input: def Create_Linear_Regression_Model():
      """
      Create a neural network class in Python to model a linear regression function.
      The class should initialize the weights and bias for the linear regression model and
      compute the forward pass.
  
      Example:
      for Create_Linear_Regression_Model() == [
          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
      ]
      """
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