diff options
| -rw-r--r-- | neural_network.py | 24 |
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) |