]
github-actions = [
    "httpx >=0.27.0,<1.0.0",
    "pydantic >=2.9.0,<3.0.0",
    "pydantic-settings >=2.1.0,<3.0.0",
    "pygithub >=2.3.0,<3.0.0",
    "pyyaml >=5.3.1,<7.0.0",
    "smokeshow >=0.5.0",
]
tests = [
    { include-group = "docs-tests" },
    "anyio[trio] >=3.2.1,<5.0.0",
    "coverage[toml] >=7.13,<8.0",
    "dirty-equals >=0.9.0",
    "flask >=3.0.0,<4.0.0",

</pre>

<p>
produces the same slice as allocating an array and <a href="#Slice_expressions">slicing</a>
it, so these two expressions are equivalent:
</p>

<pre>
make([]int, 50, 100)
new([100]int)[0:50]
</pre>

<p>
Like arrays, slices are always one-dimensional but may be composed to construct
higher-dimensional objects.
With arrays of arrays, the inner arrays are, by construction, always the same length;

    is still happening correctly along the way. See the
    [validating correctness migration guide](https://www.tensorflow.org/guide/migrate/validate_correctness)
    for more info.

# Release 0.5.0

Initial release of TensorFlow.

### Internal

* ⬆ Bump tiangolo/issue-manager from 0.5.0 to 0.5.1. PR [#12173](https://github.com/fastapi/fastapi/pull/12173) by [@dependabot[bot]](https://github.com/apps/dependabot).