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Computes the mean relative error by normalizing with the given values.
tf.metrics.mean_relative_error(
    labels, predictions, normalizer, weights=None, metrics_collections=None,
    updates_collections=None, name=None
)
The mean_relative_error function creates two local variables,
total and count that are used to compute the mean relative absolute error.
This average is weighted by weights, and it is ultimately returned as
mean_relative_error: an idempotent operation that simply divides total by
count.
For estimation of the metric over a stream of data, the function creates an
update_op operation that updates these variables and returns the
mean_reative_error. Internally, a relative_errors operation divides the
absolute value of the differences between predictions and labels by the
normalizer. Then update_op increments total with the reduced sum of the
product of weights and relative_errors, and it increments count with the
reduced sum of weights.
If weights is None, weights default to 1. Use weights of 0 to mask values.
| Args | |
|---|---|
| labels | A Tensorof the same shape aspredictions. | 
| predictions | A Tensorof arbitrary shape. | 
| normalizer | A Tensorof the same shape aspredictions. | 
| weights | Optional Tensorwhose rank is either 0, or the same rank aslabels, and must be broadcastable tolabels(i.e., all dimensions must
be either1, or the same as the correspondinglabelsdimension). | 
| metrics_collections | An optional list of collections that mean_relative_errorshould be added to. | 
| updates_collections | An optional list of collections that update_opshould
be added to. | 
| name | An optional variable_scope name. | 
| Returns | |
|---|---|
| mean_relative_error | A Tensorrepresenting the current mean, the value oftotaldivided bycount. | 
| update_op | An operation that increments the totalandcountvariables
appropriately and whose value matchesmean_relative_error. | 
| Raises | |
|---|---|
| ValueError | If predictionsandlabelshave mismatched shapes, or ifweightsis notNoneand its shape doesn't matchpredictions, or if
eithermetrics_collectionsorupdates_collectionsare not a list or
tuple. | 
| RuntimeError | If eager execution is enabled. |