[ENH] Main and Docker

data_aug_4_tsc/feature_extractors/_lite.py

@@ -1,9 +1,44 @@
+"""The LITE classification model."""
+
 import numpy as np
 import tensorflow as tf
 from aeon.classification.deep_learning import IndividualLITEClassifier
 
 
 class LITE_CLASSIFIER:
+    """The Light Inception with boosTing tEchniques (LITE).
+
+    The LITE [1]_ classificaiton model uses a CNN backbone with
+    an optimized number of parameters to classify time series
+    samples. We use aeon-toolkit [2]_ 's implementation.
+
+    Parameters
+    ----------
+    output_directory : str
+        The output directory.
+    n_epochs : int, default = 1500
+        The number of epochs to train the model.
+    batch_size : int, default = 64
+        The batch size during training.
+
+    Returns
+    -------
+    None
+
+    References
+    ----------
+    .. [1] Ismail-Fawaz, Ali, Maxime Devanne, Stefano Berretti,
+    Jonathan Weber, and Germain Forestier. "Lite: Light inception
+    with boosting techniques for time series classification." In
+    2023 IEEE 10th International Conference on Data Science and
+    Advanced Analytics (DSAA), pp. 1-10. IEEE, 2023.
+
+    .. [2] Middlehurst, Matthew, Ali Ismail-Fawaz, Antoine Guillaume,
+    Christopher Holder, David Guijo-Rubio, Guzal Bulatova, Leonidas
+    Tsaprounis et al. "aeon: a Python toolkit for learning from
+    time series." Journal of Machine Learning Research 25, no.
+    289 (2024): 1-10.
+    """
 
     def __init__(
         self, output_directory: str, n_epochs: int = 1500, batch_size: int = 64
@@ -15,7 +50,20 @@ def __init__(
         self.feature_extractor = None
 
     def fit(self, X: np.ndarray, y: np.ndarray):
+        """Train the model on labeled real samples.
+
+        Parameters
+        ----------
+        X : np.ndarray
+            The real samples.
+        y : np.ndarray
+            The labels of the real samples.
+
+        Returns
+        -------
+        A trained keras model.
 
+        """
         self.feature_extractor = IndividualLITEClassifier(
             file_path=self.output_directory,
             save_best_model=True,

dockerfile

@@ -0,0 +1,31 @@
+FROM tensorflow/tensorflow:2.16.1-gpu
+
+ARG USER_ID
+ARG GROUP_ID
+
+RUN groupadd -r -g $GROUP_ID myuser && useradd -r -u $USER_ID -g myuser -m -d /home/myuser myuser
+ENV SHELL /bin/bash
+
+RUN mkdir -p /home/myuser/code && chown -R myuser:myuser /home/myuser/code
+
+WORKDIR /home/myuser/code
+
+RUN apt update
+RUN apt install -y jq
+
+RUN pip install aeon==1.0.0
+RUN pip install keras==3.6.0
+RUN pip install hydra-core==1.3.2
+RUN pip install omegaconf==2.3.0
+RUN pip install pandas==2.2.0
+RUN pip install matplotlib==3.10.0
+RUN pip install numba==0.60.0
+RUN pip install black
+RUN pip install flake8
+RUN pip install mypy
+RUN pip install pytest
+RUN pip install pytest-cov
+RUN pip install pytest-xdist
+RUN pip install pytest-timeout
+RUN pip install pytest-rerunfailures
+RUN pip install pre-commit