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Updates the requirements on qiskit, qiskit-ibm-runtime, qiskit-machine-learning, azure-quantum, azure-identity, torch, torchvision, scikit-learn, numpy, pandas, matplotlib, plotly, jupyterlab, ipykernel, ipywidgets, python-dotenv, tqdm, pytest-mock, black, flake8 and mypy to permit the latest version.
Updates qiskit to 2.5.2

Release notes

Sourced from qiskit's releases.

Qiskit 2.5.2

Changelog

Fixed

  • Sum VF2Layout average errors in a deterministic order (#16732) (#16761)
  • Fix add/sub optimizations including the same symbols (backport #16752) (#16759)
  • Reimplement SymbolExpr::eval to be iterative (backport #16756) (#16758)
  • dagcircuit: transfer DAG-level variables in substitute_node_with_dag (#15542) (#16744)
  • Fix memory leak in Suzuki-Trotter synthesis (#16687) (#16739)
  • Fix OptimizeCliffordT producing non-unitarily-equivalent output when basis excludes sx/sxdg (#16729) (#16735)
  • Parameter expression bugfixes (backport #16283) (#16714)
  • Update to rsgridsynth 0.2.2 (backport #16685) (#16711)
  • Fix potential panic in DAGCircuit.depth by bumping rustworkx-core to 0.18.1 (#16686) (#16715)
  • Preserve StatePreparation width in inverse (#16431) (#16681)
  • Fix circuit drawing layer overlaps inside of ControlFlowOps (#16639) (#16659)
  • Fix non-determinism in DAGCircuit::remove_qubits (#16656) (#16658)
Commits

Updates qiskit-ibm-runtime to 0.50.0

Release notes

Sourced from qiskit-ibm-runtime's releases.

Qiskit Ibm Runtime 0.50.0

Changelog

Deprecated

  • Add deprecation warnings to legacy primitives (#3362)
  • Move max_execution_time to top-level options (#3361)
  • Revise QuantumProgram-related imports and deprecations (#3290)

Added

  • Add deprecation warnings to legacy primitives (#3362)
  • Add backend to client-side primitives and mode property to all primitives (#3333)
  • Support dry-run mode when executing a primitive (#3314)
  • Take Executor local mode out of experimental options (#3288)
  • Revise QuantumProgram-related imports and deprecations (#3290)
  • Version bump ibm-quantum-schemas to 0.11.20260824 (#3276)
  • Add to_pauli_lindblad_maps to NoiseLearnerV3Results (#3257)
  • Introduce XSlowGate (#3224)
  • Add MeasureReset instruction (#3199)

Changed

  • Import QuantumProgram and related classes from Samplomatic (#3206)

Removed

  • Remove legacy package extras (#3286)

Fixed

  • Use proxies and verify during account.resolve_crn (#3353)
  • Increase minimum number of noise factors for the fallback extrapolator (#3321)
  • Avoid caching calibration specific backend configurations (#3287)
  • Correctly retrieve jobs from retired backends (#3020)
Commits

Updates qiskit-machine-learning to 0.9.1

Release notes

Sourced from qiskit-machine-learning's releases.

v0.9.1

Qiskit Machine Learning 0.9.1

Qiskit Machine Learning 0.9.1 includes new regression-oriented kernel loss functions, improvements to QNN behavior and numerical robustness, a new quantum dataset generator, compatibility fixes, and updates to development and CI infrastructure.

Highlights

  • Added regression-based kernel loss functions, including SVRLoss and MSRLoss, together with convenient string aliases.
  • Added a Phase of Matter quantum dataset generator.
  • Fixed SamplerQNN._postprocess handling for transpiled circuit layouts.
  • Fixed numerical issues in EffectiveDimension Fisher information calculations for non-positive outputs.
  • Improved support for multidimensional sparse COO data.
  • Deprecated automatic qubit alignment.
  • Updated typing, linting, formatting, security, and CI tooling.

