55 lines
2.9 KiB
Plaintext
55 lines
2.9 KiB
Plaintext
# Requirements for ml-model-trainer Plugin
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This file, `requirements.txt`, specifies the Python packages required for the `ml-model-trainer` plugin to function correctly. It is used by `pip` to install these dependencies.
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## Purpose
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The `requirements.txt` file ensures that all necessary libraries are installed in the correct versions, guaranteeing consistency and reproducibility of the model training processes. It helps avoid dependency conflicts and ensures that the plugin operates as intended.
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## Contents
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Below is a template for the `requirements.txt` file. **Please carefully review and modify the versions to match your specific needs and compatibility requirements.**
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```
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# Core Dependencies
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scikit-learn==<INSERT_SCI_KIT_LEARN_VERSION_HERE>
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pandas==<INSERT_PANDAS_VERSION_HERE>
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numpy==<INSERT_NUMPY_VERSION_HERE>
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# Optional Dependencies (Uncomment and specify versions if needed)
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# matplotlib==<INSERT_MATPLOTLIB_VERSION_HERE> # For visualization
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# seaborn==<INSERT_SEABORN_VERSION_HERE> # For enhanced visualization
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# xgboost==<INSERT_XGBOOST_VERSION_HERE> # For XGBoost models
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# lightgbm==<INSERT_LIGHTGBM_VERSION_HERE> # For LightGBM models
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# tensorflow==<INSERT_TENSORFLOW_VERSION_HERE> # For TensorFlow models
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# torch==<INSERT_TORCH_VERSION_HERE> # For PyTorch models
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# Example:
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# scikit-learn==1.2.2
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# pandas==1.5.3
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# numpy==1.24.3
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```
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## Instructions
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1. **Replace Placeholders:** Carefully replace the `<INSERT_*_VERSION_HERE>` placeholders with the specific versions of each package you intend to use. It is highly recommended to specify exact versions to ensure consistent behavior across different environments.
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2. **Uncomment Optional Dependencies:** If your model training process relies on optional packages like `matplotlib`, `seaborn`, `xgboost`, `lightgbm`, `tensorflow`, or `torch`, uncomment the corresponding lines and specify the desired versions.
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3. **Consider Version Compatibility:** Pay close attention to the compatibility between different packages. Refer to the documentation of each package to understand potential version conflicts.
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4. **Updating Dependencies:** When updating the plugin, review and update the `requirements.txt` file to reflect any changes in dependencies.
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## Example Usage
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To install the dependencies listed in this file, use the following command:
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```bash
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pip install -r requirements.txt
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```
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**Important Considerations:**
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* **Virtual Environments:** It is highly recommended to use virtual environments (e.g., `venv` or `conda`) to isolate the plugin's dependencies from the global Python environment. This helps prevent conflicts with other projects.
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* **Package Management:** Consider using a package manager like `poetry` or `pipenv` for more advanced dependency management features.
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* **Testing:** Thoroughly test the plugin after installing the dependencies to ensure that everything functions correctly. |