Refactoring

Project_Model/Libs/Transformer/Classes/FeedForwardNetwork.py

@@ -0,0 +1,43 @@
+# it is position wise!
+# https://stackoverflow.com/questions/74979359/how-is-position-wise-feed-forward-neural-network-implemented-for-transformers
+
+# Why do we need a fixed size
+# https://ai.stackexchange.com/questions/37624/why-do-transformers-have-a-fixed-input-length
+
+import torch.nn as nn
+
+
+class FeedForwardNetwork(nn.Module):
+
+    def __init__(self, embedding_size: int, feed_forward_hidden_layer_dimension: int):
+
+        super().__init__()
+        self.__fully_connected_1 = nn.Linear(
+            embedding_size, feed_forward_hidden_layer_dimension
+        )  # expand in higher dimension
+
+        self.__relu = nn.ReLU()
+        self.__dropout = nn.Dropout(
+            0.1
+        )  # during training we drop something, with eval it got deactivated
+
+        self.__fully_connected_2 = nn.Linear(
+            feed_forward_hidden_layer_dimension, embedding_size
+        )  # return into the model dimension
+
+    def forward(self, x):
+        # -> NN1 -> RELU -> (Droput during training) -> NN2 ->
+
+        # 1) Linear Layer
+        x = self.__fully_connected_1(x)
+
+        # 2) ReLU
+        x = self.__relu(x)
+
+        # 3) Dropout
+        x = self.__dropout(x)
+
+        # 4) Linear Layer
+        x = self.__fully_connected_2(x)
+
+        return x