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build(deps): bump the pip-minor-patch-updates group across 2 directories with 6 updates #61

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Bumps the pip-minor-patch-updates group with 2 updates in the / directory: mypy and ruff.
Bumps the pip-minor-patch-updates group with 4 updates in the /src/sample_pytorch_gpu_project/.devcontainer directory: torch, torchvision, mlflow and azureml-mlflow.

Updates mypy from 1.11.2 to 1.13.0

Changelog

Sourced from mypy's changelog.

Mypy Release Notes

Next release

Change to enum membership semantics

As per the updated typing specification for enums, enum members must be left unannotated.

class Pet(Enum):
    CAT = 1  # Member attribute
    DOG = 2  # Member attribute
    WOLF: int = 3  # New error: Enum members must be left unannotated
species: str  # Considered a non-member attribute

In particular, the specification change can result in issues in type stubs (.pyi files), since historically it was common to leave the value absent:

# In a type stub (.pyi file)
class Pet(Enum):
# Change in semantics: previously considered members, now non-member attributes
CAT: int
DOG: int
# Mypy will now issue a warning if it detects this situation in type stubs:
# > Detected enum "Pet" in a type stub with zero members.
# > There is a chance this is due to a recent change in the semantics of enum membership.
# > If so, use `member = value` to mark an enum member, instead of `member: type`

class Pet(Enum):
# As per the specification, you should now do one of the following:
DOG = 1  # Member attribute with value 1 and known type
WOLF = cast(int, ...)  # Member attribute with unknown value but known type
LION = ...  # Member attribute with unknown value and unknown type

Contributed by Terence Honles in PR 17207 and Shantanu Jain in PR 18068.

Mypy 1.13

We’ve just uploaded mypy 1.13 to the Python Package Index (PyPI). Mypy is a static type checker for Python. You can install it as follows:

python3 -m pip install -U mypy

... (truncated)

Commits

Updates ruff from 0.6.8 to 0.7.2

Release notes

Sourced from ruff's releases.

0.7.2

Release Notes

Preview features

  • Fix formatting of single with-item with trailing comment (#14005)
  • [pyupgrade] Add PEP 646 Unpack conversion to * with fix (UP044) (#13988)

Rule changes

  • Regenerate known_stdlibs.rs with stdlibs 2024.10.25 (#13963)
  • [flake8-no-pep420] Skip namespace package enforcement for PEP 723 scripts (INP001) (#13974)

Server

  • Fix server panic when undoing an edit (#14010)

Bug fixes

  • Fix issues in discovering ruff in pip build environments (#13881)
  • [flake8-type-checking] Fix false positive for singledispatchmethod (TCH003) (#13941)
  • [flake8-type-checking] Treat return type of singledispatch as runtime-required (TCH003) (#13957)

Documentation

  • [flake8-simplify] Include caveats of enabling if-else-block-instead-of-if-exp (SIM108) (#14019)

Install ruff 0.7.2

Install prebuilt binaries via shell script

curl --proto '=https' --tlsv1.2 -LsSf https://github.com/astral-sh/ruff/releases/download/0.7.2/ruff-installer.sh | sh

Install prebuilt binaries via powershell script

powershell -ExecutionPolicy ByPass -c "irm https://github.com/astral-sh/ruff/releases/download/0.7.2/ruff-installer.ps1 | iex"

Download ruff 0.7.2

File Platform Checksum
ruff-aarch64-apple-darwin.tar.gz Apple Silicon macOS checksum
ruff-x86_64-apple-darwin.tar.gz Intel macOS checksum
ruff-aarch64-pc-windows-msvc.zip ARM64 Windows checksum
ruff-i686-pc-windows-msvc.zip x86 Windows checksum
ruff-x86_64-pc-windows-msvc.zip x64 Windows checksum

... (truncated)

Changelog

Sourced from ruff's changelog.

