[MNT] Update tensorflow and refactor networks

.github/actions/cpu_all_extras/action.yml

@@ -15,7 +15,7 @@ runs:
   using: "composite"
   steps:
     - name: Install CPU TensorFlow
-      if: ${{ runner.os == 'Linux' && inputs.python_version != '3.13' && inputs.python_version != '3.14' }}
+      if: ${{ runner.os == 'Linux' && inputs.python_version != '3.14' }}
       uses: nick-fields/retry@v3
       with:
         timeout_minutes: 30

.github/workflows/periodic_tests.yml

@@ -246,7 +246,7 @@ jobs:
         run: python -m pip list
 
       - name: Run tests
-        run: python -m pytest -n logical --doctest-only --doctest-continue-on-failure
+        run: python -m pytest -n logical --doctest-only
 
       - name: Save new cache
         uses: actions/cache/save@v5

.github/workflows/pr_pytest.yml

@@ -135,7 +135,7 @@ jobs:
         run: python -m pip list
 
       - name: Run tests
-        run: python -m pytest -n logical --doctest-only --doctest-continue-on-failure
+        run: python -m pytest -n logical --doctest-only
 
   multithreaded-estimators:
     runs-on: ubuntu-24.04

aeon/clustering/deep_learning/_ae_drnn.py

@@ -16,7 +16,7 @@
 from aeon.utils.validation._dependencies import _check_soft_dependencies
 
 if _check_soft_dependencies(["tensorflow"], severity="none"):
-    from aeon.networks._ae_drnn import _TensorDilation
+    from aeon.networks.auto_encoder._ae_drnn import _TensorDilation
 
 
 class AEDRNNClusterer(BaseDeepClusterer):
@@ -352,7 +352,7 @@ def load_model(self, model_path, estimator):
         """
         import tensorflow as tf
 
-        from aeon.networks._ae_drnn import _TensorDilation
+        from aeon.networks.auto_encoder._ae_drnn import _TensorDilation
 
         self.model_ = tf.keras.models.load_model(
             model_path, custom_objects={"_TensorDilation": _TensorDilation}

aeon/forecasting/deep_learning/_deepar.py

@@ -18,7 +18,7 @@
 
 from aeon.forecasting.base import DirectForecastingMixin, IterativeForecastingMixin
 from aeon.forecasting.deep_learning.base import BaseDeepForecaster
-from aeon.networks._deepar import DeepARNetwork
+from aeon.networks.encoder_decoder._deepar import DeepARNetwork
 
 
 class DeepARForecaster(

aeon/forecasting/deep_learning/_tcn.py

@@ -16,7 +16,7 @@
 
 from aeon.forecasting.base import IterativeForecastingMixin
 from aeon.forecasting.deep_learning.base import BaseDeepForecaster
-from aeon.networks._tcn import TCNNetwork
+from aeon.networks.encoder._tcn import TCNNetwork
 
 
 class TCNForecaster(BaseDeepForecaster, IterativeForecastingMixin):