What's Changed

New Contributors

... (truncated)

Commits
  • c97b5ed Set version to 0.9.1
  • 3bdcce7 Fix: Types errors with new version of mypy (#1063)
  • 8609b0d Bump actions/setup-python from 6 to 7 (#1052)
  • c6ae27d Removed unnecessary warnings to make QNNs consistent with other algorithms. (...
  • b651c7d Added AI policy and instructions for agents. (Issue #1057) (#1058)
  • cfcdb65 Bump coverallsapp/github-action from 2.3.7 to 2.3.8 (#1053)
  • 5b5a221 Fix CI by adding explicit casts to scalars coming from multidimensional COO (...
  • 94c12da Bump actions/checkout from 6 to 7 (#1049)
  • 725c7c8 Add Phase of Matter quantum dataset generator (#1044)
  • f683284 Fix SamplerQNN._postprocess to handle transpiled circuit layouts (#1041)
  • Additional commits viewable in compare view

Updates azure-quantum to 3.13.0

Release notes

Sourced from azure-quantum's releases.

azure-quantum_v3.13.0

What's Changed

New Contributors

Full Changelog: microsoft/azure-quantum-python@azure-quantum_v3.12.0...azure-quantum_v3.13.0

Commits
  • 39fde17 Pin cryptography to 46.0.3 (#775)
  • 959eee6 Fix job attachment 401s for submitted jobs (#773)
  • 91d124f Regenerate client from rest api (#772)
  • e7c9490 Update network isolation policy (#770)
  • 4640862 Add Job.list_attachments() to enumerate a job's output container blobs (#768)
  • 82cced9 Fix typo in signal-processing.ipynb (#769)
  • 713004b Allow version to optionally be manually set during release (#767)
  • b25df2c Add update job operation to support updating name, priority and tags (#764)
  • e1689fd Support full-result format in Pasqal Result (#762)
  • cae08e6 Query Azure Artifacts Feed for Existing Version when Determining Built Versio...
  • Additional commits viewable in compare view

Updates azure-identity to 1.26.0

Release notes

Sourced from azure-identity's releases.

azure-identity_1.26.0

1.26.0 (2026-09-30)

Features Added

  • ManagedIdentityCredential now supports user-assigned managed identities on Azure Arc-enabled servers. An identity can be selected by client ID, object ID, or resource ID. Token responses that do not confirm the requested identity are rejected. (#48967)

Bugs Fixed

  • Fixed synchronous Service Fabric managed identity authentication with MSAL 1.39.0 and later. Service Fabric now uses the session from an Azure Core RequestsTransport. (#48967)
  • Fixed an issue where AuthorizationCodeCredential and the asynchronous OnBehalfOfCredential could return a cached token for another account when multiple credentials shared a token cache. (#49001)

Other Changes

  • Added RequestIdPolicy to the default pipeline policies to ensure a unique x-ms-client-request-id header is sent with each request. (#46070)
  • CertificateCredential now passes the PEM private key to MSAL as a str rather than bytes, matching MSAL's documented client_credential contract. (#46801)
  • Bumped the minimum dependency on msal to >=1.39.0.
Commits
  • 30d8bb9 [identity] prepare azure-identity 1.26.0 release (#49290)
  • c7148b7 [identity] Enable user-assigned managed identity for AzureArcCredential (#48967)
  • c5b1f4f [Identity] Fix identity cache issue (#49001)
  • 9d085c1 [AutoPR azure-mgmt-compute-bulkaction]-generated-from-SDK Generation - Python...
  • efc412d [TA] fix release error (#49261)
  • 3d9b8b3 Prepare Responses 2.3.0b2 release (#49281)
  • 8e49d15 [AutoPR azure-mgmt-resiliencemanagement]-generated-from-SDK Generation - Pyth...
  • ef68c78 Preserve canonical agent reference in response snapshots (#49256)
  • 3754db9 Configurations: 'specification/applink/AppLink.Management/tspconfig.yaml', a...
  • 0929352 [Mgmt] Make review drafts and incomplete outcomes reliable (#49275)
  • Additional commits viewable in compare view

Updates torch to 2.14.1

Release notes

Sourced from torch's releases.

