Simplified namespace so layers can be imported from manim_ml.neural_network

Readme.md

@@ -37,9 +37,7 @@ https://user-images.githubusercontent.com/14181830/214898495-ff40c679-3f79-4954-
 ```python
 from manim import *
 
-from manim_ml.neural_network.layers.convolutional_2d import Convolutional2DLayer
-from manim_ml.neural_network.layers.feed_forward import FeedForwardLayer
-from manim_ml.neural_network.neural_network import NeuralNetwork
+from manim_ml.neural_network import Convolutional2DLayer, FeedForwardLayer, NeuralNetwork
 
 # Make the specific scene
 config.pixel_height = 700

examples/readme_example/example.py

@@ -1,8 +1,6 @@
 from manim import *
 
-from manim_ml.neural_network.layers.convolutional_2d import Convolutional2DLayer
-from manim_ml.neural_network.layers.feed_forward import FeedForwardLayer
-from manim_ml.neural_network.neural_network import NeuralNetwork
+from manim_ml.neural_network import Convolutional2DLayer, FeedForwardLayer, NeuralNetwork
 
 # Make the specific scene
 config.pixel_height = 700

manim_ml/neural_network/__init__.py

@@ -0,0 +1,23 @@
+from manim_ml.neural_network.neural_network import NeuralNetwork
+from manim_ml.neural_network.layers.feed_forward import FeedForwardLayer
+from manim_ml.neural_network.layers.convolutional_2d_to_convolutional_2d import Convolutional2DToConvolutional2D
+from manim_ml.neural_network.layers.convolutional_2d_to_feed_forward import Convolutional2DToFeedForward
+from manim_ml.neural_network.layers.convolutional_2d_to_max_pooling_2d import Convolutional2DToMaxPooling2D
+from manim_ml.neural_network.layers.convolutional_2d import Convolutional2DLayer
+from manim_ml.neural_network.layers.embedding_to_feed_forward import EmbeddingToFeedForward
+from manim_ml.neural_network.layers.embedding import EmbeddingLayer
+from manim_ml.neural_network.layers.feed_forward_to_embedding import FeedForwardToEmbedding
+from manim_ml.neural_network.layers.feed_forward_to_feed_forward import FeedForwardToFeedForward
+from manim_ml.neural_network.layers.feed_forward_to_image import FeedForwardToImage
+from manim_ml.neural_network.layers.feed_forward_to_vector import FeedForwardToVector
+from manim_ml.neural_network.layers.feed_forward import FeedForwardLayer
+from manim_ml.neural_network.layers.image_to_convolutional_2d import ImageToConvolutional2DLayer
+from manim_ml.neural_network.layers.image_to_feed_forward import ImageToFeedForward
+from manim_ml.neural_network.layers.image import ImageLayer
+from manim_ml.neural_network.layers.max_pooling_2d_to_convolutional_2d import MaxPooling2DToConvolutional2D
+from manim_ml.neural_network.layers.max_pooling_2d import MaxPooling2DLayer
+from manim_ml.neural_network.layers.paired_query_to_feed_forward import PairedQueryToFeedForward
+from manim_ml.neural_network.layers.paired_query import PairedQueryLayer
+from manim_ml.neural_network.layers.triplet_to_feed_forward import TripletToFeedForward
+from manim_ml.neural_network.layers.triplet import TripletLayer
+from manim_ml.neural_network.layers.vector import VectorLayer

manim_ml/neural_network/architectures/feed_forward.py

@@ -0,0 +1,15 @@
+from manim_ml.neural_network.layers.feed_forward import FeedForwardLayer
+
+class FeedForwardNeuralNetwork(NeuralNetwork):
+    """NeuralNetwork with just feed forward layers"""
+
+    def __init__(self, layer_node_count, node_radius=0.08, node_color=BLUE, **kwargs):
+        # construct layers
+        layers = []
+        for num_nodes in layer_node_count:
+            layer = FeedForwardLayer(
+                num_nodes, node_color=node_color, node_radius=node_radius
+            )
+            layers.append(layer)
+        # call super class
+        super().__init__(layers, **kwargs)

manim_ml/neural_network/neural_network.py

@@ -339,18 +339,3 @@ class NeuralNetwork(Group):
 
         string_repr = "NeuralNetwork([\n" + inner_string + "])"
         return string_repr
-
-
-class FeedForwardNeuralNetwork(NeuralNetwork):
-    """NeuralNetwork with just feed forward layers"""
-
-    def __init__(self, layer_node_count, node_radius=0.08, node_color=BLUE, **kwargs):
-        # construct layers
-        layers = []
-        for num_nodes in layer_node_count:
-            layer = FeedForwardLayer(
-                num_nodes, node_color=node_color, node_radius=node_radius
-            )
-            layers.append(layer)
-        # call super class
-        super().__init__(layers, **kwargs)

tests/test_feed_forward.py

@@ -0,0 +1,14 @@
+from manim import *
+
+from manim_ml.neural_network import NeuralNetwork, FeedForwardLayer
+
+class FeedForwardScene(Scene):
+
+    def construct(self):
+        nn = NeuralNetwork([
+            FeedForwardLayer(3),
+            FeedForwardLayer(5),
+            FeedForwardLayer(3)
+        ])
+
+        self.add(nn)