def _create_rates(self, dist='uniform', size=None, eps=1e-4):
        '''Create a rate parameter (usually for a recurrent network layer).

        Parameters
        ----------
        dist : {'uniform', 'log'}, optional
            Distribution of rate values. Defaults to ``'uniform'``.
        size : int, optional
            Number of rates to create. Defaults to ``self.output_size``.
        eps : float, optional
            A "buffer" preventing rate values from getting too close to 0 or 1.
            Defaults to 1e-4.

        Returns
        -------
        rates : theano shared or None
            A vector of rate parameters for certain types of recurrent layers.
        '''
        if size is None:
            size = self.output_size
        if dist == 'uniform':
            z = np.random.uniform(eps, 1 - eps, size=size).astype(util.FLOAT)
            return theano.shared(z, name=self._fmt('rate'))
        if dist == 'log':
            z = np.random.uniform(-6, -eps, size=size).astype(util.FLOAT)
            return theano.shared(np.exp(z), name=self._fmt('rate'))
        return None
def _create_rates(self, dist='uniform', size=None, eps=1e-4):
        '''Create a rate parameter (usually for a recurrent network layer).

        Parameters
        ----------
        dist : {'uniform', 'log'}, optional
            Distribution of rate values. Defaults to ``'uniform'``.
        size : int, optional
            Number of rates to create. Defaults to ``self.output_size``.
        eps : float, optional
            A "buffer" preventing rate values from getting too close to 0 or 1.
            Defaults to 1e-4.

        Returns
        -------
        rates : theano shared or None
            A vector of rate parameters for certain types of recurrent layers.
        '''
        if size is None:
            size = self.output_size
        if dist == 'uniform':
            z = np.random.uniform(eps, 1 - eps, size=size).astype(util.FLOAT)
            return theano.shared(z, name=self._fmt('rate'))
        if dist == 'log':
            z = np.random.uniform(-6, -eps, size=size).astype(util.FLOAT)
            return theano.shared(np.exp(z), name=self._fmt('rate'))
        return None
def _create_rates ( self , dist = 'uniform' , size = None , eps = 1e-4 ) : if size is None : size = self . output_size if dist == 'uniform' : z = np . random . uniform ( eps , 1 - eps , size = size ) . astype ( util . FLOAT ) return theano . shared ( z , name = self . _fmt ( 'rate' ) ) if dist == 'log' : z = np . random . uniform ( - 6 , - eps , size = size ) . astype ( util . FLOAT ) return theano . shared ( np . exp ( z ) , name = self . _fmt ( 'rate' ) ) return None
Create a rate parameter (usually for a recurrent network layer).

        Parameters
        ----------
        dist : {'uniform', 'log'}, optional
            Distribution of rate values. Defaults to ``'uniform'``.
        size : int, optional
            Number of rates to create. Defaults to ``self.output_size``.
        eps : float, optional
            A "buffer" preventing rate values from getting too close to 0 or 1.
            Defaults to 1e-4.

        Returns
        -------
        rates : theano shared or None
            A vector of rate parameters for certain types of recurrent layers.
Create a rate parameter ( usually for a recurrent network layer ) .