From bec0d46b7a2b4ab6a3a3f38fa365caf25b3cc116 Mon Sep 17 00:00:00 2001
From: Hans Dembinski <hans.dembinski@gmail.com>
Date: Sun, 26 Nov 2023 16:56:07 +0100
Subject: [PATCH 1/9] update benchmark code for newer root

---
 bench/test_cost.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/bench/test_cost.py b/bench/test_cost.py
index c9f82b65..682ac0ed 100644
--- a/bench/test_cost.py
+++ b/bench/test_cost.py
@@ -213,7 +213,8 @@ def run():
 @pytest.mark.parametrize("n", N)
 @pytest.mark.parametrize("BatchMode", [False, True])
 @pytest.mark.parametrize("NumCPU", [0, nb.get_num_threads()])
-def test_RooFit(benchmark, n, BatchMode, NumCPU):
+@pytest.mark.parametrize("EvalBackend", ["legacy", "cpu"])
+def test_RooFit(benchmark, n, BatchMode, NumCPU, EvalBackend):
     import ROOT as R
 
     x = R.RooRealVar("x", "x", 0, 1)
@@ -232,7 +233,11 @@ def run():
         sigma.setVal(0.1)
         slope.setVal(1)
         z.setVal(0.5)
-        args = [R.RooFit.PrintLevel(-1), R.RooFit.BatchMode(BatchMode)]
+        args = [
+            R.RooFit.PrintLevel(-1),
+            R.RooFit.BatchMode(BatchMode),
+            R.RooFit.EvalBackend(EvalBackend),
+        ]
         if NumCPU:
             args.append(R.RooFit.NumCPU(NumCPU))
         pdf.fitTo(data, *args)

From 379f2b4dbb032052d5467fb71aa91c4e2a0282f1 Mon Sep 17 00:00:00 2001
From: Hans Dembinski <hans.dembinski@gmail.com>
Date: Sun, 26 Nov 2023 16:58:20 +0100
Subject: [PATCH 2/9] ignore svg in bench folder

---
 .gitignore | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.gitignore b/.gitignore
index f1b916b5..8229cb75 100644
--- a/.gitignore
+++ b/.gitignore
@@ -22,6 +22,8 @@ __pycache__
 
