input: 
  def linear_regression_nn(input_dim: int, output_dim: int) -> LinearRegressionModel:
      """
      Create a neural network class in Python to model a linear regression function.
      The class should initialize the weights and bias, and implement a forward pass method.
      
      >>> model = linear_regression_nn(3, 1)
      >>> model.weights
      array([[0.],
             [0.],
             [0.]])
      >>> model.bias
      array([[0.]])
      >>> model.forward(np.array([[1, 2, 3]]))
      array([[0.]])
      """
  
output:     import numpy as np
  
      class LinearRegressionModel:
          def __init__(self, input_dim, output_dim):
              self.weights = np.zeros((input_dim, output_dim))
              self.bias = np.zeros((1, output_dim))
          
          def forward(self, x):
              return np.dot(x, self.weights) + self.bias
  
      return LinearRegressionModel(input_dim, output_dim)