aeon/networks/__init__.py

@@ -23,23 +23,24 @@
     "TCNNetwork",
     "NBeatsNetwork",
 ]
-from aeon.networks._ae_abgru import AEAttentionBiGRUNetwork
-from aeon.networks._ae_bgru import AEBiGRUNetwork
-from aeon.networks._ae_dcnn import AEDCNNNetwork
-from aeon.networks._ae_drnn import AEDRNNNetwork
-from aeon.networks._ae_fcn import AEFCNNetwork
-from aeon.networks._ae_resnet import AEResNetNetwork
-from aeon.networks._cnn import TimeCNNNetwork
-from aeon.networks._dcnn import DCNNNetwork
-from aeon.networks._deepar import DeepARNetwork
-from aeon.networks._disjoint_cnn import DisjointCNNNetwork
-from aeon.networks._encoder import EncoderNetwork
-from aeon.networks._fcn import FCNNetwork
-from aeon.networks._inception import InceptionNetwork
-from aeon.networks._lite import LITENetwork
-from aeon.networks._mlp import MLPNetwork
-from aeon.networks._nbeats import NBeatsNetwork
-from aeon.networks._resnet import ResNetNetwork
-from aeon.networks._rnn import RecurrentNetwork
-from aeon.networks._tcn import TCNNetwork
+
+from aeon.networks.auto_encoder._ae_abgru import AEAttentionBiGRUNetwork
+from aeon.networks.auto_encoder._ae_bgru import AEBiGRUNetwork
+from aeon.networks.auto_encoder._ae_dcnn import AEDCNNNetwork
+from aeon.networks.auto_encoder._ae_drnn import AEDRNNNetwork
+from aeon.networks.auto_encoder._ae_fcn import AEFCNNetwork
+from aeon.networks.auto_encoder._ae_resnet import AEResNetNetwork
+from aeon.networks.auto_encoder._nbeats import NBeatsNetwork
 from aeon.networks.base import BaseDeepLearningNetwork
+from aeon.networks.encoder._cnn import TimeCNNNetwork
+from aeon.networks.encoder._dcnn import DCNNNetwork
+from aeon.networks.encoder._disjoint_cnn import DisjointCNNNetwork
+from aeon.networks.encoder._encoder import EncoderNetwork
+from aeon.networks.encoder._fcn import FCNNetwork
+from aeon.networks.encoder._inception import InceptionNetwork
+from aeon.networks.encoder._lite import LITENetwork
+from aeon.networks.encoder._mlp import MLPNetwork
+from aeon.networks.encoder._resnet import ResNetNetwork
+from aeon.networks.encoder._rnn import RecurrentNetwork
+from aeon.networks.encoder._tcn import TCNNetwork
+from aeon.networks.encoder_decoder._deepar import DeepARNetwork

aeon/networks/auto_encoder/__init__.py

@@ -0,0 +1 @@
+"""Auto-Encoder networks."""

aeon/networks/_ae_abgru.py → aeon/networks/auto_encoder/_ae_abgru.py

@@ -38,8 +38,7 @@ class AEAttentionBiGRUNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "auto-encoder",
     }
 
@@ -52,15 +51,15 @@ def __init__(
         activation_encoder="relu",
         activation_decoder="relu",
     ):
-        super().__init__()
-
         self.latent_space_dim = latent_space_dim
         self.temporal_latent_space = temporal_latent_space
         self.activation_encoder = activation_encoder
         self.activation_decoder = activation_decoder
         self.n_layers_encoder = n_layers_encoder
         self.n_layers_decoder = n_layers_decoder
 
+        super().__init__()
+
     def build_network(self, input_shape, **kwargs):
         """Construct a network and return its input and output layers.
 

aeon/networks/_ae_bgru.py → aeon/networks/auto_encoder/_ae_bgru.py

@@ -25,8 +25,7 @@ class AEBiGRUNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "auto-encoder",
     }
 

aeon/networks/_ae_dcnn.py → aeon/networks/auto_encoder/_ae_dcnn.py

@@ -53,8 +53,7 @@ class AEDCNNNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "auto-encoder",
     }
 

aeon/networks/_ae_drnn.py → aeon/networks/auto_encoder/_ae_drnn.py

@@ -57,8 +57,7 @@ class AEDRNNNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "auto-encoder",
     }
 

aeon/networks/_ae_fcn.py → aeon/networks/auto_encoder/_ae_fcn.py

@@ -57,8 +57,7 @@ class AEFCNNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "auto-encoder",
     }
 

aeon/networks/_ae_resnet.py → aeon/networks/auto_encoder/_ae_resnet.py

@@ -69,8 +69,7 @@ class AEResNetNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "auto-encoder",
     }
 

aeon/networks/_nbeats.py → aeon/networks/auto_encoder/_nbeats.py

@@ -53,8 +53,7 @@ class NBeatsNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "auto-encoder",
     }
 

aeon/networks/auto_encoder/tests/__init__.py

@@ -0,0 +1 @@
+"""Tests for Auto-Encoder networks."""

aeon/networks/base.py

@@ -1,6 +1,6 @@
 """Abstract base class for deep learning networks."""
 
