A Machine Learning Template Project
This is a machine learning template project for generic training, validation and testing.
Project Structure
machine-learning-template
├─data
├─experiments
├─lib
├─notebooks
├─tests
└─tools
-
Project is mainly considered to be structured, where the core functional about config, models, core, loss etc. are stored in
example_lib
directory. -
And the
tests
directory are mainly consists of some test case of functional components. Generate the random inputs and test if there is any bug. -
The
notebooks
directory consists of some visulization results and early developement of some functional modules. -
The
experiments
directory consists of custom defined.yaml
file for ablation studies. -
The
tools
directory consists of custom training and testing scripts. -
The
data
directory consists of datasets for training, some subdirectory can be created by symbol link:ln -s /path/to/target/dataset dataset_name
IDE Tips
If use VS Code, put following snippets in your .vscode/setting.json
:
{
"python.autoComplete.extraPaths": [
"${workspaceFolder}/*"
],
"python.analysis.extraPaths": [
"${workspaceFolder}/*"
]
}
If use Pycharm, just mark related directories as source folders.
Create Requirements
Install the pipreqs
, and use this tools to scan your project, and generate the requirements.txt
.