PyTorch 2.14.1 Release

This release is meant to fix the following regressions and silent correctness issues:

Silent correctness fixes

  • Fix incorrect torch.linalg.lstsq solutions on MPS for complex batched underdetermined systems (#196113), fixed by #196128
  • Fix non-orthogonal U and inaccurate small singular values from torch.linalg.svd on MPS for rank-deficient and ill-conditioned inputs (#196112), fixed by #196139 and #199063
  • Update the CUDA 13.2 Linux binaries to CUDA 13.2.2 (#196351). This NVIDIA update resolves two critical issues that could produce incorrect results (CUDA 13.2.2 release notes):
    • cuBLAS: cublasLtMatmul() could ignore tensor-wide scaling for NVFP4 matrix multiplications (introduced in CUDA 13.2 Update 1)
    • Compiler: failed thread reconvergence could leave stale or corrupted register values in kernels with nested thread divergence (present since CUDA 12.8)

Regression fixes

  • Fix torch.linalg.svd, torch.linalg.svdvals and torch.linalg.lstsq failing on MPS with a Metal pipeline-state error for inputs above 8192 elements (#195937), fixed by #195949 and #195950
  • Fix internal assert in torch.svd(out=) on MPS for complex inputs (#195822), fixed by #195872
Changelog

Sourced from torch's changelog.

Releasing PyTorch

Release Compatibility Matrix

Following is the Release Compatibility Matrix for PyTorch releases:

... (truncated)

Commits
  • 5c48869 [MPS] Fix Jacobi SVD convergence for small columns (#199086)
  • 35223a2 [release/2.14] Run the release runner-group reconcile in pytorch/pytorch (#19...
  • 41ffbc4 [release-only] Update version to 2.14.1 (#198661)
  • e8f0c01 [release/2.14] [CD] Update to CUDA 13.2.2 for Linux binaries (#198644)
  • 911665d [MPS] Cherry-pick native SVD fixes into release/2.14 (#198394)
  • 2b3ec34 [release/2.14] Import SDPAParams in test_transformers to fix lint (#194970)
  • 08187d9 [cuDNN] Add guards for cuDNN SDPA decode (#194963)
  • 8ceea97 Pin cython < 3.3.0 for the Windows Triton wheel build (#194931)
  • 99ecebc [Cherry-pick][release/2.14] [inductor] Fix loop-local load CSE lifetime (#194...
  • ec283a7 Bump the Python 3.15 numpy pin to 2.5.2 (#194821)
  • Additional commits viewable in compare view

Updates torchvision to 0.29.1

Release notes

Sourced from torchvision's releases.

TorchVision 0.29.1 Release

This is a patch release, which is compatible with PyTorch 2.14.1. There are no new features added.

Packaging

  • Relax the PyTorch requirement from torch==2.14.0 to torch>=2.14. TorchVision is now ABI stable with respect to PyTorch 2.14, so it no longer pins an exact PyTorch version (#9683, cherry-pick of #9680)
Commits
  • 1f1a920 Set the pin to torch>=2.14 (#9680) (#9683)
  • 1b4390d [release/0.29] Build against the release/2.14 test-infra branch (#9682)
  • 0bb1ccf Update version to 0.29.1 (#9678)
  • fc73f5a Merge branch 'release/0.29' of github.com:pytorch/vision into release/0.29
  • f9b2669 [Cherry-pick for 0.29] (#9634)
  • e1b5802 Revert "Update version.txt for 0.30.0 (#9607)"
  • 2757376 Merge remote-tracking branch 'origin' into release/0.29
  • 9e21b88 Consolidate CUDA helpers and remove the legacy _C extension in place of Stabl...
  • 541c083 Port deform_conv2d (CUDA) to stable ABI. (#9626)
  • 2f411e7 Port ps_roi_pool (CUDA) to stable ABI. (#9623)
  • Additional commits viewable in compare view

Updates scikit-learn to 1.9.1

Release notes

Sourced from scikit-learn's releases.

