simple_nn_update_weights.py

import numpy as np

def update_weights(params, changes, learning_rate=0.01):

  """Updates weights of the layers

    Arguments
    ---------
    params: dict
      Dictionary containing 'w' and 'b'
    changes: dict
      Dictionary containing 'dw' and 'db'
    learning_rate: int, float
      Learning rate for the weight update

    Returns
    -------
    dict
      Dictionary containing updated weights and biases

      The keys for weights and bias arrays in the dict is 'w' and 'b'
  """

  w = params['w']
  b = params['b']
  dw = changes['dw']
  db = changes['db']

  w -= learning_rate*dw
  b -= learning_rate*db

  return {'w': w, 'b': b}