input: Write a function to filter out all negative numbers from the given matrix and return the matrix where all negative numbers are replaced with zeros. The function should use the numpy library to handle the matrix operations.
  
  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]]), np.array([[0, 2, 0], [0, 5, 6], [0, 8, 9]]))
  assert np.array_equal(filter_out_negative([[0, -1, -2], [-3, 4, -5], [6, -7, 8]]), np.array([[0, 0, 0], [0, 4, 0], [6, 0, 8]]))
  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]]), np.array([[0], [0], [0]]))
output: 
  def filter_out_negative(matrix):
    matrix = np.array(matrix)
    matrix[matrix < 0] = 0
    return matrix
  