Sum metric

@synalinks_export("synalinks.metrics.Sum")
class Sum(Metric):
    """Compute the (weighted) sum of the given values.

    For example, if `values` is `[1, 3, 5, 7]` then their sum is 16.

    This metric creates one variable, `total`.
    This is ultimately returned as the sum value.


    Compilation example:

    ```python
    program.compile(
        metrics=[
            synalinks.metrics.Sum(),
        ],
    )
    ```

    Args:
        name (str): (Optional) string name of the metric instance.
        in_mask (list): (Optional) list of keys to keep to compute the metric.
        out_mask (list): (Optional) list of keys to remove to compute the metric.
        in_mask_pattern (str): (Optional) Regex pattern; fields whose names match
            are kept (combined with ``in_mask`` via OR).
        out_mask_pattern (str): (Optional) Regex pattern; fields whose names match
            are dropped (combined with ``out_mask`` via OR).

    Example:

    ```python
    >>> m = metrics.Sum()
    >>> m.update_state([1, 3, 5, 7])
    >>> m.result()
    16.0
    ```
    """

    def __init__(
        self,
        name="sum",
        in_mask=None,
        out_mask=None,
        in_mask_pattern=None,
        out_mask_pattern=None,
    ):
        super().__init__(
            name=name,
            in_mask=in_mask,
            out_mask=out_mask,
            in_mask_pattern=in_mask_pattern,
            out_mask_pattern=out_mask_pattern,
        )
        self.total = self.add_variable(
            data_model=Total,
            name="total",
        )

    async def update_state(self, values):
        values = reduce_to_samplewise_values(values, reduce_fn=numpy.sum)
        total = self.total.get("total")
        self.total.update({"total": float(numpy.sum(total, values))})

    def reset_state(self):
        self.total.assign(Total())

    def result(self):
        return self.total.get("total")