 pip-wheel-metadata
 
+bench/*.svg
+
 .benchmarks
 .DS_Store
 .idea

From 60977f567023d23f80dcfb8991e835ec5cbae24f Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Wed, 6 Dec 2023 18:26:02 +0100
Subject: [PATCH 3/9] Bump actions/checkout from 3 to 4 (#945)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Bumps [actions/checkout](https://github.com/actions/checkout) from 3 to
4.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/actions/checkout/releases">actions/checkout's
releases</a>.</em></p>
<blockquote>
<h2>v4.0.0</h2>
<h2>What's Changed</h2>
<ul>
<li>Update default runtime to node20 by <a
href="https://github.com/takost"><code>@​takost</code></a> in <a
href="https://redirect.github.com/actions/checkout/pull/1436">actions/checkout#1436</a></li>
<li>Support fetching without the --progress option by <a
href="https://github.com/simonbaird"><code>@​simonbaird</code></a> in <a
href="https://redirect.github.com/actions/checkout/pull/1067">actions/checkout#1067</a></li>
<li>Release 4.0.0 by <a
href="https://github.com/takost"><code>@​takost</code></a> in <a
href="https://redirect.github.com/actions/checkout/pull/1447">actions/checkout#1447</a></li>
</ul>
<h2>New Contributors</h2>
<ul>
<li><a href="https://github.com/takost"><code>@​takost</code></a> made
their first contribution in <a
href="https://redirect.github.com/actions/checkout/pull/1436">actions/checkout#1436</a></li>
<li><a
href="https://github.com/simonbaird"><code>@​simonbaird</code></a> made
their first contribution in <a
href="https://redirect.github.com/actions/checkout/pull/1067">actions/checkout#1067</a></li>
</ul>
<p><strong>Full Changelog</strong>: <a
href="https://github.com/actions/checkout/compare/v3...v4.0.0">https://github.com/actions/checkout/compare/v3...v4.0.0</a></p>
<h2>v3.6.0</h2>
<h2>What's Changed</h2>
<ul>
<li>Mark test scripts with Bash'isms to be run via Bash by <a
href="https://github.com/dscho"><code>@​dscho</code></a> in <a
href="https://redirect.github.com/actions/checkout/pull/1377">actions/checkout#1377</a></li>
<li>Add option to fetch tags even if fetch-depth &gt; 0 by <a
href="https://github.com/RobertWieczoreck"><code>@​RobertWieczoreck</code></a>
in <a
href="https://redirect.github.com/actions/checkout/pull/579">actions/checkout#579</a></li>
<li>Release 3.6.0 by <a
href="https://github.com/luketomlinson"><code>@​luketomlinson</code></a>
in <a
href="https://redirect.github.com/actions/checkout/pull/1437">actions/checkout#1437</a></li>
</ul>
<h2>New Contributors</h2>
<ul>
<li><a
href="https://github.com/RobertWieczoreck"><code>@​RobertWieczoreck</code></a>
made their first contribution in <a
href="https://redirect.github.com/actions/checkout/pull/579">actions/checkout#579</a></li>
<li><a
href="https://github.com/luketomlinson"><code>@​luketomlinson</code></a>
made their first contribution in <a
href="https://redirect.github.com/actions/checkout/pull/1437">actions/checkout#1437</a></li>
</ul>
<p><strong>Full Changelog</strong>: <a
href="https://github.com/actions/checkout/compare/v3.5.3...v3.6.0">https://github.com/actions/checkout/compare/v3.5.3...v3.6.0</a></p>
<h2>v3.5.3</h2>
<h2>What's Changed</h2>
<ul>
<li>Fix: Checkout Issue in self hosted runner due to faulty submodule
check-ins by <a
href="https://github.com/megamanics"><code>@​megamanics</code></a> in <a
href="https://redirect.github.com/actions/checkout/pull/1196">actions/checkout#1196</a></li>
<li>Fix typos found by codespell by <a
href="https://github.com/DimitriPapadopoulos"><code>@​DimitriPapadopoulos</code></a>
in <a
href="https://redirect.github.com/actions/checkout/pull/1287">actions/checkout#1287</a></li>
<li>Add support for sparse checkouts by <a
href="https://github.com/dscho"><code>@​dscho</code></a> and <a
href="https://github.com/dfdez"><code>@​dfdez</code></a> in <a
href="https://redirect.github.com/actions/checkout/pull/1369">actions/checkout#1369</a></li>
<li>Release v3.5.3 by <a
href="https://github.com/TingluoHuang"><code>@​TingluoHuang</code></a>
in <a
href="https://redirect.github.com/actions/checkout/pull/1376">actions/checkout#1376</a></li>
</ul>
<h2>New Contributors</h2>
<ul>
<li><a
href="https://github.com/megamanics"><code>@​megamanics</code></a> made
their first contribution in <a
href="https://redirect.github.com/actions/checkout/pull/1196">actions/checkout#1196</a></li>
<li><a
href="https://github.com/DimitriPapadopoulos"><code>@​DimitriPapadopoulos</code></a>
made their first contribution in <a
href="https://redirect.github.com/actions/checkout/pull/1287">actions/checkout#1287</a></li>
<li><a href="https://github.com/dfdez"><code>@​dfdez</code></a> made
their first contribution in <a
href="https://redirect.github.com/actions/checkout/pull/1369">actions/checkout#1369</a></li>
</ul>
<p><strong>Full Changelog</strong>: <a
href="https://github.com/actions/checkout/compare/v3...v3.5.3">https://github.com/actions/checkout/compare/v3...v3.5.3</a></p>
<h2>v3.5.2</h2>
<h2>What's Changed</h2>
<ul>
<li>Fix: Use correct API url / endpoint in GHES by <a
href="https://github.com/fhammerl"><code>@​fhammerl</code></a> in <a
href="https://redirect.github.com/actions/checkout/pull/1289">actions/checkout#1289</a>
based on <a
href="https://redirect.github.com/actions/checkout/issues/1286">#1286</a>
by <a href="https://github.com/1newsr"><code>@​1newsr</code></a></li>
</ul>
<p><strong>Full Changelog</strong>: <a
href="https://github.com/actions/checkout/compare/v3.5.1...v3.5.2">https://github.com/actions/checkout/compare/v3.5.1...v3.5.2</a></p>
<h2>v3.5.1</h2>
<h2>What's Changed</h2>
<ul>
<li>Improve checkout performance on Windows runners by upgrading
<code>@​actions/github</code> dependency by <a
href="https://github.com/BrettDong"><code>@​BrettDong</code></a> in <a
href="https://redirect.github.com/actions/checkout/pull/1246">actions/checkout#1246</a></li>
</ul>
<h2>New Contributors</h2>
<ul>
<li><a href="https://github.com/BrettDong"><code>@​BrettDong</code></a>
made their first contribution in <a
href="https://redirect.github.com/actions/checkout/pull/1246">actions/checkout#1246</a></li>
</ul>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/actions/checkout/blob/main/CHANGELOG.md">actions/checkout's
changelog</a>.</em></p>
<blockquote>
<h1>Changelog</h1>
<h2>v4.1.0</h2>
<ul>
<li><a href="https://redirect.github.com/actions/checkout/pull/1396">Add
support for partial checkout filters</a></li>
</ul>
<h2>v4.0.0</h2>
<ul>
<li><a
href="https://redirect.github.com/actions/checkout/pull/1067">Support
fetching without the --progress option</a></li>
<li><a
href="https://redirect.github.com/actions/checkout/pull/1436">Update to
node20</a></li>
</ul>
<h2>v3.6.0</h2>
<ul>
<li><a
href="https://redirect.github.com/actions/checkout/pull/1377">Fix: Mark
test scripts with Bash'isms to be run via Bash</a></li>
<li><a href="https://redirect.github.com/actions/checkout/pull/579">Add
option to fetch tags even if fetch-depth &gt; 0</a></li>
</ul>
<h2>v3.5.3</h2>
<ul>
<li><a
href="https://redirect.github.com/actions/checkout/pull/1196">Fix:
Checkout fail in self-hosted runners when faulty submodule are
checked-in</a></li>
<li><a href="https://redirect.github.com/actions/checkout/pull/1287">Fix
typos found by codespell</a></li>
<li><a href="https://redirect.github.com/actions/checkout/pull/1369">Add
support for sparse checkouts</a></li>
</ul>
<h2>v3.5.2</h2>
<ul>
<li><a href="https://redirect.github.com/actions/checkout/pull/1289">Fix
api endpoint for GHES</a></li>
</ul>
<h2>v3.5.1</h2>
<ul>
<li><a href="https://redirect.github.com/actions/checkout/pull/1246">Fix
slow checkout on Windows</a></li>
</ul>
<h2>v3.5.0</h2>
<ul>
<li><a href="https://redirect.github.com/actions/checkout/pull/1237">Add
new public key for known_hosts</a></li>
</ul>
<h2>v3.4.0</h2>
<ul>
<li><a
href="https://redirect.github.com/actions/checkout/pull/1209">Upgrade
codeql actions to v2</a></li>
<li><a
href="https://redirect.github.com/actions/checkout/pull/1210">Upgrade
dependencies</a></li>
<li><a
href="https://redirect.github.com/actions/checkout/pull/1225">Upgrade
<code>@​actions/io</code></a></li>
</ul>
<h2>v3.3.0</h2>
<ul>
<li><a
href="https://redirect.github.com/actions/checkout/pull/1045">Implement
branch list using callbacks from exec function</a></li>
<li><a href="https://redirect.github.com/actions/checkout/pull/1050">Add
in explicit reference to private checkout options</a></li>
<li>[Fix comment typos (that got added in <a
href="https://redirect.github.com/actions/checkout/issues/770">#770</a>)](<a
href="https://redirect.github.com/actions/checkout/pull/1057">actions/checkout#1057</a>)</li>
</ul>
<h2>v3.2.0</h2>
<ul>
<li><a href="https://redirect.github.com/actions/checkout/pull/942">Add
GitHub Action to perform release</a></li>
<li><a href="https://redirect.github.com/actions/checkout/pull/967">Fix
status badge</a></li>
<li><a
href="https://redirect.github.com/actions/checkout/pull/1002">Replace
datadog/squid with ubuntu/squid Docker image</a></li>
<li><a href="https://redirect.github.com/actions/checkout/pull/964">Wrap
pipeline commands for submoduleForeach in quotes</a></li>
<li><a
href="https://redirect.github.com/actions/checkout/pull/1029">Update
<code>@​actions/io</code> to 1.1.2</a></li>
<li><a
href="https://redirect.github.com/actions/checkout/pull/1039">Upgrading
version to 3.2.0</a></li>
</ul>
<h2>v3.1.0</h2>
<ul>
<li><a href="https://redirect.github.com/actions/checkout/pull/939">Use
<code>@​actions/core</code> <code>saveState</code> and
<code>getState</code></a></li>
<li><a href="https://redirect.github.com/actions/checkout/pull/922">Add
<code>github-server-url</code> input</a></li>
</ul>
<h2>v3.0.2</h2>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="https://github.com/actions/checkout/commit/8ade135a41bc03ea155e62e844d188df1ea18608"><code>8ade135</code></a>
Prepare 4.1.0 release (<a
href="https://redirect.github.com/actions/checkout/issues/1496">#1496</a>)</li>
<li><a
href="https://github.com/actions/checkout/commit/c533a0a4cfc4962971818edcfac47a2899e69799"><code>c533a0a</code></a>
Add support for partial checkout filters (<a
href="https://redirect.github.com/actions/checkout/issues/1396">#1396</a>)</li>
<li><a
href="https://github.com/actions/checkout/commit/72f2cec99f417b1a1c5e2e88945068983b7965f9"><code>72f2cec</code></a>
Update README.md for V4 (<a
href="https://redirect.github.com/actions/checkout/issues/1452">#1452</a>)</li>
<li><a
href="https://github.com/actions/checkout/commit/3df4ab11eba7bda6032a0b82a6bb43b11571feac"><code>3df4ab1</code></a>
Release 4.0.0 (<a
href="https://redirect.github.com/actions/checkout/issues/1447">#1447</a>)</li>
<li><a
href="https://github.com/actions/checkout/commit/8b5e8b768746b50394015010d25e690bfab9dfbc"><code>8b5e8b7</code></a>
Support fetching without the --progress option (<a
href="https://redirect.github.com/actions/checkout/issues/1067">#1067</a>)</li>
<li><a
href="https://github.com/actions/checkout/commit/97a652b80035363df47baee5031ec8670b8878ac"><code>97a652b</code></a>
Update default runtime to node20 (<a
href="https://redirect.github.com/actions/checkout/issues/1436">#1436</a>)</li>
<li>See full diff in <a
href="https://github.com/actions/checkout/compare/v3...v4">compare
view</a></li>
</ul>
</details>
<br />


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You can trigger Dependabot actions by commenting on this PR:
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</details>

