Bump the dependabot group with 3 updates

[dependabot]

Bumps the dependabot group with 3 updates: pyvisa, pygments and tensorflow.

Updates pyvisa from 1.13.0 to 1.14.0

Commits

• 04102ee cut release 1.14.0
• 1f4fa8c update gitignore
• fc1cb89 Merge pull request #780 from pyvisa/vicp-rname
• 1034c72 rname: fix VICP resource name normalization
• a9507e5 Merge pull request #774 from dougthor42/773-fix-custom-sim-file
• 9a3056c Add support for custom simulated file backends in shell
• 088f591 Merge pull request #776 from pyvisa/mypy-fixes
• 9d1f006 fix mypy issues
• 9763240 remove conditional installation of importlib-metadata since 3.7 is not suppor...
• 2220630 Merge pull request #770 from pyvisa/dependabot/github_actions/actions/checkout-4
• Additional commits viewable in compare view

Updates pygments from 2.16.1 to 2.17.1

Release notes

Sourced from pygments's releases.

2.17.1

• Updated lexers:

  • TOML: Fix bug making lexing of single-quoted strings too eager

2.17.0

• New lexers:

  • JSX (#2524, #709)
  • Kusto (#2552)
  • ldaprc (#2532)
  • LDIF (#2489)
  • PRQL (#2507, #2523, #2559)
  • Visual Prolog and Visual Prolog Grammar (#2480)
  • Vyper (#2531, #2579)

• Updated lexers:

  • Cypher: fix comment matching, add missing keywords (#2504)
  • Fortran: add elseif keyword (#2528)
  • Lean: make it available as lean3, in preparation for a possible switch to lean highlighting as Lean 4 (#2546)
  • JSON: add MIME types and file extensions for several line-delimited JSON formats (#2490)
  • Nix: many improvements (#2551, #1800)
  • OCaml: Add and keyword, remove value from keywords (#2521)
  • Python: add starlark and bazel aliases (#2517, #2516)
  • Snowball: Treat len like size (#2508)
  • Spice: add panic keyword and -> operator (#2510)
  • squid.conf: fix catastrophic backtracking (#2583)
  • TOML: rewritten, with many fixes (#2576)
  • Turtle: support blank nodes (#2581)
  • Wikitext: fix erroneous highlighting of LanguageConverter markup (#2493), add missing variant languages (#2494)
  • CMake: support [=[ bracketed arguments ]=] (#2549)

• Fix ctags support and tests (#2487)

• Include Lexer.add_filter in the documentation (#2519)

• Add a Lean3Lexer alias (#2546)

• The pygments.styles module contains a new STYLES variable with a dictionary of built-in styles. The old STYLE_MAP variable, which uses a different format, is kept for backwards compatibility.

• On Windows, add a new installation extra (windows-terminal) which pulls in dependencies for colored console output. See :doc:cmdline for more details. (#2505)

• Support more file types in autopygmentize script (#2513)

• Change color of numbers in rrt style (#2526)

• Fix error when trying to look up plugin formatters by file extension of the output format (#2563)

• Use Hatchling as a build backend instead of setuptools. This change is transparent to most users. Distribution packagers who build without build isolation need to add hatchling as a build dependency and remove setuptools. People downloading source distributions and wheels from PyPI directly should note that they now have pygments in their file names instead of Pygments. (#2573)

• Improve the test framework to also check for lost tokens when processing the snippets and example files (#2582.)

• Improve the Dracula style definition to make it easier to maintain (#2575)

Changelog

Sourced from pygments's changelog.

