Add saliency notebook

[surajpaib]

Description

Related Issue

Type of Change

• [ ] 📚 Examples / docs / tutorials / dependencies update
• [ ] 🔧 Bug fix (non-breaking change which fixes an issue)
• [ ] 🥂 Improvement (non-breaking change which improves an existing feature)
• [ ] 🚀 New feature (non-breaking change which adds functionality)
• [ ] 💥 Breaking change (fix or feature that would cause existing functionality to change)
• [ ] 🔐 Security fix

Checklist

• [ ] I've read the CODE_OF_CONDUCT.md document.
• [ ] I've read the CONTRIBUTING.md guide.
• [ ] I've updated the code style using make codestyle.
• [ ] I've written tests for all new methods and classes that I created.
• [ ] I've written the docstring in Google format for all the methods and classes that I used.

Summary by CodeRabbit

• New Features
  • Updated training configuration for improved machine learning model performance.
  • Introduced metrics for evaluation, including Average Precision and AUROC for multiclass tasks.
  • Added new dependencies to modernize the environment and ensure compatibility with newer releases.
  • Added a new test file to validate workflows related to dummy data.
• Bug Fixes
  • Enhanced safety check command in the Makefile for better error handling.
• Chores
  • Updated workflow configuration for branch naming and Python versioning.
  • Modified publishing process to streamline package deployment.
  • Updated caching mechanism in build workflow for improved efficiency.
  • Removed outdated test file related to dummy data generation.

[coderabbitai[bot]]

Walkthrough

The changes in the configuration file fmcib_finetune.yaml focus on the setup for a machine learning experiment, particularly regarding model parameters and training configurations. Key sections include the definition of a ResNet50 model with specific adjustments, metrics for evaluation, and dataset configurations. While the trainer, optimizer, and scheduler sections remain unchanged, there are indications for potential future modifications tailored to specific tasks. Additionally, updates to the .github/workflows/publish.yml, Makefile, and pyproject.toml reflect changes in workflow configurations, safety checks, and dependency management.

Changes

File Path	Change Summary
experiments/adaptation/fmcib_finetune.yaml	Modified training setup and model parameters; specified ResNet50 architecture, metrics, and dataset configurations.
.github/workflows/publish.yml	Updated branch name from master to main, Python version from 3.8 to 3.9, added steps for package installation and publishing, and changed publishing action.
Makefile	Updated check-safety target to include an --ignore flag for safety checks; formatting changes for clarity.
pyproject.toml	Updated dependency versions for urllib3 and tornado, added new dependencies, and modified aiohttp version.
fmcib/models/load_model.py	Updated load method in LoadModel class to include weights_only=True in torch.load function.
tests/integration/config/test.yaml	Introduced new configuration file for a machine learning training pipeline with detailed setup.
tests/integration/test_dummy_data.py	Removed test function test_dummy_features.
tests/integration/test_dummy_workflows.py	Added new test functions for validating workflows related to dummy data.
.github/workflows/build.yml	Updated caching action version from v2.1.6 to v4.

🐇 "In the meadow where data flows,
A ResNet50 model grows.
With metrics set and datasets clear,
We train with joy, no room for fear.
Future tweaks await our gaze,
As we hop through machine learning's maze!" 🐇

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