theano/compile/builders.py
def connection_pattern(self, node):
        """
        Return connection pattern of subfgraph defined by inputs and outputs.

        """
        if self._connection_pattern is not None:
            return self._connection_pattern

        inp_len = len(self.local_inputs)
        out_len = len(self.local_outputs)
        cpmat_self = io_connection_pattern(
            self.local_inputs, self.local_outputs)

        lop_op = self.get_lop_op()
        cpmat_grad = io_connection_pattern(
            lop_op.local_inputs[inp_len:],
            lop_op.local_outputs)

        # cpmat_self |= cpmat_grad.T
        # cpmat_self &= out_is_disconnected
        for i, t in enumerate(self._lop_op_stypes_l):
            if t is not None:
                if isinstance(t.type, DisconnectedType):
                    for o in range(out_len):
                        cpmat_self[i][o] = False
            for o in range(out_len):
                cpmat_self[i][o] |= cpmat_grad[o][i]

        # TODO in case DisconnectedType is implemented for R_op,
        # self._rop_op_stypes_l self._rop_op should considered for
        # connection_pattern

        return list(map(list, cpmat_self))

        Return connection pattern of subfgraph defined by inputs and outputs.

        
Return connection pattern of subfgraph defined by inputs and outputs.
Return connection pattern of subfgraph defined by inputs and outputs .
def connection_pattern(self, node):
        if self._connection_pattern is not None:
            return self._connection_pattern
        inp_len = len(self.local_inputs)
        out_len = len(self.local_outputs)
        cpmat_self = io_connection_pattern(
            self.local_inputs, self.local_outputs)
        lop_op = self.get_lop_op()
        cpmat_grad = io_connection_pattern(
            lop_op.local_inputs[inp_len:],
            lop_op.local_outputs)
        for i, t in enumerate(self._lop_op_stypes_l):
            if t is not None:
                if isinstance(t.type, DisconnectedType):
                    for o in range(out_len):
                        cpmat_self[i][o] = False
            for o in range(out_len):
                cpmat_self[i][o] |= cpmat_grad[o][i]
        return list(map(list, cpmat_self))
def connection_pattern ( self , node ) : if self . _connection_pattern is not None : return self . _connection_pattern inp_len = len ( self . local_inputs ) out_len = len ( self . local_outputs ) cpmat_self = io_connection_pattern ( self . local_inputs , self . local_outputs ) lop_op = self . get_lop_op ( ) cpmat_grad = io_connection_pattern ( lop_op . local_inputs [ inp_len : ] , lop_op . local_outputs ) for i , t in enumerate ( self . _lop_op_stypes_l ) : if t is not None : if isinstance ( t . type , DisconnectedType ) : for o in range ( out_len ) : cpmat_self [ i ] [ o ] = False for o in range ( out_len ) : cpmat_self [ i ] [ o ] |= cpmat_grad [ o ] [ i ] return list ( map ( list , cpmat_self ) )
Return connection pattern of subfgraph defined by inputs and outputs.
Return connection pattern of subfgraph defined by inputs and outputs .
"""
        Return connection pattern of subfgraph defined by inputs and outputs.

        """ # cpmat_self |= cpmat_grad.T # cpmat_self &= out_is_disconnected # TODO in case DisconnectedType is implemented for R_op, # self._rop_op_stypes_l self._rop_op should considered for # connection_pattern
self
node