def METHOD_NAME(self, inputs):
    self.layers[0].activations = inputs
    for i in range(self.num_layers - 1):
        self.layers[i].add_bias(
            self.batch_size, self.layers[i + 1].num_nodes_in_layer
        )
        temp = np.add(
            np.matmul(self.layers[i].activations, self.layers[i].weights_for_layer),
            self.layers[i].bias_for_layer,
        )
        if self.layers[i + 1].activation_function == "sigmoid":
            self.layers[i + 1].activations = self.sigmoid(temp)
        elif self.layers[i + 1].activation_function == "softmax":
            self.layers[i + 1].activations = self.softmax(temp)
        elif self.layers[i + 1].activation_function == "relu":
            self.layers[i + 1].activations = self.relu(temp)
        elif self.layers[i + 1].activation_function == "tanh":
            self.layers[i + 1].activations = self.tanh(temp)
        else:
            self.layers[i + 1].activations = temp