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Hans Dembinski <HDembinski@users.noreply.github.com>
---
 .github/workflows/coverage.yml                 | 2 +-
 .github/workflows/docs.yml                     | 2 +-
 .github/workflows/release.yml                  | 8 ++++----
 .github/workflows/test.yml                     | 4 ++--
 bench/plot.ipynb                               | 2 +-
 doc/_static/interactive_demo.ipynb             | 2 +-
 doc/notebooks/automatic_differentiation.ipynb  | 2 +-
 doc/notebooks/basic.ipynb                      | 2 +-
 doc/notebooks/binned_vs_unbinned.ipynb         | 2 +-
 doc/notebooks/conditional_variable.ipynb       | 2 +-
 doc/notebooks/cost_function_benchmarks.ipynb   | 2 +-
 doc/notebooks/cost_functions.ipynb             | 2 +-
 doc/notebooks/cython.ipynb                     | 2 +-
 doc/notebooks/error_bands.ipynb                | 2 +-
 doc/notebooks/external_minimizer.ipynb         | 2 +-
 doc/notebooks/generic_least_squares.ipynb      | 2 +-
 doc/notebooks/gof.ipynb                        | 2 +-
 doc/notebooks/hesse_and_minos.ipynb            | 2 +-
 doc/notebooks/interactive.ipynb                | 2 +-
 doc/notebooks/memory_layout.ipynb              | 2 +-
 doc/notebooks/numba.ipynb                      | 2 +-
 doc/notebooks/roofit.ipynb                     | 2 +-
 doc/notebooks/roofit/rf101_basics.ipynb        | 2 +-
 doc/notebooks/roofit/rf109_chi2residpull.ipynb | 2 +-
 doc/notebooks/scipy_and_constraints.ipynb      | 2 +-
 doc/notebooks/simultaneous_fits.ipynb          | 2 +-
 doc/notebooks/template_fits.ipynb              | 2 +-
 doc/notebooks/template_gof.ipynb               | 2 +-
 doc/notebooks/template_model_mix.ipynb         | 2 +-
 29 files changed, 33 insertions(+), 33 deletions(-)

diff --git a/.github/workflows/coverage.yml b/.github/workflows/coverage.yml
index ebde7adf..ab3d05d3 100644
--- a/.github/workflows/coverage.yml
+++ b/.github/workflows/coverage.yml
@@ -26,7 +26,7 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
       with:
         submodules: true
     - uses: hendrikmuhs/ccache-action@v1.2
diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index 1c5dae26..cf2fa5b0 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -15,7 +15,7 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
       with:
         submodules: true
     - uses: hendrikmuhs/ccache-action@v1.2
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index 4c11f25d..2474e425 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -16,7 +16,7 @@ jobs:
     outputs:
       tag: ${{ steps.tag.outputs.tag }}
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
         with:
           submodules: true
           fetch-depth: 0
@@ -56,7 +56,7 @@ jobs:
       CIBW_BUILD: ${{ matrix.py }}-*
       CIBW_ARCHS_LINUX: ${{ matrix.arch }}
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
         with:
           submodules: true
 
@@ -77,7 +77,7 @@ jobs:
     name: source package
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
         with:
           submodules: true
 
@@ -111,7 +111,7 @@ jobs:
     runs-on: ubuntu-latest
     if: ${{ github.ref == 'refs/heads/main' }}
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - uses: softprops/action-gh-release@v1
         with:
           name: v${{ needs.release_check.outputs.tag }}
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 03542c0e..f498e7df 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -29,7 +29,7 @@ jobs:
             python-version: "pypy-3.8"
       fail-fast: false
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
       with:
         submodules: true
     # must come after checkout
@@ -51,7 +51,7 @@ jobs:
   #     py: /opt/python/cp309-cp309/bin/python
   #     img: quay.io/pypa/manylinux2014_aarch64
   #   steps:
-  #   - uses: actions/checkout@v3
+  #   - uses: actions/checkout@v4
   #     with:
   #       submodules: true
   #   - uses: docker/setup-qemu-action@v2
diff --git a/bench/plot.ipynb b/bench/plot.ipynb
index 3a9df847..14f6af03 100644
--- a/bench/plot.ipynb
+++ b/bench/plot.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/doc/_static/interactive_demo.ipynb b/doc/_static/interactive_demo.ipynb
index 493806f2..56c79148 100644
--- a/doc/_static/interactive_demo.ipynb
+++ b/doc/_static/interactive_demo.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/doc/notebooks/automatic_differentiation.ipynb b/doc/notebooks/automatic_differentiation.ipynb
index c6039e43..deca8fd1 100644
--- a/doc/notebooks/automatic_differentiation.ipynb
+++ b/doc/notebooks/automatic_differentiation.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "attachments": {},
    "cell_type": "markdown",
diff --git a/doc/notebooks/basic.ipynb b/doc/notebooks/basic.ipynb
index 72850b26..a3738004 100644
--- a/doc/notebooks/basic.ipynb
+++ b/doc/notebooks/basic.ipynb
@@ -1,5 +1,5 @@
 {
-    "cells": [
+  "cells": [
         {
             "attachments": {},
             "cell_type": "markdown",
diff --git a/doc/notebooks/binned_vs_unbinned.ipynb b/doc/notebooks/binned_vs_unbinned.ipynb
index 18e97623..9c80a20b 100644
--- a/doc/notebooks/binned_vs_unbinned.ipynb
+++ b/doc/notebooks/binned_vs_unbinned.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/doc/notebooks/conditional_variable.ipynb b/doc/notebooks/conditional_variable.ipynb
index 817d555f..70154be5 100644
--- a/doc/notebooks/conditional_variable.ipynb
+++ b/doc/notebooks/conditional_variable.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "id": "naked-recruitment",
diff --git a/doc/notebooks/cost_function_benchmarks.ipynb b/doc/notebooks/cost_function_benchmarks.ipynb
index c4485c7a..65071b31 100644
--- a/doc/notebooks/cost_function_benchmarks.ipynb
+++ b/doc/notebooks/cost_function_benchmarks.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/doc/notebooks/cost_functions.ipynb b/doc/notebooks/cost_functions.ipynb
index a82de510..c277dda5 100644
--- a/doc/notebooks/cost_functions.ipynb
+++ b/doc/notebooks/cost_functions.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "id": "negative-concord",
diff --git a/doc/notebooks/cython.ipynb b/doc/notebooks/cython.ipynb
index ab321466..81df01ec 100644
--- a/doc/notebooks/cython.ipynb
+++ b/doc/notebooks/cython.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/doc/notebooks/error_bands.ipynb b/doc/notebooks/error_bands.ipynb
index f434fd1b..cd7971c1 100644
--- a/doc/notebooks/error_bands.ipynb
+++ b/doc/notebooks/error_bands.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "id": "frozen-raising",
diff --git a/doc/notebooks/external_minimizer.ipynb b/doc/notebooks/external_minimizer.ipynb
index cc0fe8b5..3f7fa71b 100644
--- a/doc/notebooks/external_minimizer.ipynb
+++ b/doc/notebooks/external_minimizer.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/doc/notebooks/generic_least_squares.ipynb b/doc/notebooks/generic_least_squares.ipynb
index a3fd89a5..367477e0 100644
--- a/doc/notebooks/generic_least_squares.ipynb
+++ b/doc/notebooks/generic_least_squares.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/doc/notebooks/gof.ipynb b/doc/notebooks/gof.ipynb
index b499cb8d..098b55cd 100644
--- a/doc/notebooks/gof.ipynb
+++ b/doc/notebooks/gof.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/doc/notebooks/hesse_and_minos.ipynb b/doc/notebooks/hesse_and_minos.ipynb
index abb0ceed..fce04a25 100644
--- a/doc/notebooks/hesse_and_minos.ipynb
+++ b/doc/notebooks/hesse_and_minos.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "attachments": {},
    "cell_type": "markdown",
diff --git a/doc/notebooks/interactive.ipynb b/doc/notebooks/interactive.ipynb
index c5ec41ee..ddb07d12 100644
--- a/doc/notebooks/interactive.ipynb
+++ b/doc/notebooks/interactive.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "attachments": {},
    "cell_type": "markdown",
diff --git a/doc/notebooks/memory_layout.ipynb b/doc/notebooks/memory_layout.ipynb
index dba02c0e..790d62a0 100644
--- a/doc/notebooks/memory_layout.ipynb
+++ b/doc/notebooks/memory_layout.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/doc/notebooks/numba.ipynb b/doc/notebooks/numba.ipynb
index 3ac41ebc..fae5cb50 100644
--- a/doc/notebooks/numba.ipynb
+++ b/doc/notebooks/numba.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/doc/notebooks/roofit.ipynb b/doc/notebooks/roofit.ipynb
index 6181d15c..ecf85686 100644
--- a/doc/notebooks/roofit.ipynb
+++ b/doc/notebooks/roofit.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "attachments": {},
    "cell_type": "markdown",
diff --git a/doc/notebooks/roofit/rf101_basics.ipynb b/doc/notebooks/roofit/rf101_basics.ipynb
index 9141ed32..36b28b1d 100644
--- a/doc/notebooks/roofit/rf101_basics.ipynb
+++ b/doc/notebooks/roofit/rf101_basics.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "attachments": {},
    "cell_type": "markdown",
diff --git a/doc/notebooks/roofit/rf109_chi2residpull.ipynb b/doc/notebooks/roofit/rf109_chi2residpull.ipynb
index 1aa59d23..8e589bb9 100644
--- a/doc/notebooks/roofit/rf109_chi2residpull.ipynb
+++ b/doc/notebooks/roofit/rf109_chi2residpull.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "attachments": {},
    "cell_type": "markdown",
diff --git a/doc/notebooks/scipy_and_constraints.ipynb b/doc/notebooks/scipy_and_constraints.ipynb
index 0b271cda..23846aab 100644
--- a/doc/notebooks/scipy_and_constraints.ipynb
+++ b/doc/notebooks/scipy_and_constraints.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "id": "ffdfe095",
diff --git a/doc/notebooks/simultaneous_fits.ipynb b/doc/notebooks/simultaneous_fits.ipynb
index ce937b1e..cab60b3c 100644
--- a/doc/notebooks/simultaneous_fits.ipynb
+++ b/doc/notebooks/simultaneous_fits.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/doc/notebooks/template_fits.ipynb b/doc/notebooks/template_fits.ipynb
index 0497d64d..a61ca7be 100644
--- a/doc/notebooks/template_fits.ipynb
+++ b/doc/notebooks/template_fits.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "attachments": {},
    "cell_type": "markdown",
diff --git a/doc/notebooks/template_gof.ipynb b/doc/notebooks/template_gof.ipynb
index b4b44818..410df094 100644
--- a/doc/notebooks/template_gof.ipynb
+++ b/doc/notebooks/template_gof.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "attachments": {},
    "cell_type": "markdown",
diff --git a/doc/notebooks/template_model_mix.ipynb b/doc/notebooks/template_model_mix.ipynb
index 628dce49..686746da 100644
--- a/doc/notebooks/template_model_mix.ipynb
+++ b/doc/notebooks/template_model_mix.ipynb
@@ -1,5 +1,5 @@
 {
- "cells": [
+  "cells": [
   {
    "attachments": {},
    "cell_type": "markdown",

