The streaming_mean function creates two local variables, total and count
that are used to compute the average of values. This average is ultimately
returned as mean which is 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.
update_op increments total with the reduced sum of the product of values
and weights, 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
values
A Tensor of arbitrary dimensions.
weights
Tensor whose rank is either 0, or the same rank as values, and
must be broadcastable to values (i.e., all dimensions must be either
1, or the same as the corresponding values dimension).
metrics_collections
An optional list of collections that mean should be
added to.
updates_collections
An optional list of collections that update_op should
be added to.
name
An optional variable_scope name.
Returns
mean
A Tensor representing the current mean, the value of total divided
by count.
update_op
An operation that increments the total and count variables
appropriately and whose value matches mean.
Raises
ValueError
If weights is not None and its shape doesn't match values,
or if either metrics_collections or updates_collections are not a list
or tuple.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.contrib.metrics.streaming_mean\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/contrib/metrics/python/ops/metric_ops.py#L227-L274) |\n\nComputes the (weighted) mean of the given values. (deprecated) \n\n tf.contrib.metrics.streaming_mean(\n values, weights=None, metrics_collections=None, updates_collections=None,\n name=None\n )\n\n| **Warning:** THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Please switch to tf.metrics.mean\n\nThe `streaming_mean` function creates two local variables, `total` and `count`\nthat are used to compute the average of `values`. This average is ultimately\nreturned as `mean` which is an idempotent operation that simply divides\n`total` by `count`.\n\nFor estimation of the metric over a stream of data, the function creates an\n`update_op` operation that updates these variables and returns the `mean`.\n`update_op` increments `total` with the reduced sum of the product of `values`\nand `weights`, and it increments `count` with the reduced sum of `weights`.\n\nIf `weights` is `None`, weights default to 1. Use weights of 0 to mask values.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `values` | A `Tensor` of arbitrary dimensions. |\n| `weights` | `Tensor` whose rank is either 0, or the same rank as `values`, and must be broadcastable to `values` (i.e., all dimensions must be either `1`, or the same as the corresponding `values` dimension). |\n| `metrics_collections` | An optional list of collections that `mean` should be added to. |\n| `updates_collections` | An optional list of collections that `update_op` should be added to. |\n| `name` | An optional variable_scope name. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|-------------|--------------------------------------------------------------------------------------------------------------|\n| `mean` | A `Tensor` representing the current mean, the value of `total` divided by `count`. |\n| `update_op` | An operation that increments the `total` and `count` variables appropriately and whose value matches `mean`. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|-------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `ValueError` | If `weights` is not `None` and its shape doesn't match `values`, or if either `metrics_collections` or `updates_collections` are not a list or tuple. |\n\n\u003cbr /\u003e"]]
View source on GitHub