utils.log_helper

log_helper

Please Reference ding/ding/utils/log_helper.py for usage.

build_logger

Overview:

Build text logger and tensorboard logger.

Arguments:

• path (str): Logger(Textlogger & SummaryWriter)’s saved dir

• name (str): The logger file name

• need_tb (bool): Whether SummaryWriter instance would be created and returned

• need_text (bool): Whether loggingLogger instance would be created and returned

• text_level (int` or str): Logging level of logging.Logger, default set to logging.INFO

Returns:

• logger (Optional[logging.Logger]): Logger that displays terminal output

• tb_logger (Optional['SummaryWriter']): Saves output to tfboard, only return when need_tb.

LoggerFactory

ding.utils.log_helper.LoggerFactory.create_logger(path: str, name: str = 'default', level: Union[int, str] = 20) → logging.Logger

Overview:

Create logger using logging

Arguments:

• name (str): Logger’s name

• path (str): Logger’s save dir

• level (int or str): Used to set the level. Reference: Logger.setLevel method.

Returns:

• (logging.Logger): new logging logger

ding.utils.log_helper.LoggerFactory.get_tabulate_vars(variables: Dict[str, Any]) → str

Overview:

Get the text description in tabular form of all vars

Arguments:

• variables (List[str]): Names of the vars to query.

Returns:

• string (str): Text description in tabular form of all vars

DistributionTimeImage

Overview:

DistributionTimeImage can be used to store images accorrding to time_steps, for data with 3 dims``(time, category, value)``

Interface:

__init__, add_one_time_step, get_image

ding.utils.log_helper.DistributionTimeImage.__init__(self, maxlen: int = 600, val_range: Optional[dict] = None)

Overview:

Init the DistributionTimeImage class

Arguments:

• maxlen (int): The max length of data inputs

• val_range (dict or None): Dict with val_range['min'] and val_range['max'].

ding.utils.log_helper.DistributionTimeImage.add_one_time_step(self, data: numpy.ndarray) → None

Overview:

Step one timestep in DistributionTimeImage and add the data to distribution image

Arguments:

• data (np.ndarray): The data input

ding.utils.log_helper.DistributionTimeImage.get_image(self) → numpy.ndarray

Overview:

Return the distribution image

Returns:

• img (np.ndarray): The calculated distribution image

pretty_print

Overview:

Print a dict result in a pretty way

Arguments:

• result (dict): The result to print

• direct_print (bool): Whether to print directly

Returns:

• string (str): The pretty-printed result in str format