input: Write a python function to perform matrix multiplication and addition with bias using TensorFlow.
  assert np.allclose(my_function(np.array([[1, 2], [3, 4]]), np.array([[0.1, 0.2], [0.3, 0.4]]), np.array([0.1, 0.2])), np.array([[0.8, 1.2], [1.8, 2.6]]))
  assert np.allclose(my_function(np.array([[2, 0], [1, 3]]), np.array([[0.5, 0.1], [0.2, 0.4]]), np.array([0.2, 0.3])), np.array([[1.2, 0.5], [1.7, 1.7]]))
  assert np.allclose(my_function(np.array([[0, -1], [2, 3]]), np.array([[0.6, 0.7], [0.8, 0.9]]), np.array([0.4, 0.5])), np.array([[-0.4, -0.4], [3.4, 4.2]]))
output: import tensorflow as tf
  import numpy as np
  
  def my_function(A, B, bias):
      A_tf = tf.constant(A, dtype=tf.float32)
      B_tf = tf.constant(B, dtype=tf.float32)
      bias_tf = tf.constant(bias, dtype=tf.float32)
      
      result = tf.matmul(A_tf, B_tf) + bias_tf
      return result.numpy()