From 6de40c0a79304c25c4b969d39c39095bbef32058 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Wed, 6 Dec 2023 18:26:17 +0100
Subject: [PATCH 4/9] Bump docker/setup-qemu-action from 2 to 3 (#944)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Bumps
[docker/setup-qemu-action](https://github.com/docker/setup-qemu-action)
from 2 to 3.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/docker/setup-qemu-action/releases">docker/setup-qemu-action's
releases</a>.</em></p>
<blockquote>
<h2>v3.0.0</h2>
<ul>
<li>Node 20 as default runtime (requires <a
href="https://github.com/actions/runner/releases/tag/v2.308.0">Actions
Runner v2.308.0</a> or later) by <a
href="https://github.com/crazy-max"><code>@​crazy-max</code></a> in <a
href="https://redirect.github.com/docker/setup-qemu-action/pull/102">docker/setup-qemu-action#102</a></li>
<li>Bump <code>@​actions/core</code> from 1.10.0 to 1.10.1 in <a
href="https://redirect.github.com/docker/setup-qemu-action/pull/103">docker/setup-qemu-action#103</a></li>
<li>Bump semver from 6.3.0 to 6.3.1 in <a
href="https://redirect.github.com/docker/setup-qemu-action/pull/89">docker/setup-qemu-action#89</a></li>
</ul>
<p><strong>Full Changelog</strong>: <a
href="https://github.com/docker/setup-qemu-action/compare/v2.2.0...v3.0.0">https://github.com/docker/setup-qemu-action/compare/v2.2.0...v3.0.0</a></p>
<h2>v2.2.0</h2>
<ul>
<li>Trim off spaces in <code>platforms</code> input by <a
href="https://github.com/Chocobo1"><code>@​Chocobo1</code></a> in <a
href="https://redirect.github.com/docker/setup-qemu-action/pull/64">docker/setup-qemu-action#64</a></li>
<li>Switch to actions-toolkit implementation by <a
href="https://github.com/crazy-max"><code>@​crazy-max</code></a> in <a
href="https://redirect.github.com/docker/setup-qemu-action/pull/70">docker/setup-qemu-action#70</a>
<a
href="https://redirect.github.com/docker/setup-qemu-action/pull/80">docker/setup-qemu-action#80</a>
<a
href="https://redirect.github.com/docker/setup-qemu-action/pull/83">docker/setup-qemu-action#83</a></li>
</ul>
<p><strong>Full Changelog</strong>: <a
href="https://github.com/docker/setup-qemu-action/compare/v2.1.0...v2.2.0">https://github.com/docker/setup-qemu-action/compare/v2.1.0...v2.2.0</a></p>
<h2>v2.1.0</h2>
<ul>
<li>Use context for inputs by <a
href="https://github.com/crazy-max"><code>@​crazy-max</code></a> (<a
href="https://redirect.github.com/docker/setup-qemu-action/issues/62">#62</a>)</li>
<li>Use built-in <code>getExecOutput</code> by <a
href="https://github.com/crazy-max"><code>@​crazy-max</code></a> (<a
href="https://redirect.github.com/docker/setup-qemu-action/issues/61">#61</a>)</li>
<li>Remove workaround for <code>setOutput</code> by <a
href="https://github.com/crazy-max"><code>@​crazy-max</code></a> (<a
href="https://redirect.github.com/docker/setup-qemu-action/issues/63">#63</a>)</li>
<li>Bump <code>@​actions/core</code> from 1.6.0 to 1.10.0 (<a
href="https://redirect.github.com/docker/setup-qemu-action/issues/54">#54</a>
<a
href="https://redirect.github.com/docker/setup-qemu-action/issues/58">#58</a>
<a
href="https://redirect.github.com/docker/setup-qemu-action/issues/59">#59</a>)</li>
</ul>
<p><strong>Full Changelog</strong>: <a
href="https://github.com/docker/setup-qemu-action/compare/v2.0.0...v2.1.0">https://github.com/docker/setup-qemu-action/compare/v2.0.0...v2.1.0</a></p>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="https://github.com/docker/setup-qemu-action/commit/68827325e0b33c7199eb31dd4e31fbe9023e06e3"><code>6882732</code></a>
Merge pull request <a
href="https://redirect.github.com/docker/setup-qemu-action/issues/103">#103</a>
from docker/dependabot/npm_and_yarn/actions/core-1.10.1</li>
<li><a
href="https://github.com/docker/setup-qemu-action/commit/183f4af5043c24c5dcd58e6e9868b7df0a201a17"><code>183f4af</code></a>
chore: update generated content</li>
<li><a
href="https://github.com/docker/setup-qemu-action/commit/f17493529ee8f8b9fd58ed31aa1e9816c8345eb8"><code>f174935</code></a>
build(deps): bump <code>@​actions/core</code> from 1.10.0 to 1.10.1</li>
<li><a
href="https://github.com/docker/setup-qemu-action/commit/2e423eb50075d10a6af463e39e267d4057cc07bb"><code>2e423eb</code></a>
Merge pull request <a
href="https://redirect.github.com/docker/setup-qemu-action/issues/89">#89</a>
from docker/dependabot/npm_and_yarn/semver-6.3.1</li>
<li><a
href="https://github.com/docker/setup-qemu-action/commit/ecc406afa7d79acce0ed8a04bb5eb086136fd000"><code>ecc406a</code></a>
Bump semver from 6.3.0 to 6.3.1</li>
<li><a
href="https://github.com/docker/setup-qemu-action/commit/12dec5e201ab2f6dbea47c28f4a138590189069a"><code>12dec5e</code></a>
Merge pull request <a
href="https://redirect.github.com/docker/setup-qemu-action/issues/102">#102</a>
from crazy-max/update-node20</li>
<li><a
href="https://github.com/docker/setup-qemu-action/commit/c29b31213096fed2f8b8b36e66385d52653bf332"><code>c29b312</code></a>
chore: node 20 as default runtime</li>
<li><a
href="https://github.com/docker/setup-qemu-action/commit/34ae628c8f4fb0d5c8921b9a0ffa9dcf66120c07"><code>34ae628</code></a>
chore: update generated content</li>
<li><a
href="https://github.com/docker/setup-qemu-action/commit/1f3d2e1ac09548bbfb7d44b1809ac66e3d551ea4"><code>1f3d2e1</code></a>
chore: fix author in package.json</li>
<li><a
href="https://github.com/docker/setup-qemu-action/commit/277dbe8c9c1990b42dc38cb1f35a593889a31a62"><code>277dbe8</code></a>
vendor: bump <code>@​docker/actions-toolkit</code> from 0.3.0 to
0.12.0</li>
<li>Additional commits viewable in <a
href="https://github.com/docker/setup-qemu-action/compare/v2...v3">compare
view</a></li>
</ul>
</details>
<br />


