Add feedforwarding method

1 files changed, 18 insertions, 6 deletions

diff --git a/neural_network.py b/neural_network.py
index 827b066..3ca1c64 100644
--- a/neural_network.py
+++ b/neural_network.py
@@ -1,4 +1,5 @@
 import numpy as np
+from scipy.special import expit
 from utils import random_array
 
 CYRILLIC_ALPHABET = ['I', 'А', 'Б', 'В', 'Г', 'Д', 'Е', 'Ë', 'Ж', 'З',
@@ -21,30 +22,41 @@ class NeuralNetwork:
     Train the neural network. It loads the dataset contained in ./data,
     converts each image into a numpy array and uses that data for training.
     """
-    def train():
+    def train(self):
         pass
 
     """
     Guess the letter contained in the image file pointed by
     input_image (a path).
     """
-    def guess(input_image: str) -> str:
+    def guess(self, input_image: str) -> str:
         pass
 
     """
     Save the weights to a csv file.
     """
-    def save():
+    def save(self):
         pass
 
     """
     Load the weights from a csv file.
     """
-    def load(weights_file: str):
+    def load(self, weights_file: str):
         pass
 
     """
     Feedforwarding.
     """
-    def _predict(input_layer: np.array):
-        pass
+    def _predict(self, input_layer: np.array):
+        hidden_layer_inputs = np.dot(input_layer, self._hidden_weights)
+        hidden_layer_outputs = self._get_layer_output(hidden_layer_inputs)
+        output_layer_inputs = np.dot(self._output_weights, hidden_layer_outputs)
+
+        # The output layer outputs. (Final output of the neural network).
+        return self._get_layer_output(output_layer_inputs)
+
+    """
+    Apply the sigmoid function to a given layer
+    """
+    def _get_layer_output(self, layer: np.array):
+        return expit(layer)