input: Write a function that filters out all negative numbers from a given matrix. Return the modified matrix where all negative numbers are replaced with zeros. If the given matrix is empty, return an empty matrix.
  
  import numpy as np
  
  def filter_out_negative(matrix):
    # Convert matrix to numpy array
    matrix = np.array(matrix)
    # Find all negative numbers and set them to 0
    matrix[matrix < 0] = 0
    return matrix
  
  assert np.array_equal(filter_out_negative([[-1, 2, -3], [-4, 5, 6], [-7, 8, 9]]), [[0, 2, 0], [0, 5, 6], [0, 8, 9]])
  assert np.array_equal(filter_out_negative([[1, -2], [3, -4]]), [[1, 0], [3, 0]])
  assert np.array_equal(filter_out_negative([]), np.array([]))
  assert np.array_equal(filter_out_negative([[5, 6], [7, 8]]), [[5, 6], [7, 8]])
  assert np.array_equal(filter_out_negative([[-1, -2], [-3, -4]]), [[0, 0], [0, 0]])
output: 
  def filter_out_negative(matrix):
    if not matrix:
      return np.array([])
    matrix = np.array(matrix)
    matrix[matrix < 0] = 0
    return matrix
  