Method append

machine_learning/automatic_differentiation.py:221–245

Adds Operation object to the related Variable objects for creating computational graph for calculating gradients. Args: op_type: Operation type params: Input parameters to the operation output: Output variable of the operation

(
        self,
        op_type: OpType,
        params: list[Variable],
        output: Variable,
        other_params: dict | None = None,
    )

        self.enabled = False

    def append(
        self,
        op_type: OpType,
        params: list[Variable],
        output: Variable,
        other_params: dict | None = None,
    ) -> None:
        """
        Adds Operation object to the related Variable objects for
        creating computational graph for calculating gradients.

        Args:
            op_type: Operation type
            params: Input parameters to the operation
            output: Output variable of the operation
        """
        operation = Operation(op_type, other_params=other_params)
        param_nodes = []
        for param in params:
            param.add_param_to(operation)
            param_nodes.append(param)
        output.add_result_of(operation)

        operation.add_params(param_nodes)
        operation.add_output(output)

    def gradient(self, target: Variable, source: Variable) -> np.ndarray | None:
        """