Scikit-learn 1.9.1

We're happy to announce the 1.9.1 release.

This release contains a few bug fixes and is the first version supporting Python 3.15.

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v1.9.html#version-1-9-1

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds can be installed using:

conda install -c conda-forge scikit-learn

Thanks to everyone who contributed to this release !

Commits
  • 866c0f5 generate changelog
  • 12f135f update upper bounds
  • 43ff2f2 bump version
  • b851524 DOC Mark dev index as orphan (#34916)
  • 01d56d4 DOC Fix wikipedia principal eigenvector example references (#34915)
  • b86a1e2 🔒 🤖 CI Update lock files for array-api CI build(s) 🔒 🤖 ...
  • d282698 🔒 🤖 CI Update lock files for main CI build(s) 🔒 🤖 (#34897)
  • eb34279 🔒 🤖 CI Update lock files for free-threaded CI build(s) 🔒 :rob...
  • 7581303 FIX: Fix QuantileTransformer(ignore_implicit_zeros=True) sub-sampling behav...
  • ac47f4d FIX: avoid EfficiencyWarning in OPTICS with metric='precomputed' (#34692)
  • Additional commits viewable in compare view

Updates numpy to 2.5.3

Release notes

Sourced from numpy's releases.

v2.5.3 (Sep 6, 2026)

NumPy 2.5.3 Release Notes

The NumPy 2.5.3 is a patch release that fixes bugs discovered after the 2.5.2 release. Apart from the usual bug and maintenance work, there are a number of StringDType related fixes for problems discovered during the ongoing string work in the main branch.

This release supports Python versions 3.12-3.15

Changes

  • Casting a fixed-width byte string array (np.bytes_) to StringDType now raises TypeError when the bytes are not valid UTF-8. Previously the invalid bytes were stored as-is and later caused undefined behavior in string operations.

    (gh-32296)

  • MaskedArray._fill_value would become stale when ufuncs that change dtype left the result holding a fill_value typed for the old dtype. The mismatch was silent until something later called _check_fill_value, such as .view(), and then a TypeError would be raised. Now, when the copied fill_value is no longer valid for the new dtype, fall back to the default fill_value for that dtype instead of propagating the stale value. This may raise a ComplexWarning if the fill_value is complex and the new dtype is real.

    (gh-32423)

Contributors

A total of 9 people contributed to this release. People with a "+" by their names contributed a patch for the first time.

  • Charles Harris
  • Iason Krommydas
  • James Davies +
  • Joren Hammudoglu
  • Maanas Arora
  • Matti Picus
  • Nathan Goldbaum
  • Shikhar Goel +
  • Yeonho Kim +

Pull requests merged

A total of 27 pull requests were merged for this release.

  • #32235: MAINT: Prepare 2.5.x for further development

... (truncated)

Changelog

Sourced from numpy's changelog.

This is a walkthrough of the NumPy 2.4.0 release on Linux, which will be the first feature release using the numpy/numpy-release <https://github.com/numpy/numpy-release>__ repository.

The commands can be copied into the command line, but be sure to replace 2.4.0 with the correct version. This should be read together with the :ref:general release guide <prepare_release>.

Facility preparation

Before beginning to make a release, use the requirements/*_requirements.txt files to ensure that you have the needed software. Most software can be installed with pip, but some will require apt-get, dnf, or whatever your system uses for software. You will also need a GitHub personal access token (PAT) to push the documentation. There are a few ways to streamline things:

  • Git can be set up to use a keyring to store your GitHub personal access token. Search online for the details.

Prior to release

Add/drop Python versions

When adding or dropping Python versions, multiple config and CI files need to be edited in addition to changing the minimum version in pyproject.toml. Make these changes in an ordinary PR against main and backport if necessary. We currently release wheels for new Python versions after the first Python RC once manylinux and cibuildwheel support that new Python version.

