input: from typing import List
  
  def linear_regression_forward(input_data: List[List[float]], weights: List[float], bias: float) -> List[float]:
      """ Perform a forward pass using the given weights and bias on the list of input data.
      Each list in input_data represents a row with features.
      >>> linear_regression_forward([[1.0, 2.0], [3.0, 4.0]], [0.5, 0.5], 1.0)
      [2.5, 4.5]
      >>> linear_regression_forward([[0.0, 0.0], [1.0, 1.0]], [1.0, 1.0], 0.0)
      [0.0, 2.0]
      """
output:     results = []
      for row in input_data:
          result = sum(w * x for w, x in zip(weights, row)) + bias
          results.append(result)
      return results