input: Write a function to filter out all negative numbers from the given matrix. The function should return the matrix with all negative numbers replaced by zero. Use numpy for handling the matrix. If the matrix is empty, return an empty matrix.
  
  import numpy as np
  
  def filter_out_negative(matrix):
      if not matrix:
          return np.array([])
      matrix = np.array(matrix)
      matrix[matrix < 0] = 0
      return matrix
  
  assert np.array_equal(filter_out_negative([[-1, 2, -3], [-4, 5, 6], [-7, 8, 9]]), np.array([[0, 2, 0], [0, 5, 6], [0, 8, 9]]))
  assert np.array_equal(filter_out_negative([[1, -2], [-3, 4]]), np.array([[1, 0], [0, 4]]))
  assert np.array_equal(filter_out_negative([[0, 0, 0], [0, 0, 0]]), np.array([[0, 0, 0], [0, 0, 0]]))
  assert np.array_equal(filter_out_negative([]), np.array([]))
  assert np.array_equal(filter_out_negative([[1, 2, 3], [4, 5, 6]]), np.array([[1, 2, 3], [4, 5, 6]]))
output: import numpy as np
  
  def filter_out_negative(matrix):
      if not matrix:
          return np.array([])
      matrix = np.array(matrix)
      matrix[matrix < 0] = 0
      return matrix