Version 2.17.1

(released November 19, 2023)

• Updated lexers:

  • TOML: Fix bug making lexing of single-quoted strings too eager

Version 2.17.0

(released November 18, 2023)

• New lexers:

  • JSX (#2524, #709)
  • Kusto (#2552)
  • ldaprc (#2532)
  • LDIF (#2489)
  • PRQL (#2507, #2523, #2559)
  • Visual Prolog and Visual Prolog Grammar (#2480)
  • Vyper (#2531, #2579)

• Updated lexers:

  • Cypher: fix comment matching, add missing keywords (#2504)
  • Fortran: add elseif keyword (#2528)
  • Lean: make it available as lean3, in preparation for a possible switch to lean highlighting as Lean 4 (#2546)
  • JSON: add MIME types and file extensions for several line-delimited JSON formats (#2490)
  • Nix: many improvements (#2551, #1800)
  • OCaml: Add and keyword, remove value from keywords (#2521)
  • Python: add starlark and bazel aliases (#2517, #2516)
  • Snowball: Treat len like size (#2508)
  • Spice: add panic keyword and -> operator (#2510)
  • squid.conf: fix catastrophic backtracking (#2583)
  • TOML: rewritten, with many fixes (#2576)
  • Turtle: support blank nodes (#2581)
  • Wikitext: fix erroneous highlighting of LanguageConverter markup (#2493), add missing variant languages (#2494)
  • CMake: support [=[ bracketed arguments ]=] (#2549)

• Fix ctags support and tests (#2487)

• Include Lexer.add_filter in the documentation (#2519)

• Add a Lean3Lexer alias (#2546)

• The pygments.styles module contains a new STYLES variable with a dictionary of built-in styles. The old STYLE_MAP variable, which uses a different format, is kept for backwards compatibility.

• On Windows, add a new installation extra (windows-terminal) which pulls in dependencies for colored console output. See :doc:cmdline for more details.

... (truncated)

Commits

• f5eb039 Prepare 2.17.1 hotfix release.
• 0c66899 Update CHANGES
• 220a2a9 TOML: fix bug with eager literal strings
• 5cf7389 Another formatting fix in CHANGES.
• 5874c34 Fix code formatting in the CHANGES file.
• 49090a3 Prepare for next release.
• 26e29a6 Bump version number.
• a7d537b Use 3.12 final release in CI.
• 89ea036 Prepare for 2.17 release.
• 333e5b9 Update CHANGES for the next release.
• Additional commits viewable in compare view

Updates tensorflow from 2.14.0 to 2.15.0

Release notes

Sourced from tensorflow's releases.

TensorFlow 2.15.0

Release 2.15.0

TensorFlow

Breaking Changes

• tf.types.experimental.GenericFunction has been renamed to tf.types.experimental.PolymorphicFunction.

Major Features and Improvements

• oneDNN CPU performance optimizations Windows x64 & x86.

  • Windows x64 & x86 packages:
    • oneDNN optimizations are enabled by default on X86 CPUs
  • To explicitly enable or disable oneDNN optimizations, set the environment variable TF_ENABLE_ONEDNN_OPTS to 1 (enable) or 0 (disable) before running TensorFlow. To fall back to default settings, unset the environment variable.
  • oneDNN optimizations can yield slightly different numerical results compared to when oneDNN optimizations are disabled due to floating-point round-off errors from different computation approaches and orders.
  • To verify if oneDNN optimizations are on, look for a message with "oneDNN custom operations are on" in the log. If the exact phrase is not there, it means they are off.

• Making the tf.function type system fully available:

  • tf.types.experimental.TraceType now allows custom tf.function inputs to declare Tensor decomposition and type casting support.
  • Introducing tf.types.experimental.FunctionType as the comprehensive representation of the signature of tf.function callables. It can be accessed through the function_type property of tf.functions and ConcreteFunctions. See the tf.types.experimental.FunctionType documentation for more details.

• Introducing tf.types.experimental.AtomicFunction as the fastest way to perform TF computations in Python.

  • Can be accessed through inference_fn property of ConcreteFunctions
  • Does not support gradients.
  • See tf.types.experimental.AtomicFunction documentation for how to call and use it.

• tf.data:

  • Moved option warm_start from tf.data.experimental.OptimizationOptions to tf.data.Options.

