input: def LinearRegressionModel(input_dim: int, output_dim: int):
      """
      Create a neural network class in Python to model a linear regression function.
      The class initializes the weights and bias for a linear regression model,
      and it includes a forward method to compute the output given input data.
      
      >>> model = LinearRegressionModel(3, 2)
      >>> model.weights
      array([[0., 0.],
             [0., 0.],
             [0., 0.]])
      >>> model.bias
      array([[0., 0.]])
      >>> model.forward(np.array([[1, 2, 3]]))
      array([[0., 0.]])
      """
      import numpy as np
      
      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):
          out = np.dot(x, self.weights) + self.bias
          return out
output:     return type('LinearRegressionModel', (object,), {
          '__init__': __init__,
          'forward': forward
      })()