def set_input_space(self, space):

        self.input_space = space

        if isinstance(space, VectorSpace):
            self.requires_reformat = False
            self.input_dim = space.dim
        else:
            self.requires_reformat = True
            self.input_dim = space.get_total_dimension()
            self.desired_space = VectorSpace(self.input_dim)

        self.output_space = VectorSpace(self.dim)

        rng = self.dbm.rng
        if self.irange is not None:
            assert self.sparse_init is None
            W = rng.uniform(-self.irange, self.irange,
                            (self.input_dim, self.dim)) * \
                (rng.uniform(0., 1., (self.input_dim, self.dim))
                    < self.include_prob)
        else:
            assert self.sparse_init is not None
            W = np.zeros((self.input_dim, self.dim))
            W *= self.sparse_stdev

        W = sharedX(W)
        W.name = self.layer_name + '_W'

        self.transformer = MatrixMul(W)

        W, = self.transformer.get_params()
        assert W.name is not None
Returns a dictionary of files and folders for a given reference and path.
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/models/dbm/ising.py/IsingHidden.set_input_space--crossover with--dataset/ETHPy150Open ros-infrastructure/bloom/bloom/git.py/ls_tree