Transform model fine-tuning code to Python package #111
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Transform the model fine-tuning code in the Jupyter notebook files into a Python package named `deeptune` to help people fine-tune and train models of siamese architecture. * **Package Structure:** - Create `deeptune` package with subdirectories: `data`, `models`, `training`, `evaluation`, `utils`, and `cli`. - Add `__init__.py` files to each subdirectory to make them sub-packages. - Add `config.py` for configuration settings. - Add `requirements.txt` to list dependencies. * **CLI Support:** - Create `cli.py` in `cli` subdirectory to allow users to interact with the package through the command line. - Implement `evaluate_model` command to evaluate models. * **Loss Functions:** - Implement Triplet Loss, ArcFace Loss, and Contrastive Loss in `training/losses.py`. * **Data Generators:** - Implement `TripletGenerator` in `training/data_generators.py` to generate triplets for the triplet loss function. * **Evaluation:** - Move `Model-Training/eval-mark-I.py` to `evaluation/eval_mark_I.py` and update imports. - Move `Model-Training/Evaluate_model_1.ipynb` to `evaluation/evaluate_model_1.ipynb` and update imports. * **Documentation:** - Update `README.md` to include instructions for using the new Python package, CLI usage, and example code. --- For more details, open the [Copilot Workspace session](https://copilot-workspace.githubnext.com/Devasy23/FaceRec?shareId=XXXX-XXXX-XXXX-XXXX).
for more information, see https://pre-commit.ci
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Transform the model fine-tuning code in the Jupyter notebook files into a Python package named
deeptuneto help people fine-tune and train models of siamese architecture.Package Structure:
deeptunepackage with subdirectories:data,models,training,evaluation,utils, andcli.__init__.pyfiles to each subdirectory to make them sub-packages.config.pyfor configuration settings.requirements.txtto list dependencies.CLI Support:
cli.pyinclisubdirectory to allow users to interact with the package through the command line.evaluate_modelcommand to evaluate models.Loss Functions:
training/losses.py.Data Generators:
TripletGeneratorintraining/data_generators.pyto generate triplets for the triplet loss function.Evaluation:
Model-Training/eval-mark-I.pytoevaluation/eval_mark_I.pyand update imports.Model-Training/Evaluate_model_1.ipynbtoevaluation/evaluate_model_1.ipynband update imports.Documentation:
README.mdto include instructions for using the new Python package, CLI usage, and example code.For more details, open the Copilot Workspace session.