum_div_dimshuffle_bug False N/A 0 N/A N/A N/A print WARNING: using SLOW rng N/A RandomStreams N/A N/A tensor shared_randomstreams RandomStreams N/A N/A theano.sandbox.rng_mrg N/A RandomStreams N/A N/A N/A theano sandbox rng_mrg MRG_RandomStreams pylearn2.expr.activations rescaled_softmax Corruptor N/A object N/A N/A 
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    Parameters
    ----------
    corruption_level : float
        Some measure of the amount of corruption to do. What this means
        will be implementation specific.
    rng : RandomState object or seed, optional
        NumPy random number generator object (or seed for creating one)
        used to initialize a `RandomStreams`.
     __init__ N/A N/A self corruption_level rng N/A 2001 N/A N/A rng N/A make_np_rng rng which_method N/A randn randint N/A seed N/A int N/A N/A rng randint N/A 2 30 N/A N/A self s_rng N/A RandomStreams seed N/A N/A self corruption_level corruption_level N/A __call__ N/A N/A self inputs N/A N/A N/A 
        (Symbolically) corrupt the inputs with a noise process.

        Parameters
        ----------
        inputs : tensor_like, or list of tensor_likes
            Theano symbolic(s) representing a (list of) (mini)batch of
            inputs to be corrupted, with the first dimension indexing
            training examples and the second indexing data dimensions.

        Returns
        -------
        corrupted : tensor_like, or list of tensor_likes
            Theano symbolic(s) representing the corresponding corrupted
            inputs.
         N/A N/A isinstance inputs N/A tensor Variable N/A N/A N/A N/A self _corrupt inputs N/A N/A N/A N/A N/A self _corrupt inp N/A inp inputs N/A _corrupt N/A N/A self x N/A N/A N/A 
        Corrupts a single tensor_like object.

        Parameters
        ----------
        x : tensor_like
            Theano symbolic representing a (mini)batch of inputs to be
            corrupted, with the first dimension indexing training
            examples and the second indexing data dimensions.

        Returns
        -------
        corrupted : tensor_like
            Theano symbolic representing the corresponding corrupted input.

        Notes
        -----
        This is the method that all subclasses should implement. The logic in
        Corruptor.__call__ handles mapping over multiple tensor_like inputs.
         N/A N/A NotImplementedError N/A corruption_free_energy N/A N/A self corrupted_X X N/A N/A N/A 
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         N/A N/A NotImplementedError N/A N/A DummyCorruptor N/A Corruptor N/A N/A 
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     __call__ N/A N/A self inputs N/A N/A N/A 
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         N/A inputs N/A N/A BinomialCorruptor N/A Corruptor N/A N/A 
    A binomial corruptor that sets inputs to 0 with probability
    0 < `corruption_level` < 1.
     _corrupt N/A N/A self x N/A N/A N/A 
        Corrupts a single tensor_like object.

        Parameters
        ----------
        x : tensor_like
            Theano symbolic representing a (mini)batch of inputs to be
            corrupted, with the first dimension indexing training
            examples and the second indexing data dimensions.

        Returns
        -------
        corrupted : tensor_like
            Theano symbolic representing the corresponding corrupted input.
         N/A N/A N/A N/A N/A self s_rng binomial size N/A x shape n 1 p N/A 1 N/A self corruption_level dtype N/A N/A theano config floatX x N/A N/A DropoutCorruptor N/A BinomialCorruptor N/A N/A 
    Sets inputs to 0 with probability of corruption_level and then
    divides by (1 - corruption_level) to keep expected activation
    constant.
     _corrupt N/A N/A self x N/A N/A N/A 
        Corrupts a single tensor_like object.

        Parameters
        ----------
        x : tensor_like
            Theano symbolic representing a (mini)batch of inputs to be
            corrupted, with the first dimension indexing training
            examples and the second indexing data dimensions.

        Returns
        -------
        corrupted : tensor_like
            Theano symbolic representing the corresponding corrupted input.
         N/A N/A N/A self corruption_level 1e-05 N/A N/A x N/A dropped N/A N/A N/A super DropoutCorruptor self _corrupt x N/A N/A N/A 1.0 N/A 1.0 N/A self corruption_level dropped N/A N/A GaussianCorruptor N/A Corruptor N/A N/A 
    A Gaussian corruptor transforms inputs by adding zero mean isotropic
    Gaussian noise.

    Parameters
    ----------
    stdev : WRITEME
    rng : WRITEME
     __init__ N/A N/A self stdev rng N/A 2001 N/A N/A N/A N/A N/A super GaussianCorruptor self __init__ corruption_level stdev rng rng N/A _corrupt N/A N/A self x N/A N/A N/A 
        Corrupts a single tensor_like object.

        Parameters
        ----------
        x : tensor_like
            Theano symbolic representing a (mini)batch of inputs to be
            corrupted, with the first dimension indexing training
            examples and the second indexing data dimensions.

        Returns
        -------
        corrupted : tensor_like
            Theano symbolic representing the corresponding corrupted input.
         N/A noise N/A N/A N/A self s_rng normal size N/A x shape avg 0.0 std N/A self corruption_level dtype N/A N/A theano config floatX N/A N/A noise x N/A corruption_free_energy N/A N/A self corrupted_X X N/A N/A N/A 
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         N/A axis N/A range 1 N/A len N/A N/A X type broadcastable N/A rval N/A N/A N/A T sum N/A N/A T sqr N/A corrupted_X X axis axis N/A 2.0 N/A N/A self corruption_level 2.0 N/A N/A N/A len N/A N/A rval type broadcastable 1 N/A rval N/A N/A SaltPepperCorruptor N/A Corruptor N/A N/A 
    Corrupts the input with salt and pepper noise.