[![Dependabot compatibility
score](https://dependabot-badges.githubapp.com/badges/compatibility_score?dependency-name=docker/setup-qemu-action&package-manager=github_actions&previous-version=2&new-version=3)](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores)

You can trigger a rebase of this PR by commenting `@dependabot rebase`.

[//]: # (dependabot-automerge-start)
[//]: # (dependabot-automerge-end)

---

<details>
<summary>Dependabot commands and options</summary>
<br />

You can trigger Dependabot actions by commenting on this PR:
- `@dependabot rebase` will rebase this PR
- `@dependabot recreate` will recreate this PR, overwriting any edits
that have been made to it
- `@dependabot merge` will merge this PR after your CI passes on it
- `@dependabot squash and merge` will squash and merge this PR after
your CI passes on it
- `@dependabot cancel merge` will cancel a previously requested merge
and block automerging
- `@dependabot reopen` will reopen this PR if it is closed
- `@dependabot close` will close this PR and stop Dependabot recreating
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- `@dependabot show <dependency name> ignore conditions` will show all
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- `@dependabot ignore this major version` will close this PR and stop
Dependabot creating any more for this major version (unless you reopen
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Dependabot creating any more for this minor version (unless you reopen
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</details>

> **Note**
> Automatic rebases have been disabled on this pull request as it has
been open for over 30 days.

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
---
 .github/workflows/release.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index 2474e425..8dbcd328 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -61,7 +61,7 @@ jobs:
           submodules: true
 
       - if: ${{ matrix.arch == 'aarch64' }}
-        uses: docker/setup-qemu-action@v2
+        uses: docker/setup-qemu-action@v3
 
       - uses: pypa/cibuildwheel@v2.14.1
         env:

From 503ff9f4a6603a7d646659f9ce05af3637b339fa Mon Sep 17 00:00:00 2001
From: Henry Schreiner <henry.fredrick.schreiner@cern.ch>
Date: Wed, 6 Dec 2023 12:28:23 -0500
Subject: [PATCH 5/9] fix: include debug info on failures (#946)

Adding debug info on failures.

---------

Signed-off-by: Henry Schreiner <henryschreineriii@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
---
 CMakeLists.txt | 1 +
 1 file changed, 1 insertion(+)

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 7274430d..eb69d67f 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -92,5 +92,6 @@ else()
 endif()
 target_include_directories(_core PRIVATE extern/root/math/minuit2/inc)
 set_target_properties(_core PROPERTIES VISIBILITY_INLINES_HIDDEN ON)
+target_compile_definitions(_core PUBLIC PYBIND11_DETAILED_ERROR_MESSAGES=1)
 
 install(TARGETS _core DESTINATION iminuit)

From 347164ef6c400dd9880df5aa99e41248268913d3 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 6 Dec 2023 18:29:43 +0100
Subject: [PATCH 6/9] [pre-commit.ci] pre-commit autoupdate (#939)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

<!--pre-commit.ci start-->
updates:
- [github.com/pre-commit/pre-commit-hooks: v4.4.0 →
v4.5.0](https://github.com/pre-commit/pre-commit-hooks/compare/v4.4.0...v4.5.0)
- [github.com/psf/black-pre-commit-mirror: 23.7.0 →
23.11.0](https://github.com/psf/black-pre-commit-mirror/compare/23.7.0...23.11.0)
- [github.com/astral-sh/ruff-pre-commit: v0.0.286 →
v0.1.6](https://github.com/astral-sh/ruff-pre-commit/compare/v0.0.286...v0.1.6)
- [github.com/pre-commit/mirrors-clang-format: v16.0.6 →
v17.0.6](https://github.com/pre-commit/mirrors-clang-format/compare/v16.0.6...v17.0.6)
- [github.com/pre-commit/mirrors-mypy: v1.5.1 →
v1.7.1](https://github.com/pre-commit/mirrors-mypy/compare/v1.5.1...v1.7.1)
<!--pre-commit.ci end-->

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
---
 .pre-commit-config.yaml | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 4ea69348..53b30875 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -15,7 +15,7 @@
 repos:
 # Standard hooks
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.4.0
+  rev: v4.5.0
   hooks:
   - id: check-case-conflict
   - id: check-docstring-first
@@ -34,20 +34,20 @@ repos:
 
 # Python formatting
 - repo: https://github.com/psf/black-pre-commit-mirror
-  rev: 23.7.0
+  rev: 23.11.0
   hooks:
   - id: black
 
 # Ruff linter, replacement for flake8, pydocstyle, isort
 - repo: https://github.com/astral-sh/ruff-pre-commit
-  rev: 'v0.0.286'
+  rev: 'v0.1.6'
   hooks:
     - id: ruff
       args: [--fix, --show-fixes]
 
 # C++ formatting
 - repo: https://github.com/pre-commit/mirrors-clang-format
-  rev: v16.0.6
+  rev: v17.0.6
   hooks:
   - id: clang-format
 
@@ -62,7 +62,7 @@ repos:
 
 # Python type checking
 - repo: https://github.com/pre-commit/mirrors-mypy
-  rev: 'v1.5.1'
+  rev: 'v1.7.1'
   hooks:
   - id: mypy
     additional_dependencies: [numpy]

From ab0628706ed897c5f267b9bf6fe9032aaaa2e574 Mon Sep 17 00:00:00 2001
From: Hans Dembinski <HDembinski@users.noreply.github.com>
Date: Wed, 6 Dec 2023 18:30:03 +0100
Subject: [PATCH 7/9] Benchmark update to ROOT 6.30 (#951)

The benchmark is updated to compare to RooFit in ROOT 6.30, which
features a changed API, and new computation backends that are faster.