Backport pull requests

Changes that have been marked for this release must be backported to the maintenance/2.4.x branch.

Update 2.4.0 milestones

Look at the issues/prs with 2.4.0 milestones and either push them off to a later version, or maybe remove the milestone. You may need to add a milestone.

Check the numpy-release repo

... (truncated)

Commits
  • dd88c0c Merge pull request #32511 from charris/prepare-2.5.3
  • edcac6a REL: Prepare for the NumPy 2.5.3 release
  • fd4d908 Merge pull request #32509 from charris/backport-32496
  • 65bb1da BUG: fix crash in ufunc.resolve_dtypes with a Python scalar type (#32496)
  • 294956e Merge pull request #32506 from charris/backport-32503
  • 26428d9 DOC: fix scipy docs links in intersphinx mapping (#32507)
  • 5fab1cb DOC: use static scipy doc site for intershpinx (#32503)
  • 7beed2f Merge pull request #32481 from ngoldbaum/stringdtype-backport
  • 8972f70 Merge pull request #32478 from charris/backport-32466
  • ab1b589 Merge pull request #32477 from charris/backport-32423
  • Additional commits viewable in compare view

Updates pandas to 3.0.6

Release notes

Sourced from pandas's releases.

pandas 3.0.6

We are pleased to announce the release of pandas 3.0.6. This is a patch release in the 3.0.x series and includes some regression fixes and bug fixes. We recommend that all users of the 3.0.x series upgrade to this version. This is also the first release to support Python 3.15.

See the full whatsnew for a list of all the changes.

Pandas 3.0 supports Python 3.11 and higher. The release can be installed from PyPI:

python -m pip install --upgrade pandas==3.0.*

Or from conda-forge

conda install -c conda-forge pandas=3.0

Please report any issues with the release on the pandas issue tracker.

Thanks to all the contributors who made this release possible.

Commits
  • 2905718 RLS: 3.0.6
  • 3188ced [backport 3.0.x] BUG: read_csv(sep=None) raised TypeError instead of falling...
  • f097905 DOC: cleanup 3.0.6 whatsnew + mention Python 3.15 support (#68965) (#68969)
  • 4f68223 [backport 3.0.x] BUG: fix setting with bool column mask into 1-column DataFra...
  • e3df0e8 [backport 3.0.x] BUG: full-slice setitem into a pyarrow-backed array shared m...
  • b7735f6 Backport PR #66117 on branch 3.0.x (BUG: interpolate leaving NAs unfilled for...
  • bca0b77 [backport 3.0.x] BUG: read_csv leaked the string-intern table when a column f...
  • bca1e5d [backport 3.0.x] BUG: prevent external mutation of RangeIndex._data (CoW) (#6...
  • c95b42c [3.0.x] CI: skip cython-lint on pre-commit.ci (#68910)
  • 9cbd884 [backport 3.0.x] Backport of some already merged regression fixes (#68447)
  • Additional commits viewable in compare view

Updates matplotlib to 3.11.2

Release notes

Sourced from matplotlib's releases.

REL: v3.11.2

This is the second bugfix release of the 3.11.x series.

This release contains several bug-fixes and adjustments:

  • Speed up RGBA-stage image resampling
  • Fix hexbin clipping in PDF output
  • Fix \text with internal braces
  • Fix some crashes and make some checks more robust to unlikely cases
  • Fix frame skew when saving GIF animations with PillowWriter
  • Fix HiDPI handling in Qt toolbar and WebAgg embeddings
  • Fix ResizeEvent handling for TextBox
  • Fix bug with PGF hatch linewidth and color
  • Fix a bug with drawing an empty Collection
  • Fix incorrect glyphs in Cairo backends
  • Improve build system to prevent conflicts between wheels and system libraries
Commits
  • d3ca917 REL: v3.11.2
  • b76fea9 DOC: Set current version to 3.11.2
  • 39c7f06 DOC: Prepare GitHub stats for 3.11.2
  • 5dd13e3 Merge branch 'v3.11.1-doc' into release-3.11.2
  • aa484be Merge branch 'v3.11.0-doc' into v3.11.1-doc

