input: Write a function to filter out all negative numbers from a given matrix and return the modified matrix with all negative numbers replaced by zeroes.
  
  def filter_out_negative(matrix):
    # Convert matrix to numpy array
    import numpy as np
    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]]), np.array([[0, 2, 0], [0, 5, 6], [0, 8, 9]]))
  assert np.array_equal(filter_out_negative([[1, -2, 3], [-4, -5, 6], [7, -8, 9]]), np.array([[1, 0, 3], [0, 0, 6], [7, 0, 9]]))
  assert np.array_equal(filter_out_negative([]), np.array([]))
  assert np.array_equal(filter_out_negative([[1, 2, 3], [4, 5, 6], [7, 8, 9]]), np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]))
  assert np.array_equal(filter_out_negative([[-1, -2, -3], [-4, -5, -6], [-7, -8, -9]]), np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0]]))
output: def filter_out_negative(matrix):
    import numpy as np
    matrix = np.array(matrix)
    matrix[matrix < 0] = 0
    return matrix