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
---
 bench/plot.ipynb   | 110 +++++++++++++++++++++++++++++++++++++--------
 bench/test_cost.py | 109 ++++++++++++++++++++++++++++++--------------
 2 files changed, 167 insertions(+), 52 deletions(-)

diff --git a/bench/plot.ipynb b/bench/plot.ipynb
index 14f6af03..6cf7454e 100644
--- a/bench/plot.ipynb
+++ b/bench/plot.ipynb
@@ -2,26 +2,88 @@
   "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ".benchmarks/Darwin-CPython-3.11-64bit/0002_1ce156c8bfc48d97216c2852c30305386cd952dd_20231206_170213_uncommited-changes.json\n",
+      "benchmark results\n",
+      "  2023-12-06T17:12:29.954340\n",
+      "  Intel(R) Core(TM) i7-8569U CPU @ 2.80GHz\n",
+      "\n",
+      "UnbinnedNLL\n",
+      "UnbinnedNLL_log\n",
+      "nll_numba_stats\n",
+      "nll_scipy.stats\n",
+      "nll_numba\n",
+      "minuit\n",
+      "minuit_numba\n",
+      "minuit_log\n",
+      "minuit_log_numba\n",
+      "minuit_parallel_fastmath\n",
+      "minuit_parallel_fastmath_log\n",
+      "minuit_cfunc\n",
+      "minuit_UnbinnedNLL\n",
+      "minuit_UnbinnedNLL_log\n",
+      "RooFit_legacy\n",
+      "RooFit_legacy_NumCPU\n",
+      "RooFit_cpu\n",
+      "RooFit_cpu_NumCPU\n",
+      "RooFit_codegen\n",
+      "RooFit_codegen_NumCPU\n",
+      "RooFit_codegen_no_grad\n",
+      "RooFit_codegen_no_grad_NumCPU\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "import json\n",
     "import sys\n",
     "\n",
-    "if len(sys.argv) == 2:\n",
-    "    fn = sys.argv[1]\n",
-    "else:\n",
-    "    from pathlib import Path\n",
+    "from pathlib import Path\n",
     "\n",
-    "    paths = []\n",
-    "    for p in (Path(\"..\") / \".benchmarks\").rglob(\"*.json\"):\n",
-    "        paths.append((p.stat().st_mtime, p))\n",
-    "    paths.sort()\n",
-    "    fn = paths[-1][1]\n",
+    "paths = []\n",
+    "for p in Path(\".benchmarks\").rglob(\"*.json\"):\n",
+    "    paths.append((p.stat().st_mtime, p))\n",
+    "paths.sort()\n",
+    "fn = paths[-1][1]\n",
     "\n",
+    "print(fn)\n",
     "with open(fn) as f:\n",
     "    data = json.load(f)\n",
     "\n",
@@ -40,7 +102,15 @@
     "    n = int(n)\n",
     "    name = b[\"name\"]\n",
     "    name = name[name.find(\"_\") + 1 : name.find(\"[\")]\n",
-    "    extra = [k for (k, v) in params.items() if k not in (\"n\", \"lib\", \"model\") and v]\n",
+    "    extra = []\n",
+    "    for k, v in params.items():\n",
+    "        if k in (\"n\", \"lib\", \"model\"):\n",
+    "            continue\n",
+    "        if isinstance(v, (bool, int)):\n",
+    "            if v:\n",
+    "                extra.append(k)\n",
+    "        else:\n",
+    "            extra.append(v)\n",
     "    if extra:\n",
     "        name += \"_\" + \"_\".join(extra)\n",
     "    for key in (\"lib\", \"model\"):\n",
@@ -65,12 +135,16 @@
     "        \"minuit_cfunc\": \"iminuit+numba.cfunc\",\n",
     "    },\n",
     "    \"RooFit vs. iminuit+numba\": {\n",
-    "        \"RooFit\": \"RooFit\",\n",
-    "        \"RooFit_BatchMode\": \"RooFit with BatchMode\",\n",
-    "        \"RooFit_NumCPU\": \"RooFit with NumCPU\",\n",
+    "        \"RooFit_legacy\": \"RooFit [legacy]\",\n",
+    "        \"RooFit_legacy_NumCPU\": \"RooFit [legacy, parallel]\",\n",
+    "        \"RooFit_cpu\": \"RooFit [CPU]\",\n",
+    "        # \"RooFit_cpu_NumCPU\": \"RooFit [CPU, parallel]\",\n",
+    "        \"RooFit_codegen\": \"RooFit [Codegen]\",\n",
+    "        \"RooFit_codegen_no_grad\": \"RooFit [CodegenNoGrad]\",\n",
+    "        # \"RooFit_codegen_NumCPU\": \"RooFit [Codegen, parallel]\",\n",
     "        \"minuit\": \"iminuit+numba\",\n",
-    "        \"minuit_parallel_fastmath\": \"iminuit+numba with parallel, fastmath\",\n",
-    "        \"minuit_parallel_fastmath_log\": \"iminuit+numba logpdf with parallel, fastmath\",\n",
+    "        \"minuit_parallel_fastmath\": \"iminuit+numba [parallel, fastmath]\",\n",
+    "        \"minuit_parallel_fastmath_log\": \"iminuit+numba logpdf [parallel, fastmath]\",\n",
     "    },\n",
     "}\n",
     "\n",
@@ -132,7 +206,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.16"
+   "version": "3.11.3"
   },
   "orig_nbformat": 4
  },
diff --git a/bench/test_cost.py b/bench/test_cost.py
index 682ac0ed..7f841076 100644
--- a/bench/test_cost.py
+++ b/bench/test_cost.py
@@ -35,9 +35,12 @@ def logsumexp(a, b):
     r = np.empty_like(a)
     for i in nb.prange(len(r)):
         if a[i] > b[i]:
-            r[i] = a[i] + np.log(1 + np.exp(b[i] - a[i]))
+            c = a[i]
+            d = b[i]
         else:
-            r[i] = b[i] + np.log(1 + np.exp(a[i] - b[i]))
+            c = b[i]
+            d = a[i]
+        r[i] = c + np.log1p(np.exp(d - c))
     return r
 
 
@@ -210,39 +213,77 @@ def run():
     assert_allclose(m.values[:-1], ARGS[:-1], atol=2 / n**0.5)
 
 
-@pytest.mark.parametrize("n", N)
-@pytest.mark.parametrize("BatchMode", [False, True])
-@pytest.mark.parametrize("NumCPU", [0, nb.get_num_threads()])
-@pytest.mark.parametrize("EvalBackend", ["legacy", "cpu"])
-def test_RooFit(benchmark, n, BatchMode, NumCPU, EvalBackend):
+try:
     import ROOT as R
 
-    x = R.RooRealVar("x", "x", 0, 1)
-    z = R.RooRealVar("z", "z", 0.5, 0, 1)
-    mu = R.RooRealVar("mu", "mu", 0.5, 0, 1)
-    sigma = R.RooRealVar("sigma", "sigma", 0.1, 0, 10)
-    slope = R.RooRealVar("slope", "slope", 1.0, 0, 10)
-    pdf1 = R.RooGaussian("gauss", "gauss", x, mu, sigma)
-    pdf2 = R.RooExponential("expon", "expon", x, slope)
-    pdf = R.RooAddPdf("pdf", "pdf", [pdf1, pdf2], [z])
+    if R.__version__ >= "6.30":
+
+        @pytest.mark.parametrize("n", N)
+        @pytest.mark.parametrize("NumCPU", [0, nb.get_num_threads()])
+        @pytest.mark.parametrize(
+            "EvalBackend", ["legacy", "cpu", "codegen", "codegen_no_grad"]
+        )
+        def test_RooFit(benchmark, n, NumCPU, EvalBackend):
+            x = R.RooRealVar("x", "x", 0, 1)
+            z = R.RooRealVar("z", "z", 0.5, 0, 1)
+            mu = R.RooRealVar("mu", "mu", 0.5, 0, 1)
+            sigma = R.RooRealVar("sigma", "sigma", 0.1, 0, 10)
+            slope = R.RooRealVar("slope", "slope", 1.0, 0, 10)
+            pdf1 = R.RooGaussian("gauss", "gauss", x, mu, sigma)
+            pdf2 = R.RooExponential("expon", "expon", x, slope)
+            pdf = R.RooAddPdf("pdf", "pdf", [pdf1, pdf2], [z])
+
+            data = pdf.generate(x, n)
+
+            args = [R.RooFit.PrintLevel(-1), R.RooFit.EvalBackend(EvalBackend)]
+            if NumCPU:
+                args.append(R.RooFit.NumCPU(NumCPU))
+
+            def run():
+                mu.setVal(0.5)
+                sigma.setVal(0.1)
+                slope.setVal(1)
+                z.setVal(0.5)
+                pdf.fitTo(data, *args)
+
+            benchmark(run)
+            assert_allclose(z.getVal(), 0.5, atol=5 / n**0.5)
+            assert_allclose(mu.getVal(), 0.5, atol=5 / n**0.5)
+            assert_allclose(sigma.getVal(), 0.1, atol=5 / n**0.5)
 