@dependabot
deps(lora-quantum-ai): bump the lora-quantum-ai-deps group across 1 d…
f6f5810 
…irectory with 21 updates

Updates the requirements on [qiskit](https://github.com/Qiskit/qiskit), [qiskit-ibm-runtime](https://github.com/Qiskit/qiskit-ibm-runtime), [qiskit-machine-learning](https://github.com/qiskit-community/qiskit-machine-learning), [azure-quantum](https://github.com/microsoft/azure-quantum-python), [azure-identity](https://github.com/Azure/azure-sdk-for-python), [torch](https://github.com/pytorch/pytorch), [torchvision](https://github.com/pytorch/vision), [scikit-learn](https://github.com/scikit-learn/scikit-learn), [numpy](https://github.com/numpy/numpy), [pandas](https://github.com/pandas-dev/pandas), [matplotlib](https://github.com/matplotlib/matplotlib), [plotly](https://github.com/plotly/plotly.py), [jupyterlab](https://github.com/jupyterlab/jupyterlab), [ipykernel](https://github.com/ipython/ipykernel), [ipywidgets](https://github.com/jupyter-widgets/ipywidgets), [python-dotenv](https://github.com/theskumar/python-dotenv), [tqdm](https://github.com/tqdm/tqdm), [pytest-mock](https://github.com/pytest-dev/pytest-mock), [black](https://github.com/psf/black), [flake8](https://github.com/pycqa/flake8) and [mypy](https://github.com/python/mypy) to permit the latest version.

Updates `qiskit` to 2.5.2
- [Release notes](https://github.com/Qiskit/qiskit/releases)
- [Changelog](https://github.com/Qiskit/qiskit/blob/main/docs/release_notes.rst)
- [Commits](Qiskit/qiskit@2.5.0...2.5.2)

Updates `qiskit-ibm-runtime` to 0.50.0
- [Release notes](https://github.com/Qiskit/qiskit-ibm-runtime/releases)
- [Commits](Qiskit/qiskit-ibm-runtime@0.47.0...0.50.0)

Updates `qiskit-machine-learning` to 0.9.1
- [Release notes](https://github.com/qiskit-community/qiskit-machine-learning/releases)
- [Commits](qiskit-community/qiskit-machine-learning@0.9.0...0.9.1)

Updates `azure-quantum` to 3.13.0
- [Release notes](https://github.com/microsoft/azure-quantum-python/releases)
- [Commits](microsoft/azure-quantum-python@azure-quantum_v3.10.0...azure-quantum_v3.13.0)

Updates `azure-identity` to 1.26.0
- [Release notes](https://github.com/Azure/azure-sdk-for-python/releases)
- [Commits](Azure/azure-sdk-for-python@azure-identity_1.25.3...azure-identity_1.26.0)

Updates `torch` to 2.14.1
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
- [Commits](pytorch/pytorch@ciflow/torchtitan/113258...v2.14.1)

Updates `torchvision` to 0.29.1
- [Release notes](https://github.com/pytorch/vision/releases)
- [Commits](pytorch/vision@v0.28.0...v0.29.1)

Updates `scikit-learn` to 1.9.1
- [Release notes](https://github.com/scikit-learn/scikit-learn/releases)
- [Commits](scikit-learn/scikit-learn@1.9.0...1.9.1)

Updates `numpy` to 2.5.3
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/RELEASE_WALKTHROUGH.rst)
- [Commits](numpy/numpy@v2.5.1...v2.5.3)

Updates `pandas` to 3.0.6
- [Release notes](https://github.com/pandas-dev/pandas/releases)
- [Commits](pandas-dev/pandas@v3.0.4...v3.0.6)

Updates `matplotlib` to 3.11.2
- [Release notes](https://github.com/matplotlib/matplotlib/releases)
- [Commits](matplotlib/matplotlib@v3.11.0...v3.11.2)

