# tf.math.is_strictly_increasing

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| [![](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/check_ops.py#L2027-L2067) |

Returns `True` if `x` is strictly increasing.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.debugging.is_strictly_increasing`](https://www.tensorflow.org/api_docs/python/tf/math/is_strictly_increasing), [`tf.compat.v1.is_strictly_increasing`](https://www.tensorflow.org/api_docs/python/tf/math/is_strictly_increasing), [`tf.compat.v1.math.is_strictly_increasing`](https://www.tensorflow.org/api_docs/python/tf/math/is_strictly_increasing)

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    tf.math.is_strictly_increasing(
        x, name=None
    )

Elements of `x` are compared in row-major order. The tensor `[x[0],...]`
is strictly increasing if for every adjacent pair we have `x[i] < x[i+1]`.
If `x` has less than two elements, it is trivially strictly increasing.

See also: `is_non_decreasing`

    x1 = tf.constant([1.0, 2.0, 3.0])
    tf.math.is_strictly_increasing(x1)
    <tf.Tensor: shape=(), dtype=bool, numpy=True>
    x2 = tf.constant([3.0, 1.0, 2.0])
    tf.math.is_strictly_increasing(x2)
    <tf.Tensor: shape=(), dtype=bool, numpy=False>

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| ## Args ||
|---|---|
| `x` | Numeric `Tensor`. |
| `name` | A name for this operation (optional). Defaults to "is_strictly_increasing" |

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| ## Returns ||
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| Boolean `Tensor`, equal to `True` iff `x` is strictly increasing. ||

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| ## Raises ||
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| `TypeError` | if `x` is not a numeric tensor. |

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