Merge pull request #11 from sascha-kirch/document_models

Document models

DeepSaki/__init__.py

@@ -3,9 +3,9 @@
 from . import constraints
 from . import initializers
 from . import layers
-from . import loss
+from . import losses
 from . import models
-from . import optimizer
+from . import optimizers
 from . import utils
 
 __version__ = "1.0.0"
@@ -18,8 +18,8 @@
     "constraints",
     "initializers",
     "layers",
-    "loss",
+    "losses",
     "models",
-    "optimizer",
+    "optimizers",
     "utils",
 ]

DeepSaki/activations/complex_valued_activations.py

@@ -13,11 +13,11 @@ class ComplexActivation(tf.keras.layers.Layer):
         tf.keras.layers.Layer
     """
 
-    def __init__(self, activation: tf.keras.layers.Layer = tf.keras.layers.ReLU(), **kwargs: Any) -> None:
+    def __init__(self, activation: tf.keras.layers.Layer, **kwargs: Any) -> None:
         """Initialize ComplexActivation.
 
         Args:
-            activation (tf.keras.layers.Layer, optional): Activation function to complexyfy. Defaults to tf.keras.layers.ReLU().
+            activation (tf.keras.layers.Layer): Activation function to complexyfy.
             kwargs: keyword arguments passed to the parent class tf.keras.layers.Layer.
         """
         super(ComplexActivation, self).__init__(**kwargs)

DeepSaki/augmentations/grid_cutting.py

@@ -18,11 +18,12 @@ def _random_boundingbox(height: int, width: int) -> Tuple[int, int, int, int]:
         x value bottom-right corner.
         y value bottom-right corner.
     """
-    r = np.sqrt(1.0 - np.random.beta(1, 1))
+    random_generator = np.random.default_rng()
+    r = np.sqrt(1.0 - random_generator.beta(1, 1))
     w = np.floor(width * r)
     h = np.floor(height * r)
-    x = np.random.randint(width)
-    y = np.random.randint(height)
+    x = random_generator.integers(width)
+    y = random_generator.integers(height)
 
     x1 = int(np.clip(x - w // 2, 0, width))
     y1 = int(np.clip(y - h // 2, 0, height))

DeepSaki/initializers/he_alpha.py

@@ -99,7 +99,7 @@ def __init__(self, alpha: float = 0.3, seed: Optional[int] = None) -> None:
         """
         super(HeAlphaUniform, self).__init__(alpha, seed)
 
-    def __call__(self, shape: List[int], dtype: Optional[Union[tf.DType | np.dtype]] = None) -> tf.Tensor:
+    def __call__(self, shape: List[int], dtype: Optional[Union[tf.DType, np.dtype]] = None) -> tf.Tensor:
         """Dunder method to call the object instance.
 
         Args:

DeepSaki/initializers/initializer_helper.py

@@ -15,12 +15,14 @@ def make_initializer_complex(
     **Examples:**
     ```python
     # Standalone usage:
-    initializer = make_initializer_complex(tf.keras.initializers.GlorotUniform())
+    import DeepSaki as dsk
+    initializer = dsk.initializers.make_initializer_complex(tf.keras.initializers.GlorotUniform())
     values = initializer(shape=(2, 2))
     ```
     ```python
     # Usage in a Keras layer:
-    initializer = make_initializer_complex(tf.keras.initializers.GlorotUniform())
+    import DeepSaki as dsk
+    initializer = dsk.initializers.make_initializer_complex(tf.keras.initializers.GlorotUniform())
     layer = tf.keras.layers.Dense(3, kernel_initializer=initializer)
     ```
 

DeepSaki/layers/__init__.py

@@ -20,7 +20,7 @@
 from DeepSaki.layers.layer_composites import DenseBlock
 from DeepSaki.layers.layer_composites import DownSampleBlock
 from DeepSaki.layers.layer_composites import UpSampleBlock
-from DeepSaki.layers.layer_composites import ResidualIdentityBlock
+from DeepSaki.layers.layer_composites import ResidualBlock
 from DeepSaki.layers.layer_composites import ResBlockDown
 from DeepSaki.layers.layer_composites import ResBlockUp
 from DeepSaki.layers.layer_composites import ScaleLayer