-    data = pdf.generate(x, n)
+    else:
 
-    def run():
-        mu.setVal(0.5)
-        sigma.setVal(0.1)
-        slope.setVal(1)
-        z.setVal(0.5)
-        args = [
-            R.RooFit.PrintLevel(-1),
-            R.RooFit.BatchMode(BatchMode),
-            R.RooFit.EvalBackend(EvalBackend),
-        ]
-        if NumCPU:
-            args.append(R.RooFit.NumCPU(NumCPU))
-        pdf.fitTo(data, *args)
-
-    benchmark(run)
-    assert_allclose(z.getVal(), 0.5, atol=5 / n**0.5)
-    assert_allclose(mu.getVal(), 0.5, atol=5 / n**0.5)
-    assert_allclose(sigma.getVal(), 0.1, atol=5 / n**0.5)
+        @pytest.mark.parametrize("n", N)
+        @pytest.mark.parametrize("NumCPU", [0, nb.get_num_threads()])
+        @pytest.mark.parametrize("BatchMode", [False, True])
+        def test_RooFit(benchmark, n, NumCPU, BatchMode):
+            x = R.RooRealVar("x", "x", 0, 1)
+            z = R.RooRealVar("z", "z", 0.5, 0, 1)
+            mu = R.RooRealVar("mu", "mu", 0.5, 0, 1)
+            sigma = R.RooRealVar("sigma", "sigma", 0.1, 0, 10)
+            slope = R.RooRealVar("slope", "slope", 1.0, 0, 10)
+            pdf1 = R.RooGaussian("gauss", "gauss", x, mu, sigma)
+            pdf2 = R.RooExponential("expon", "expon", x, slope)
+            pdf = R.RooAddPdf("pdf", "pdf", [pdf1, pdf2], [z])
+
+            data = pdf.generate(x, n)
+
+            args = [R.RooFit.PrintLevel(-1), R.RooFit.BatchMode(BatchMode)]
+            if NumCPU:
+                args.append(R.RooFit.NumCPU(NumCPU, 1))
+                args.append(R.RooFit.Parallelize(NumCPU))
+
+            def run():
+                mu.setVal(0.5)
+                sigma.setVal(0.1)
+                slope.setVal(1)
+                z.setVal(0.5)
+                pdf.fitTo(data, *args)
+
+            benchmark(run)
+            assert_allclose(z.getVal(), 0.5, atol=5 / n**0.5)
+            assert_allclose(mu.getVal(), 0.5, atol=5 / n**0.5)
+            assert_allclose(sigma.getVal(), 0.1, atol=5 / n**0.5)
+
+except ModuleNotFoundError:
+    pass

From 86c520115154ac44acf7c599c7d01b5989116209 Mon Sep 17 00:00:00 2001
From: Hans Dembinski <HDembinski@users.noreply.github.com>
Date: Thu, 7 Dec 2023 13:03:58 +0100
Subject: [PATCH 8/9] Fix use of removed array rules in test (#952)

This fixes the failing test and two performance warnings raised in the
tests. Like @henryiii suggested, these changes were needed in one
particular test which relied on broadcasting rules (in this case they
were narrowing rules) that have been removed from numpy.

Previously, it was possible to do this
```
a = np.zeroes(2)
b = np.ones(1)
a[0] += b # add sequence of length 1 to scalar
```
---
 src/iminuit/util.py    |  2 +-
 tests/test_cost.py     | 12 ++++++------
 tests/test_minimize.py |  6 +++---
 3 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/src/iminuit/util.py b/src/iminuit/util.py
index 8f62ac03..fa3b1af4 100644
--- a/src/iminuit/util.py
+++ b/src/iminuit/util.py
@@ -236,7 +236,7 @@ def _set(self, i: int, arg: UserBound) -> None:
         state.set_error(i, err)
 
 
-def _normalize_limit(lim: UserBound) -> Tuple[float, float]:
+def _normalize_limit(lim: Optional[Iterable]) -> Tuple[float, float]:
     if lim is None:
         return (-np.inf, np.inf)
     a, b = lim
diff --git a/tests/test_cost.py b/tests/test_cost.py
index 05a1e407..b683b621 100644
--- a/tests/test_cost.py
+++ b/tests/test_cost.py
@@ -1164,7 +1164,7 @@ def grad2(x, b, a):
         return g
 
     def model3(x, c):
-        return c
+        return c * np.ones_like(x)
 
     def grad3(x, c):
         return np.ones((1, len(x)))
@@ -1201,7 +1201,7 @@ def grad3(x, c):
         a = 2
         b = 3
         ref = np.zeros(2)
-        ref[0] += lsq1.grad(a)
+        ref[0] += lsq1.grad(a)[0]
         ref[[1, 0]] += lsq2.grad(b, a)
         assert_allclose(lsq12.grad(a, b), ref)
 
@@ -1214,9 +1214,9 @@ def grad3(x, c):
         a = 2
         b = 3
         ref = np.zeros(2)
-        ref[0] += lsq1.grad(a)
+        ref[0] += lsq1.grad(a)[0]
         ref[[1, 0]] += lsq2.grad(b, a)
-        ref[0] += lsq1.grad(a)
+        ref[0] += lsq1.grad(a)[0]
         assert_allclose(lsq121.grad(a, b), ref)
 
     lsq312 = lsq3 + lsq12
@@ -1229,8 +1229,8 @@ def grad3(x, c):
         b = 3
         c = 4
         ref = np.zeros(3)
-        ref[0] += lsq3.grad(c)
-        ref[1] += lsq1.grad(a)
+        ref[0] += lsq3.grad(c)[0]
+        ref[1] += lsq1.grad(a)[0]
         ref[[2, 1]] += lsq2.grad(b, a)
         assert_allclose(lsq312.grad(c, a, b), ref)
 
diff --git a/tests/test_minimize.py b/tests/test_minimize.py
index ea5d50e3..07e51d67 100644
--- a/tests/test_minimize.py
+++ b/tests/test_minimize.py
@@ -63,9 +63,9 @@ def rosen(par):
 
 
 def test_disp(capsys):
-    minimize(lambda x: x**2, 0)
+    minimize(lambda x: np.sum(x**2), 0)
     assert capsys.readouterr()[0] == ""
-    minimize(lambda x: x**2, 0, options={"disp": True})
+    minimize(lambda x: np.sum(x**2), 0, options={"disp": True})
     assert capsys.readouterr()[0] != ""
 
 
@@ -115,7 +115,7 @@ class Fcn:
 
         def __call__(self, x):
             self.n += 1
-            return x**2 + 1e-2 * (self.n % 3)
+            return np.sum(x**2 + 1e-2 * (self.n % 3))
 
     r = minimize(Fcn(), [1], options={"maxfun": 100000000})
     assert not r.success

