Computes the mean squared error between the labels and predictions.

The mean_squared_error function creates two local variables, total and count that are used to compute the mean squared error. This average is weighted by weights, and it is ultimately returned as mean_squared_error: an idempotent operation that simply divides total by count.

For estimation of the metric over a stream of data, the function creates an