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src/p/y/pylearn2-HEAD/pylearn2/models/dbm/layer.py   pylearn2(Download)
        if self.center:
            p_ofs, h_ofs = self.init_mf_state()
            self.p_offset = sharedX(self.output_space.get_origin(), 'p_offset')
            self.h_offset = sharedX(self.h_space.get_origin(), 'h_offset')
            f = function([], updates={self.p_offset: p_ofs[0,:,:,:], self.h_offset: h_ofs[0,:,:,:]})
        if self.center:
            p_ofs, h_ofs = self.init_mf_state()
            self.p_offset = sharedX(self.output_space.get_origin(), 'p_offset')
            self.h_offset = sharedX(self.h_space.get_origin(), 'h_offset')
            f = function([], updates={self.p_offset: p_ofs[:,:,:,0], self.h_offset: h_ofs[:,:,:,0]})

src/p/y/pylearn2-HEAD/pylearn2/models/mlp.py   pylearn2(Download)
                             self.init_bias)
        else:
            self.b = sharedX(self.detector_space.get_origin() + self.init_bias)
 
        self.b.name = self.layer_name + '_b'

src/p/y/pylearn2-HEAD/pylearn2/models/maxout.py   pylearn2(Download)
                             self.init_bias)
        else:
            self.b = sharedX(self.detector_space.get_origin() + self.init_bias)
        self.b.name = 'b'