-__maintainer__ = []
+__maintainer__ = ["hadifawaz1999"]
 
 from abc import ABC, abstractmethod
 
@@ -15,15 +15,14 @@ class BaseDeepLearningNetwork(ABC):
     """Abstract base class for deep learning networks."""
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
-        "structure": "encoder",
+        "python_dependencies": "tensorflow",
+        "python_version": "<3.14",
     }
 
     @abstractmethod
-    def __init__(self, soft_dependencies="tensorflow", python_version="<3.13"):
-        _check_soft_dependencies(soft_dependencies)
-        _check_python_version(python_version)
+    def __init__(self):
+        _check_soft_dependencies(self._config["python_dependencies"])
+        _check_python_version(self._config["python_version"])
         super().__init__()
 
     def __repr__(self):

aeon/networks/encoder/__init__.py

@@ -0,0 +1 @@
+"""Encoder networks."""

aeon/networks/_cnn.py → aeon/networks/encoder/_cnn.py

@@ -54,8 +54,7 @@ class TimeCNNNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "encoder",
     }
 

aeon/networks/_dcnn.py → aeon/networks/encoder/_dcnn.py

@@ -41,8 +41,7 @@ class DCNNNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.12",
+        **BaseDeepLearningNetwork._config,
         "structure": "encoder",
     }
 
@@ -56,8 +55,6 @@ def __init__(
         dilation_rate=None,
         padding="causal",
     ):
-        super().__init__()
-
         self.latent_space_dim = latent_space_dim
         self.kernel_size = kernel_size
         self.n_filters = n_filters
@@ -66,7 +63,9 @@ def __init__(
         self.activation = activation
         self.padding = padding
 
-    def build_network(self, input_shape):
+        super().__init__()
+
+    def build_network(self, input_shape, **kwargs):
         """Construct a network and return its input and output layers.
 
         Parameters

aeon/networks/_disjoint_cnn.py → aeon/networks/encoder/_disjoint_cnn.py

@@ -85,8 +85,7 @@ class DisjointCNNNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "encoder",
     }
 

aeon/networks/_encoder.py → aeon/networks/encoder/_encoder.py

@@ -43,6 +43,11 @@ class EncoderNetwork(BaseDeepLearningNetwork):
     for Artificial Intelligence, 120--129 2018.
     """
 
+    _config = {
+        **BaseDeepLearningNetwork._config,
+        "structure": "encoder",
+    }
+
     def __init__(
         self,
         kernel_size=None,

aeon/networks/_fcn.py → aeon/networks/encoder/_fcn.py

@@ -43,8 +43,7 @@ class FCNNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "encoder",
     }
 

aeon/networks/_inception.py → aeon/networks/encoder/_inception.py

@@ -2,6 +2,8 @@
 
 __maintainer__ = ["hadifawaz1999"]
 
+import numpy as np
+
 from aeon.networks.base import BaseDeepLearningNetwork
 
 
@@ -95,8 +97,7 @@ class InceptionNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "encoder",
     }
 
@@ -152,23 +153,11 @@ def hybrid_layer(self, input_tensor, input_channels, kernel_sizes=None):
         of the output features extracted form hand-crafted convolution filters.
 
         """
-        import numpy as np
         import tensorflow as tf
 
-        kernel_sizes = [2, 4, 8, 16, 32, 64] if kernel_sizes is None else kernel_sizes
-
         self.keep_track = 0
 
-        """
-        Function to create the hybrid layer consisting of non
-        trainable Conv1D layers with custom filters.
-
-        Args:
-
-            input_tensor: input tensor
-            input_channels : number of input channels, 1 in case of UCR Archive
-        """
-
+        kernel_sizes = [2, 4, 8, 16, 32, 64] if kernel_sizes is None else kernel_sizes
         conv_list = []
 
         # for increasing detection filters

aeon/networks/_lite.py → aeon/networks/encoder/_lite.py

@@ -51,8 +51,7 @@ class LITENetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "encoder",
     }
 

aeon/networks/_mlp.py → aeon/networks/encoder/_mlp.py

@@ -42,8 +42,7 @@ class MLPNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "encoder",
     }
 
@@ -56,15 +55,15 @@ def __init__(
         dropout_last: float = None,
         use_bias: bool = True,
     ):
-        super().__init__()
-
         self.n_layers = n_layers
         self.n_units = n_units
         self.activation = activation
         self.dropout_rate = dropout_rate
         self.dropout_last = dropout_last
         self.use_bias = use_bias
 
+        super().__init__()
+
     def build_network(self, input_shape, **kwargs):
         """Construct a network and return its input and output layers.
 

aeon/networks/_resnet.py → aeon/networks/encoder/_resnet.py

@@ -63,8 +63,7 @@ class ResNetNetwork(BaseDeepLearningNetwork):
     """
 
     _config = {
-        "python_dependencies": ["tensorflow"],
-        "python_version": "<3.13",
+        **BaseDeepLearningNetwork._config,
         "structure": "encoder",
     }