# tf.compat.v1.metrics.true_positives_at_thresholds

<br />

|---|
| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/metrics_impl.py#L2080-L2133) |

Computes true positives at provided threshold values.

    tf.compat.v1.metrics.true_positives_at_thresholds(
        labels,
        predictions,
        thresholds,
        weights=None,
        metrics_collections=None,
        updates_collections=None,
        name=None
    )

If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.

<br />

<br />

<br />

| ## Args ||
|---|---|
| `labels` | A `Tensor` whose shape matches `predictions`. Will be cast to `bool`. |
| `predictions` | A floating point `Tensor` of arbitrary shape and whose values are in the range `[0, 1]`. |
| `thresholds` | A python list or tuple of float thresholds in `[0, 1]`. |
| `weights` | Optional `Tensor` whose rank is either 0, or the same rank as `labels`, and must be broadcastable to `labels` (i.e., all dimensions must be either `1`, or the same as the corresponding `labels` dimension). |
| `metrics_collections` | An optional list of collections that `true_positives` should be added to. |
| `updates_collections` | An optional list of collections that `update_op` should be added to. |
| `name` | An optional variable_scope name. |

<br />

<br />

<br />

<br />

| ## Returns ||
|---|---|
| `true_positives` | A float `Tensor` of shape `[len(thresholds)]`. |
| `update_op` | An operation that updates the `true_positives` variable and returns its current value. |

<br />

<br />

<br />

<br />

| ## Raises ||
|---|---|
| `ValueError` | If `predictions` and `labels` have mismatched shapes, or if `weights` is not `None` and its shape doesn't match `predictions`, or if either `metrics_collections` or `updates_collections` are not a list or tuple. |
| `RuntimeError` | If eager execution is enabled. |

<br />