Updates `plotly` to 7.1.0
- [Release notes](https://github.com/plotly/plotly.py/releases)
- [Changelog](https://github.com/plotly/plotly.py/blob/main/CHANGELOG.md)
- [Commits](plotly/plotly.py@v6.9.0...v7.1.0)

Updates `jupyterlab` to 4.6.4
- [Release notes](https://github.com/jupyterlab/jupyterlab/releases)
- [Changelog](https://github.com/jupyterlab/jupyterlab/blob/main/RELEASE.md)
- [Commits](https://github.com/jupyterlab/jupyterlab/compare/@jupyterlab/lsp@4.6.1...@jupyterlab/lsp@4.6.4)

Updates `ipykernel` to 7.4.0
- [Release notes](https://github.com/ipython/ipykernel/releases)
- [Changelog](https://github.com/ipython/ipykernel/blob/main/CHANGELOG.md)
- [Commits](ipython/ipykernel@v7.3.0...v7.4.0)

Updates `ipywidgets` to 8.1.9
- [Release notes](https://github.com/jupyter-widgets/ipywidgets/releases)
- [Commits](jupyter-widgets/ipywidgets@8.1.8...8.1.9)

Updates `python-dotenv` to 1.2.4
- [Release notes](https://github.com/theskumar/python-dotenv/releases)
- [Changelog](https://github.com/theskumar/python-dotenv/blob/main/CHANGELOG.md)
- [Commits](theskumar/python-dotenv@v1.2.2...v1.2.4)

Updates `tqdm` to 4.70.1
- [Release notes](https://github.com/tqdm/tqdm/releases)
- [Commits](tqdm/tqdm@v4.68.4...v4.70.1)

Updates `pytest-mock` to 3.16.0
- [Release notes](https://github.com/pytest-dev/pytest-mock/releases)
- [Changelog](https://github.com/pytest-dev/pytest-mock/blob/main/CHANGELOG.rst)
- [Commits](pytest-dev/pytest-mock@v3.15.1...v3.16.0)

Updates `black` to 26.10.0
- [Release notes](https://github.com/psf/black/releases)
- [Changelog](https://github.com/psf/black/blob/main/CHANGES.md)
- [Commits](psf/black@26.5.1...26.10.0)

Updates `flake8` to 7.4.1
- [Commits](PyCQA/flake8@7.3.0...7.4.1)

Updates `mypy` to 2.4.0
- [Changelog](https://github.com/python/mypy/blob/master/CHANGELOG.md)
- [Commits](python/mypy@v2.2.0...v2.4.0)

---
updated-dependencies:
- dependency-name: qiskit
  dependency-version: 2.5.2
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: qiskit-ibm-runtime
  dependency-version: 0.50.0
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: qiskit-machine-learning
  dependency-version: 0.9.1
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: azure-quantum
  dependency-version: 3.13.0
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: azure-identity
  dependency-version: 1.26.0
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: torch
  dependency-version: 2.14.1
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: torchvision
  dependency-version: 0.29.1
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: scikit-learn
  dependency-version: 1.9.1
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: numpy
  dependency-version: 2.5.3
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: pandas
  dependency-version: 3.0.6
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: matplotlib
  dependency-version: 3.11.2
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: plotly
  dependency-version: 7.1.0
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: jupyterlab
  dependency-version: 4.6.4
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: ipykernel
  dependency-version: 7.4.0
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: ipywidgets
  dependency-version: 8.1.9
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: python-dotenv
  dependency-version: 1.2.4
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: tqdm
  dependency-version: 4.70.1
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: pytest-mock
  dependency-version: 3.16.0
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: black
  dependency-version: 26.10.0
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: flake8
  dependency-version: 7.4.1
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
- dependency-name: mypy
  dependency-version: 2.4.0
  dependency-type: direct:production
  dependency-group: lora-quantum-ai-deps
...

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dependabot Bot requested a review from Bryan-Roe as a code owner October 8, 2026 04:19

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