feedforward.py 文件源码

def _setup_vars(self, sparse_input):
        '''Setup Theano variables for our network.

        Parameters
        ----------
        sparse_input : bool
            If True, create an input variable that can hold a sparse matrix.
            Defaults to False, which assumes all arrays are dense.

        Returns
        -------
        vars : list of theano variables
            A list of the variables that this network requires as inputs.
        '''
        # x represents our network's input.
        self.x = TT.matrix('x')
        if sparse_input:
            self.x = SS.csr_matrix('x')

        # for a classifier, this specifies the correct labels for a given input.
        self.labels = TT.ivector('labels')

        # and the weights are reshaped to be just a vector.
        self.weights = TT.vector('weights')

        if self.weighted:
            return [self.x, self.labels, self.weights]
        return [self.x, self.labels]