Fix wave training script imports

[pderrenger]

Summary

• replace star imports in training scripts with explicit utility imports
• add direct numpy/torch imports for names used by the scripts
• format the affected utilities and scripts with Ruff

Tests

• python -m ruff check gcp/wave_pytorch_gcp.py train.py train_tf.py utils/utils.py utils/torch_utils.py
• python -m ruff format gcp/wave_pytorch_gcp.py train.py train_tf.py utils/utils.py utils/torch_utils.py
• python -m compileall -q gcp/wave_pytorch_gcp.py train.py train_tf.py utils/utils.py utils/torch_utils.py
• git diff --check

🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

🧹 This PR mainly cleans up and standardizes the ultralytics/wave training scripts, improving code clarity, import safety, and maintainability without changing the core training behavior.

📊 Key Changes

• ✅ Replaced wildcard imports with explicit imports in PyTorch, TensorFlow, and GCP scripts:
  • from utils import * → targeted function imports
  • from utils.torch_utils import * and from utils.utils import * → explicit named imports
• 📦 Added missing direct imports for numpy and torch where they were already being used.
• 🔇 Renamed unused variables like nz, nx, and ymu to _nz, _nx, and _ymu to make it clear they are intentionally unused.
• ✨ Improved string formatting consistency using safer f-string patterns like f"{a!s}" and f"{i!s}".
• 📚 Reformatted several long lines and nested calls for better readability, including:
  • scipy.io.savemat(...)
  • TensorFlow apply_gradients(...)
  • Plotly layout definitions
  • PyTorch convolution layer definitions
  • large list definitions in experiment settings
• 🧩 Reformatted splitdata() to return values across multiple lines for easier reading.
• 📝 Minor README formatting cleanup for dependency setup.

🎯 Purpose & Impact

• 👀 Makes the codebase easier to read and understand for new contributors and researchers.
• 🛡️ Reduces risks from wildcard imports, which can hide dependencies and cause naming conflicts.
• 🔧 Improves maintainability by making module dependencies explicit and code style more consistent.
• 🚀 Helps future development and debugging by clarifying which variables are used and which are not.
• 📈 Likely no major user-facing behavior change, but it should make the project more stable and easier to extend over time.

[UltralyticsAssistant]

👋 Hello @pderrenger, thank you for submitting a ultralytics/wave 🚀 PR! This is an automated message to help with review readiness, and an engineer will assist shortly. Please review the checklist below to help ensure a smooth merge ✨

-✅ Define a Purpose: Clearly explain the purpose of your fix or feature in your PR description, and link to any relevant issues. Ensure your commit messages are clear, concise, and adhere to the project's conventions.
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-✅ Update Documentation: Update the relevant documentation for any new or modified features.
-✅ Add Tests: If applicable, include or update tests to cover your changes, and confirm that all tests are passing.
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-✅ Minimize Changes: Limit your changes to the minimum necessary for your bug fix or feature addition. "It is not daily increase but daily decrease, hack away the unessential. The closer to the source, the less wastage there is." — Bruce Lee

For more guidance, please refer to our Contributing Guide. Don't hesitate to leave a comment if you have any questions. Thank you for contributing to Ultralytics! 🚀

[UltralyticsAssistant]

🔍 PR Review

_{Made with ❤️ by Ultralytics Actions}

PR looks clean. The diff is limited to explicit import fixes, adding missing NumPy/Torch imports, and non-functional formatting/cleanup changes, and I did not find any genuine issues in the changed lines.

[UltralyticsAssistant]

Merged — great cleanup work by @pderrenger, with contributions from @glenn-jocher. 🎉

As Leonardo da Vinci said, “Simplicity is the ultimate sophistication.” This PR reflects that well: clearer imports, safer dependencies, improved readability, and more consistent formatting all make ultralytics/wave easier to maintain and extend without changing its core behavior.

Thanks for helping strengthen the codebase in ways that will benefit every future contributor.