• tf.lite:

  • sub_op and mul_op support broadcasting up to 6 dimensions.

  • The tflite::SignatureRunner class, which provides support for named parameters and for multiple named computations within a single TF Lite model, is no longer considered experimental. Likewise for the following signature-related methods of tflite::Interpreter:

    • tflite::Interpreter::GetSignatureRunner
    • tflite::Interpreter::signature_keys
    • tflite::Interpreter::signature_inputs
    • tflite::Interpreter::signature_outputs
    • tflite::Interpreter::input_tensor_by_signature
    • tflite::Interpreter::output_tensor_by_signature

  • Similarly, the following signature runner functions in the TF Lite C API are no longer considered experimental:

... (truncated)

Changelog

Sourced from tensorflow's changelog.

Release 2.15.0

TensorFlow

Breaking Changes

• tf.types.experimental.GenericFunction has been renamed to tf.types.experimental.PolymorphicFunction.

Known Caveats

Major Features and Improvements

• oneDNN CPU performance optimizations Windows x64 & x86.

  • Windows x64 & x86 packages:
    • oneDNN optimizations are enabled by default on X86 CPUs
  • To explicitly enable or disable oneDNN optimizations, set the environment variable TF_ENABLE_ONEDNN_OPTS to 1 (enable) or 0 (disable) before running TensorFlow. To fall back to default settings, unset the environment variable.
  • oneDNN optimizations can yield slightly different numerical results compared to when oneDNN optimizations are disabled due to floating-point round-off errors from different computation approaches and orders.
  • To verify if oneDNN optimizations are on, look for a message with "oneDNN custom operations are on" in the log. If the exact phrase is not there, it means they are off.

• Making the tf.function type system fully available:

  • tf.types.experimental.TraceType now allows custom tf.function inputs to declare Tensor decomposition and type casting support.
  • Introducing tf.types.experimental.FunctionType as the comprehensive representation of the signature of tf.function callables. It can be accessed through the function_type property of tf.functions and ConcreteFunctions. See the tf.types.experimental.FunctionType documentation for more details.

• Introducing tf.types.experimental.AtomicFunction as the fastest way to perform TF computations in Python.

  • Can be accessed through inference_fn property of ConcreteFunctions
  • Does not support gradients.
  • See tf.types.experimental.AtomicFunction documentation for how to call and use it.

• tf.data:

  • Moved option warm_start from tf.data.experimental.OptimizationOptions to tf.data.Options.

• tf.lite:

  • sub_op and mul_op support broadcasting up to 6 dimensions.

  • The tflite::SignatureRunner class, which provides support for named parameters and for multiple named computations within a single TF Lite model, is no longer considered experimental. Likewise for the following signature-related methods of tflite::Interpreter:

    • tflite::Interpreter::GetSignatureRunner
    • tflite::Interpreter::signature_keys
    • tflite::Interpreter::signature_inputs
    • tflite::Interpreter::signature_outputs
    • tflite::Interpreter::input_tensor_by_signature
    • tflite::Interpreter::output_tensor_by_signature

... (truncated)

Commits

• 6887368 Merge pull request #62369 from tensorflow/r2.15-ea45e14c926
• 6f92629 Change jaxlib version to the next earliest version for MacOS + Linux CI builds.
• 71b7f97 Merge pull request #62350 from rtg0795/r2.15
• 486d1c0 Update requirements.in and lock files
• d289c2d Merge pull request #62349 from tensorflow-jenkins/version-numbers-2.15.0-20998
• 9d77d88 Update version numbers to 2.15.0
• 9381e7c Merge pull request #62348 from tensorflow/rtg0795-patch-1
• e554d29 Update setup.py with released version of Estimator and Keras
• 2a4ec94 Merge pull request #62308 from tensorflow/r2.15-e44f8a08051
• cca5fda Merge pull request #62307 from tensorflow/r2.15-a1fd78b23b1
• Additional commits viewable in compare view

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