Python utils.save_variables方法代码示例

# 需要导入模块: from src import utils [as 别名]
# 或者: from src.utils import save_variables [as 别名]
def save_d_at_t(outputs, global_step, output_dir, metric_summary, N):
  """Save distance to goal at all time steps.
  
  Args:
    outputs        : [gt_dist_to_goal].
    global_step : number of iterations.
    output_dir     : output directory.
    metric_summary : to append scalars to summary.
    N              : number of outputs to process.

  """
  d_at_t = np.concatenate(map(lambda x: x[0][:,:,0]*1, outputs), axis=0)
  fig, axes = utils.subplot(plt, (1,1), (5,5))
  axes.plot(np.arange(d_at_t.shape[1]), np.mean(d_at_t, axis=0), 'r.')
  axes.set_xlabel('time step')
  axes.set_ylabel('dist to next goal')
  axes.grid('on')
  file_name = os.path.join(output_dir, 'dist_at_t_{:d}.png'.format(global_step))
  with fu.fopen(file_name, 'w') as f:
    fig.savefig(f, bbox_inches='tight', transparent=True, pad_inches=0)
  file_name = os.path.join(output_dir, 'dist_at_t_{:d}.pkl'.format(global_step))
  utils.save_variables(file_name, [d_at_t], ['d_at_t'], overwrite=True)
  plt.close(fig)
  return None 

# 需要导入模块: from src import utils [as 别名]
# 或者: from src.utils import save_variables [as 别名]
def save_all(outputs, global_step, output_dir, metric_summary, N):
  """Save numerous statistics.
  
  Args:
    outputs        : [locs, goal_loc, gt_dist_to_goal, node_ids, perturbs]
    global_step    : number of iterations.
    output_dir     : output directory.
    metric_summary : to append scalars to summary.
    N              : number of outputs to process.
  """
  all_locs = np.concatenate(map(lambda x: x[0], outputs), axis=0)
  all_goal_locs = np.concatenate(map(lambda x: x[1], outputs), axis=0)
  all_d_at_t = np.concatenate(map(lambda x: x[2][:,:,0]*1, outputs), axis=0)
  all_node_ids = np.concatenate(map(lambda x: x[3], outputs), axis=0)
  all_perturbs = np.concatenate(map(lambda x: x[4], outputs), axis=0)
  
  file_name = os.path.join(output_dir, 'all_locs_at_t_{:d}.pkl'.format(global_step))
  vars = [all_locs, all_goal_locs, all_d_at_t, all_node_ids, all_perturbs]
  var_names = ['all_locs', 'all_goal_locs', 'all_d_at_t', 'all_node_ids', 'all_perturbs']
  utils.save_variables(file_name, vars, var_names,  overwrite=True)
  return None 

# 需要导入模块: from src import utils [as 别名]
# 或者: from src.utils import save_variables [as 别名]
def _write_map_files(b_in, b_out, transform):
  cats = get_categories()

  env = utils.Foo(padding=10, resolution=5, num_point_threshold=2,
                  valid_min=-10, valid_max=200, n_samples_per_face=200)
  robot = utils.Foo(radius=15, base=10, height=140, sensor_height=120,
                    camera_elevation_degree=-15)
  
  building_loader = factory.get_dataset('sbpd')
  for flip in [False, True]:
    b = nav_env.Building(b_out, robot, env, flip=flip,
                         building_loader=building_loader)
    logging.info("building_in: %s, building_out: %s, transform: %d", b_in,
                 b_out, transform)
    maps = _get_semantic_maps(b_in, transform, b.map, flip, cats)
    maps = np.transpose(np.array(maps), axes=[1,2,0])

    #  Load file from the cache.
    file_name = '{:s}_{:d}_{:d}_{:d}_{:d}_{:d}_{:d}.pkl'
    file_name = file_name.format(b.building_name, b.map.size[0], b.map.size[1],
                                 b.map.origin[0], b.map.origin[1],
                                 b.map.resolution, flip)
    out_file = os.path.join(DATA_DIR, 'processing', 'class-maps', file_name)
    logging.info('Writing semantic maps to %s.', out_file)
    save_variables(out_file, [maps, cats], ['maps', 'cats'], overwrite=True) 

# 需要导入模块: from src import utils [as 别名]
# 或者: from src.utils import save_variables [as 别名]
def write_room_dimensions(b_in, b_out, transform):
  rooms = get_room_in_building(b_in)
  room_dimension = {}
  for r in rooms:
    room = load_room(b_in, r, category_list=None)
    vertex = np.concatenate(room['vertexs'], axis=0)
    room_dimension[r] = np.concatenate((np.min(vertex, axis=0), np.max(vertex, axis=0)), axis=0)
  if transform == 1:
    room_dimension = _transform_area5b(room_dimension)
  
  out_file = os.path.join(DATA_DIR, 'processing', 'room-dimension', b_out+'.pkl')
  save_variables(out_file, [room_dimension], ['room_dimension'], overwrite=True)