Method get_corrupted_input

code/dA.py:196–220

This function keeps ``1-corruption_level`` entries of the inputs the same and zero-out randomly selected subset of size ``corruption_level`` Note : first argument of theano.rng.binomial is the shape(size) of random numbers that it should produce second a

(self, input, corruption_level)

        self.params = [self.W, self.b, self.b_prime]

    def get_corrupted_input(self, input, corruption_level):
        """This function keeps ``1-corruption_level`` entries of the inputs the
        same and zero-out randomly selected subset of size ``corruption_level``
        Note : first argument of theano.rng.binomial is the shape(size) of
               random numbers that it should produce
               second argument is the number of trials
               third argument is the probability of success of any trial

                this will produce an array of 0s and 1s where 1 has a
                probability of 1 - ``corruption_level`` and 0 with
                ``corruption_level``

                The binomial function return int64 data type by
                default.  int64 multiplicated by the input
                type(floatX) always return float64.  To keep all data
                in floatX when floatX is float32, we set the dtype of
                the binomial to floatX. As in our case the value of
                the binomial is always 0 or 1, this don't change the
                result. This is needed to allow the gpu to work
                correctly as it only support float32 for now.

        """
        return self.theano_rng.binomial(size=input.shape, n=1,
                                        p=1 - corruption_level,
                                        dtype=theano.config.floatX) * input

    def get_hidden_values(self, input):
        """ Computes the values of the hidden layer """