[nabla9]

prompt:

  def general_artificial_intelligence_main_loop(state_tensor, input_tensor):

result:

  def general_artificial_intelligence_main_loop(state_tensor, input_tensor):
    state_matrix = state_tensor.contiguous().view(-1, state_tensor.size(-1))
    action_space = generate_discrete_action_space(
        state_matrix, action_space_type='grid-world')
    reward_matrix = action_space.action_space.observation_to_values(input_tensor)
    next_state_matrix = fml.identity(state_matrix)
    state_tensor_copy = state_matrix.clone()