0.7.2

Preview features

  • Fix formatting of single with-item with trailing comment (#14005)
  • [pyupgrade] Add PEP 646 Unpack conversion to * with fix (UP044) (#13988)

Rule changes

  • Regenerate known_stdlibs.rs with stdlibs 2024.10.25 (#13963)
  • [flake8-no-pep420] Skip namespace package enforcement for PEP 723 scripts (INP001) (#13974)

Server

  • Fix server panic when undoing an edit (#14010)

Bug fixes

  • Fix issues in discovering ruff in pip build environments (#13881)
  • [flake8-type-checking] Fix false positive for singledispatchmethod (TCH003) (#13941)
  • [flake8-type-checking] Treat return type of singledispatch as runtime-required (TCH003) (#13957)

Documentation

  • [flake8-simplify] Include caveats of enabling if-else-block-instead-of-if-exp (SIM108) (#14019)

0.7.1

Preview features

  • Fix E221 and E222 to flag missing or extra whitespace around == operator (#13890)
  • Formatter: Alternate quotes for strings inside f-strings in preview (#13860)
  • Formatter: Join implicit concatenated strings when they fit on a line (#13663)
  • [pylint] Restrict iteration-over-set to only work on sets of literals (PLC0208) (#13731)

Rule changes

  • [flake8-type-checking] Support auto-quoting when annotations contain quotes (#11811)

Server

  • Avoid indexing the workspace for single-file mode (#13770)

Bug fixes

  • Make ARG002 compatible with EM101 when raising NotImplementedError (#13714)

Other changes

  • Introduce more Docker tags for Ruff (similar to uv) (#13274)

... (truncated)

Commits

Updates torch from 2.4.1 to 2.5.1

Release notes

Sourced from torch's releases.

PyTorch 2.5.1: bug fix release

This release is meant to fix the following regressions:

Besides the regression fixes, the release includes several documentation updates.

See release tracker pytorch/pytorch#132400 for additional information.

PyTorch 2.5.0 Release, SDPA CuDNN backend, Flex Attention

PyTorch 2.5 Release Notes

  • Highlights
  • Backwards Incompatible Change
  • Deprecations
  • New Features
  • Improvements
  • Bug fixes
  • Performance
  • Documentation
  • Developers
  • Security

Highlights

We are excited to announce the release of PyTorch® 2.5! This release features a new CuDNN backend for SDPA, enabling speedups by default for users of SDPA on H100s or newer GPUs. As well, regional compilation of torch.compile offers a way to reduce the cold start up time for torch.compile by allowing users to compile a repeated nn.Module (e.g. a transformer layer in LLM) without recompilations. Finally, TorchInductor CPP backend offers solid performance speedup with numerous enhancements like FP16 support, CPP wrapper, AOT-Inductor mode, and max-autotune mode. This release is composed of 4095 commits from 504 contributors since PyTorch 2.4. We want to sincerely thank our dedicated community for your contributions. As always, we encourage you to try these out and report any issues as we improve 2.5. More information about how to get started with the PyTorch 2-series can be found at our Getting Started page. As well, please check out our new ecosystem projects releases with TorchRec and TorchFix.

Beta Prototype
CuDNN backend for SDPA FlexAttention
torch.compile regional compilation without recompilations Compiled Autograd
TorchDynamo added support for exception handling & MutableMapping types Flight Recorder
TorchInductor CPU backend optimization Max-autotune Support on CPU with GEMM Template
TorchInductor on Windows
FP16 support on CPU path for both eager mode and TorchInductor CPP backend
Autoload Device Extension
Enhanced Intel GPU support

*To see a full list of public feature submissions click here.

BETA FEATURES

[Beta] CuDNN backend for SDPA

The cuDNN "Fused Flash Attention" backend was landed for torch.nn.functional.scaled_dot_product_attention. On NVIDIA H100 GPUs this can provide up to 75% speed-up over FlashAttentionV2. This speedup is enabled by default for all users of SDPA on H100 or newer GPUs.

