[ENH] Starting Self Supervised Model with first example (#2385)

* add ssl module in transformations collection

* add api

* add test params

* fix example

* restart tests

* test fix params

* network none

* revert

* import inside function

* try dummy

* test repr

* network repr

* enhance testing

* fix test

* replace tcnn by lite

* tony's comments

* fix typing

* fix znorm

* z_norm in test

* add exp module

* Update repr.py

* Update base.py

* Automatic `pre-commit` fixes

---------

Co-authored-by: MatthewMiddlehurst <pfm15hbu@gmail.com>
Co-authored-by: MatthewMiddlehurst <25731235+MatthewMiddlehurst@users.noreply.github.com>

Author: hadifawaz1999

README.md

@@ -26,6 +26,7 @@ does not apply:
 - `segmentation`
 - `similarity_search`
 - `visualisation`
+- `transformations.collection.self_supervised`
 
 | Overview        |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
 |-----------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|

aeon/networks/base.py

@@ -4,6 +4,7 @@
 
 from abc import ABC, abstractmethod
 
+from aeon.utils.repr import get_unchanged_and_required_params_as_str
 from aeon.utils.validation._dependencies import (
     _check_python_version,
     _check_soft_dependencies,
@@ -25,6 +26,11 @@ def __init__(self, soft_dependencies="tensorflow", python_version="<3.13"):
         _check_python_version(python_version)
         super().__init__()
 
+    def __repr__(self):
+        """Format str output like scikit-learn estimators."""
+        changed_params = get_unchanged_and_required_params_as_str(self)
+        return f"{self.__class__.__name__}({changed_params})"
+
     @abstractmethod
     def build_network(self, input_shape, **kwargs):
         """Construct a network and return its input and output layers.

aeon/networks/tests/test_network_base.py

@@ -20,7 +20,8 @@ def build_network(self, input_shape, **kwargs):
         import tensorflow as tf
 
         input_layer = tf.keras.layers.Input(input_shape)
-        output_layer = tf.keras.layers.Dense(units=10)(input_layer)
+        flatten_layer = tf.keras.layers.Flatten()(input_layer)
+        output_layer = tf.keras.layers.Dense(units=10)(flatten_layer)
 
         return input_layer, output_layer
 

aeon/transformations/collection/self_supervised/__init__.py

@@ -0,0 +1,5 @@
+"""Self Supervised deep learning transformers."""
+
+__all__ = ["TRILITE"]
+
+from aeon.transformations.collection.self_supervised._trilite import TRILITE