class Softmax:
  # ...

  def forward(self, input):
    '''
    Performs a forward pass of the softmax layer using the given input.
    Returns a 1d numpy array containing the respective probability values.
    - input can be any array with any dimensions.
    '''
    self.last_input_shape = input.shape

    input = input.flatten()
    self.last_input = input

    input_len, nodes = self.weights.shape

    totals = np.dot(input, self.weights) + self.biases
    self.last_totals = totals

    exp = np.exp(totals)
    return exp / np.sum(exp, axis=0)