[Beta] torch.compile regional compilation without recompilations

Regional compilation without recompilations, via torch._dynamo.config.inline_inbuilt_nn_modules which default to True in 2.5+. This option allows users to compile a repeated nn.Module (e.g. a transformer layer in LLM) without recompilations. Compared to compiling the full model, this option can result in smaller compilation latencies with 1%-5% performance degradation compared to full model compilation.

... (truncated)

Commits

Updates torchvision from 0.19.1 to 0.20.1

Release notes

Sourced from torchvision's releases.

Torchvision 0.20 release

Highlights

Encoding / Decoding images

Torchvision is further extending its encoding/decoding capabilities. For this version, we added a WEBP decoder, and a batch JPEG decoder on CUDA GPUs, which can lead to 10X speed-ups over CPU decoding.

We have also improved the UX of our decoding APIs to be more user-friendly. The main entry point is now torchvision.io.decode_image(), and it can take as input either a path (as str or pathlib.Path), or a tensor containing the raw encoded data.

Read more on the docs!

We also added support for HEIC and AVIF decoding, but these are currently only available when building from source. We are working on making those available directly in the upcoming releases. Stay tuned!

Detailed changes

Bug Fixes

[datasets] Update URL of SBDataset train_noval (#8551) [datasets] EuroSAT: fix SSL certificate issues (#8563) [io] Check average_rate availability in video reader (#8548)

New Features

[io] Add batch JPEG GPU decoding (decode_jpeg()) (#8496) [io] Add WEBP image decoder: decode_image(), decode_webp() (#8527, #8612, #8610) [io] Add HEIC and AVIF decoders, only available when building from source (#8597, #8596, #8647, #8613, #8621)

Improvements

[io] Add support for decoding 16bits png (#8524) [io] Allow decoding functions to accept the mode parameter as a string (#8627) [io] Allow decode_image() to support paths (#8624) [io] Automatically send video to CPU in io.write_video (#8537) [datasets] Better progress bar for file downloading (#8556) [datasets] Add Path type annotation for ImageFolder (#8526) [ops] Register nms and roi_align Autocast policy for PyTorch Intel GPU backend (#8541) [transforms] Use Sequence for parameters type checking in transforms.RandomErase (#8615) [transforms] Support v2.functional.gaussian_blur backprop (#8486) [transforms] Expose transforms.v2 utils for writing custom transforms. (#8670) [utils] Fix f-string in color error message (#8639) [packaging] Revamped and improved debuggability of setup.py build (#8535, #8581, #8581, #8582, #8590, #8533, #8528, #8659) [Documentation] Various documentation improvements (#8605, #8611, #8506, #8507, #8539, #8512, #8513, #8583, #8633) [tests] Various tests improvements (#8580, #8553, #8523, #8617, #8518, #8579, #8558, #8617, #8641) [code quality] Various code quality improvements (#8552, #8555, #8516, #8526, #8602, #8615, #8639, #8532) [ci] #8562, #8644, #8592, #8542, #8594, #8530, #8656

... (truncated)

Commits

Updates mlflow from 2.16.2 to 2.17.2

Release notes

Sourced from mlflow's releases.

MLflow 2.17.2 includes several major features and improvements

Features:

Bug fixes:

Documentation updates:

Small bug fixes and documentation updates:

#13569, @​serena-ruan; #13595, @​BenWilson2; #13593, @​mnijhuis-dnb;

MLflow 2.17.1 is a patch release that includes several major features and improvements

Features:

Bug fixes:

Documentation updates:

Small bug fixes and documentation updates:

#13293, #13510, #13501, #13506, #13446, @​harupy; #13341, #13342, @​WeichenXu123; #13396, @​dvorst; #13535, @​chenmoneygithub; #13503, #13469, #13416, @​B-Step62; #13519, #13516, @​serena-ruan; #13504, @​sunishsheth2009; #13508, @​KamilStachera; #13397, @​kriscon-db

MLflow 2.17.0

We are excited to announce the release of MLflow 2.17.0! This release includes several enhancements to extend the

... (truncated)

Changelog

Sourced from mlflow's changelog.