From 7be42dfb6e6b6ab72393ea9420f66264940fa9c9 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Thu, 7 Dec 2023 13:04:50 +0100
Subject: [PATCH 9/9] Bump pypa/cibuildwheel from 2.14.1 to 2.16.1 (#943)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Bumps [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel) from
2.14.1 to 2.16.1.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/pypa/cibuildwheel/releases">pypa/cibuildwheel's
releases</a>.</em></p>
<blockquote>
<h2>v2.16.1</h2>
<ul>
<li>🛠 Updates the prerelease CPython 3.12 version to 3.12.0rc3 (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1625">#1625</a>)</li>
<li>🛠 Only calls <code>linux32</code> in containers when necessary (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1599">#1599</a>)</li>
</ul>
<h2>v2.16.0</h2>
<ul>
<li>✨ Add the ability to pass additional flags to a build frontend
through the <a
href="https://cibuildwheel.readthedocs.io/en/stable/options/#build-frontend">CIBW_BUILD_FRONTEND</a>
option (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1588">#1588</a>).</li>
<li>✨ The environment variable SOURCE_DATE_EPOCH is now automatically
passed through to container Linux builds (useful for <a
href="https://reproducible-builds.org/docs/source-date-epoch/">reproducible
builds</a>!) (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1589">#1589</a>)</li>
<li>🛠 Updates the prerelease CPython 3.12 version to 3.12.0rc2 (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1604">#1604</a>)</li>
<li>🐛 Fix <code>requires_python</code> auto-detection from setup.py when
the call to <code>setup()</code> is within an <code>if __name__ ==
&quot;__main__&quot;</code> block (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1613">#1613</a>)</li>
<li>🐛 Fix a bug that prevented building Linux wheels in Docker on a
Windows host (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1573">#1573</a>)</li>
<li>🐛 <code>--only</code> can now select prerelease-pythons (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1564">#1564</a>)</li>
<li>📚 Docs &amp; examples updates (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1582">#1582</a>,
<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1593">#1593</a>,
<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1598">#1598</a>,
<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1615">#1615</a>)</li>
</ul>
<h2>v2.15.0</h2>
<ul>
<li>🌟 CPython 3.12 wheels are now built by default - without the
CIBW_PRERELEASE_PYTHONS flag. It's time to build and upload these wheels
to PyPI! This release includes CPython 3.12.0rc1, which is guaranteed to
be ABI compatible with the final release. (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1565">#1565</a>)</li>
<li>✨ Adds musllinux_1_2 support - this allows packagers to build for
musl-based Linux distributions on a more recent Alpine image, and a
newer musl libc. (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1561">#1561</a>)</li>
</ul>
</blockquote>
</details>
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md">pypa/cibuildwheel's
changelog</a>.</em></p>
<blockquote>
<h3>v2.16.1</h3>
<p><em>26 September 2023</em></p>
<ul>
<li>🛠 Updates the prerelease CPython 3.12 version to 3.12.0rc3 (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1625">#1625</a>)</li>
<li>🛠 Only calls <code>linux32</code> in containers when necessary (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1599">#1599</a>)</li>
</ul>
<h3>v2.16.0</h3>
<p><em>18 September 2023</em></p>
<ul>
<li>✨ Add the ability to pass additional flags to a build frontend
through the <a
href="https://cibuildwheel.readthedocs.io/en/stable/options/#build-frontend">CIBW_BUILD_FRONTEND</a>
option (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1588">#1588</a>).</li>
<li>✨ The environment variable SOURCE_DATE_EPOCH is now automatically
passed through to container Linux builds (useful for <a
href="https://reproducible-builds.org/docs/source-date-epoch/">reproducible
builds</a>!) (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1589">#1589</a>)</li>
<li>🛠 Updates the prerelease CPython 3.12 version to 3.12.0rc2 (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1604">#1604</a>)</li>
<li>🐛 Fix <code>requires_python</code> auto-detection from setup.py when
the call to <code>setup()</code> is within an `if <strong>name</strong>
== &quot;<strong>main</strong>&quot; block (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1613">#1613</a>)</li>
<li>🐛 Fix a bug that prevented building Linux wheels in Docker on a
Windows host (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1573">#1573</a>)</li>
<li>🐛 <code>--only</code> can now select prerelease-pythons (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1564">#1564</a>)</li>
<li>📚 Docs &amp; examples updates (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1582">#1582</a>,
<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1593">#1593</a>,
<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1598">#1598</a>,
<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1615">#1615</a>)</li>
</ul>
<h3>v2.15.0</h3>
<p><em>8 August 2023</em></p>
<ul>
<li>🌟 CPython 3.12 wheels are now built by default - without the
CIBW_PRERELEASE_PYTHONS flag. It's time to build and upload these wheels
to PyPI! This release includes CPython 3.12.0rc1, which is guaranteed to
be ABI compatible with the final release. (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1565">#1565</a>)</li>
<li>✨ Adds musllinux_1_2 support - this allows packagers to build for
musl-based Linux distributions on a more recent Alpine image, and a
newer musl libc. (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1561">#1561</a>)</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="https://github.com/pypa/cibuildwheel/commit/7da7df1efc530f07d1945c00934b8cfd34be0d50"><code>7da7df1</code></a>
Bump version: v2.16.1</li>
<li><a
href="https://github.com/pypa/cibuildwheel/commit/9deb1b6794913450fc222b73e2ada1a0eec00487"><code>9deb1b6</code></a>
Merge pull request <a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1625">#1625</a>
from pypa/update-dependencies-pr</li>
<li><a
href="https://github.com/pypa/cibuildwheel/commit/271c5fe6e461766c93e9c45d29923ca93ed751e8"><code>271c5fe</code></a>
[pre-commit.ci] pre-commit autoupdate (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1627">#1627</a>)</li>
<li><a
href="https://github.com/pypa/cibuildwheel/commit/c716cfaeb8bb52556017300e35cbd7044a614804"><code>c716cfa</code></a>
Update dependencies</li>
<li><a
href="https://github.com/pypa/cibuildwheel/commit/099d397aee3ec4bead60ae0c8a554d77b156c86c"><code>099d397</code></a>
Merge pull request <a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1599">#1599</a>
from mayeut/manylinux-entrypoint</li>
<li><a
href="https://github.com/pypa/cibuildwheel/commit/72222654f48f70f792df979f05e0c1dea470ae35"><code>7222265</code></a>
[pre-commit.ci] pre-commit autoupdate (<a
href="https://redirect.github.com/pypa/cibuildwheel/issues/1619">#1619</a>)</li>
<li><a
href="https://github.com/pypa/cibuildwheel/commit/7a8b8012ffe79448b50852f8b7c327292ed61f48"><code>7a8b801</code></a>
clearer simulate_32_bit initialization</li>
<li><a
href="https://github.com/pypa/cibuildwheel/commit/0ccf1dc016d1bb88e118ce6549475e82b21217bd"><code>0ccf1dc</code></a>
remove GHA runner cached docker images</li>
<li><a
href="https://github.com/pypa/cibuildwheel/commit/ba11212a135469b1b3c878756cba85d5258ba9c9"><code>ba11212</code></a>
use fixture in oci_container_test.py to clean-up images after tests</li>
<li><a
href="https://github.com/pypa/cibuildwheel/commit/6d0890e7e04f37bf026d12e72031430f4f85b06c"><code>6d0890e</code></a>
add tests</li>
<li>Additional commits viewable in <a
href="https://github.com/pypa/cibuildwheel/compare/v2.14.1...v2.16.1">compare
view</a></li>
</ul>
</details>
<br />


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---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Hans Dembinski <HDembinski@users.noreply.github.com>
---
 .github/workflows/release.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index 8dbcd328..65500690 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -63,7 +63,7 @@ jobs:
       - if: ${{ matrix.arch == 'aarch64' }}
         uses: docker/setup-qemu-action@v3
 
-      - uses: pypa/cibuildwheel@v2.14.1
+      - uses: pypa/cibuildwheel@v2.16.1
         env:
           CIBW_BUILD: ${{ matrix.py }}-*
           CIBW_ARCHS: ${{ matrix.arch }}