    Sets some elements of the tensor to 0 or 1. Only really makes sense
    to use on binary valued matrices.
     _corrupt N/A N/A self x N/A N/A N/A 
        Corrupts a single tensor_like object.

        Parameters
        ----------
        x : tensor_like
            Theano symbolic representing a (mini)batch of inputs to be
            corrupted, with the first dimension indexing training
            examples and the second indexing data dimensions.

        Returns
        -------
        corrupted : tensor_like
            Theano symbolic representing the corresponding corrupted input.
         N/A a N/A N/A N/A self s_rng binomial size N/A x shape p N/A 1 N/A self corruption_level dtype N/A N/A theano config floatX N/A b N/A N/A N/A self s_rng binomial size N/A x shape p 0.5 dtype N/A N/A theano config floatX N/A c N/A N/A N/A T eq a 0 b N/A N/A N/A x a c N/A N/A OneHotCorruptor N/A Corruptor N/A N/A 
    Corrupts a one-hot vector by changing active element with some
    probability.
     _corrupt N/A N/A self x N/A N/A N/A 
        Corrupts a single tensor_like object.

        Parameters
        ----------
        x : tensor_like
            Theano symbolic representing a (mini)batch of inputs to be
            corrupted, with the first dimension indexing training
            examples and the second indexing data dimensions.

        Returns
        -------
        corrupted : tensor_like
            Theano symbolic representing the corresponding corrupted input.
         N/A num_examples N/A N/A x shape N/A 0 N/A num_classes N/A N/A x shape N/A 1 N/A keep_mask N/A N/A T addbroadcast N/A N/A N/A self s_rng binomial size N/A num_examples 1 p N/A 1 N/A self corruption_level dtype int8 1 N/A pvals N/A N/A T alloc N/A 1.0 num_classes num_classes N/A one_hot N/A N/A N/A self s_rng multinomial size N/A num_examples pvals pvals N/A N/A N/A keep_mask x N/A N/A 1 keep_mask one_hot N/A N/A SmoothOneHotCorruptor N/A Corruptor N/A N/A 
    Corrupts a one-hot vector in a way that preserves some information.

    This adds Gaussian noise to a vector and then computes the softmax.
     _corrupt N/A N/A self x N/A N/A N/A 
        Corrupts a single tensor_like object.

        Parameters
        ----------
        x : tensor_like
            Theano symbolic representing a (mini)batch of inputs to be
            corrupted, with the first dimension indexing training
            examples and the second indexing data dimensions.

        Returns
        -------
        corrupted : tensor_like
            Theano symbolic representing the corresponding corrupted input.
         N/A noise N/A N/A N/A self s_rng normal size N/A x shape avg 0.0 std N/A self corruption_level dtype N/A N/A theano config floatX N/A N/A rescaled_softmax N/A x noise N/A N/A BinomialSampler N/A Corruptor N/A N/A 
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     __init__ N/A N/A self N/A args kwargs N/A N/A N/A N/A N/A super BinomialSampler self __init__ 0 args kwargs N/A _corrupt N/A N/A self x N/A N/A N/A 
        Corrupts a single tensor_like object.

        Parameters
        ----------
        x : tensor_like
            Theano symbolic representing a (mini)batch of inputs to be
            corrupted, with the first dimension indexing training
            examples and the second indexing data dimensions.

        Returns
        -------
        corrupted : tensor_like
            Theano symbolic representing the corresponding corrupted input.
         N/A N/A N/A N/A self s_rng binomial size N/A x shape p x dtype N/A N/A theano config floatX N/A N/A MultinomialSampler N/A Corruptor N/A N/A 
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     __init__ N/A N/A self N/A args kwargs N/A N/A N/A N/A N/A super MultinomialSampler self __init__ 0 args kwargs N/A _corrupt N/A N/A self x N/A N/A N/A 
        Treats each row in matrix as a multinomial trial.

        Parameters
        ----------
        x : tensor_like
            x must be a matrix where all elements are non-negative
            (with at least one non-zero element)
        Returns
        -------
        y : tensor_like
            y will have the same shape as x. Each row in y will be a
            one hot vector, and can be viewed as the outcome of the
            multinomial trial defined by the probabilities of that row
            in x.
         N/A normalized N/A x N/A N/A x sum axis 1 keepdims True N/A N/A N/A N/A self s_rng multinomial pvals normalized dtype N/A N/A theano config floatX N/A N/A ComposedCorruptor N/A Corruptor N/A N/A 
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    Parameters
    ----------
    corruptors : list of Corruptor objects
        The corruptors are applied in reverse order. This matches the
        typical function application notation. Thus
        `ComposedCorruptor(a, b)._corrupt(X)` is the same as `a(b(X))`.

    Notes
    -----
    Does NOT call Corruptor.__init__, so does not contain all of the
    standard fields for Corruptors.
     __init__ N/A N/A self N/A corruptors N/A N/A N/A N/A len corruptors 1 N/A N/A self _corruptors corruptors N/A _corrupt N/A N/A self x N/A N/A N/A 
        Corrupts a single tensor_like object.

        Parameters
        ----------
        x : tensor_like
            Theano symbolic representing a (mini)batch of inputs to be
            corrupted, with the first dimension indexing training
            examples and the second indexing data dimensions.

        Returns
        -------
        corrupted : tensor_like
            Theano symbolic representing the corresponding corrupted input.
         N/A result x N/A c N/A reversed N/A self _corruptors N/A N/A result N/A c result N/A result N/A N/A get N/A N/A str N/A N/A N/A  Evaluate str into a corruptor object, if it exists  N/A obj N/A N/A globals N/A str N/A N/A issubclass obj Corruptor N/A N/A obj N/A N/A N/A NameError str N/A