2.17.2 (2024-10-31)

MLflow 2.17.2 includes several major features and improvements

Features:

Bug fixes:

Documentation updates:

Small bug fixes and documentation updates:

#13569, @​serena-ruan; #13595, @​BenWilson2; #13593, @​mnijhuis-dnb;

2.17.1 (2024-10-25)

MLflow 2.17.1 includes several major features and improvements

Features:

Bug fixes:

Documentation updates:

Small bug fixes and documentation updates:

#13293, #13510, #13501, #13506, #13446, @​harupy; #13341, #13342, @​WeichenXu123; #13396, @​dvorst; #13535, @​chenmoneygithub; #13503, #13469, #13416, @​B-Step62; #13519, #13516, @​serena-ruan; #13504, @​sunishsheth2009; #13508, @​KamilStachera; #13397, @​kriscon-db

... (truncated)

Commits

Updates azureml-mlflow from 1.57.0.post1 to 1.58.0.post2

Commits

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@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels Nov 1, 2024
@dependabot dependabot bot force-pushed the dependabot/pip/pip-minor-patch-updates-e0689106b1 branch 2 times, most recently from 49d307c to a648eaa Compare November 3, 2024 05:56
@dependabot
build(deps): bump the pip-minor-patch-updates group across 2 director…
439c438 
…ies with 6 updates

Bumps the pip-minor-patch-updates group with 2 updates in the / directory: [mypy](https://github.com/python/mypy) and [ruff](https://github.com/astral-sh/ruff).
Bumps the pip-minor-patch-updates group with 4 updates in the /src/sample_pytorch_gpu_project/.devcontainer directory: [torch](https://github.com/pytorch/pytorch), [torchvision](https://github.com/pytorch/vision), [mlflow](https://github.com/mlflow/mlflow) and [azureml-mlflow](https://github.com/Azure/MachineLearningNotebooks).


Updates `mypy` from 1.11.2 to 1.13.0
- [Changelog](https://github.com/python/mypy/blob/master/CHANGELOG.md)
- [Commits](python/mypy@v1.11.2...v1.13.0)

Updates `ruff` from 0.6.8 to 0.7.2
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](astral-sh/ruff@0.6.8...0.7.2)

Updates `torch` from 2.4.1 to 2.5.1
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
- [Commits](pytorch/pytorch@v2.4.1...v2.5.1)

Updates `torchvision` from 0.19.1 to 0.20.1
- [Release notes](https://github.com/pytorch/vision/releases)
- [Commits](pytorch/vision@v0.19.1...v0.20.1)

Updates `mlflow` from 2.16.2 to 2.17.2
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.16.2...v2.17.2)

Updates `azureml-mlflow` from 1.57.0.post1 to 1.58.0.post2
- [Release notes](https://github.com/Azure/MachineLearningNotebooks/releases)
- [Commits](https://github.com/Azure/MachineLearningNotebooks/commits)

---
updated-dependencies:
- dependency-name: mypy
  dependency-type: direct:development
  update-type: version-update:semver-minor
  dependency-group: pip-minor-patch-updates
- dependency-name: ruff
  dependency-type: direct:development
  update-type: version-update:semver-minor
  dependency-group: pip-minor-patch-updates
- dependency-name: torch
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: pip-minor-patch-updates
- dependency-name: torchvision
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: pip-minor-patch-updates
- dependency-name: mlflow
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: pip-minor-patch-updates
- dependency-name: azureml-mlflow
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: pip-minor-patch-updates
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot force-pushed the dependabot/pip/pip-minor-patch-updates-e0689106b1 branch from a648eaa to 439c438 Compare November 3, 2024 07:11
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dependabot bot commented on behalf of github Dec 1, 2024

Looks like these dependencies are updatable in another way, so this is no longer needed.

@dependabot dependabot bot closed this Dec 1, 2024
@dependabot dependabot bot deleted the dependabot/pip/pip-minor-patch-updates-e0689106b1 branch December 1, 2024 23:42
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