input: Write a function to filter out all negative numbers from the given matrix. If a number is negative, replace it with 0. The matrix should be converted into a numpy array before performing the filtering operation. The function should return the modified matrix with all negative numbers replaced by 0.
  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([[1, -2, 3], [-4, 5, -6]]), np.array([[1, 0, 3], [0, 5, 0]]))
  assert np.array_equal(filter_out_negative([[-10, -20], [-30, -40]]), np.array([[0, 0], [0, 0]]))
  assert np.array_equal(filter_out_negative([[0, 10, 20], [30, 40, 50]]), np.array([[0, 10, 20], [30, 40, 50]]))
  assert np.array_equal(filter_out_negative([]), np.array([]))
output: 
  def filter_out_negative(matrix):
    matrix = np.array(matrix)
    matrix[matrix < 0] = 0
    return matrix
  