ksuit.writers.log_writer
========================

.. py:module:: ksuit.writers.log_writer


Classes
-------

.. autoapisummary::

   ksuit.writers.log_writer.LogWriter


Module Contents
---------------

.. py:class:: LogWriter(path_provider, update_counter, tracker)

   Writes logs into a local file and (optionally) to an online webinterface (identified via the `tracker`).
   All logs that should be written for a certain update in the training will be cached and written to the `tracker`
   all at once. For writing the logs to disk, everything for the full training process is cached and only after
   training finished, the logs are written to disk (writing repeatedly to disk takes a long time).

   :param path_provider: Provides the path to store all logs to the disk after training.
   :param update_counter: Provides the current training progress add the current epoch/update/sample to every log entry.
                          This allows, e.g., changing the x-axis to "epoch" in online visiualization tools.
   :param tracker: Provides an interface for logging to an online experiment tracking platform.


   .. py:attribute:: logger


   .. py:attribute:: path_provider


   .. py:attribute:: update_counter


   .. py:attribute:: tracker


   .. py:attribute:: log_entries
      :type:  list[dict[str, Any]]
      :value: []



   .. py:attribute:: log_cache
      :type:  dict[str, Any] | None
      :value: None



   .. py:attribute:: non_scalar_keys
      :type:  set[str]


   .. py:method:: get_all_metric_values(key)

      Retrieves all values of a metric from all log entries. Used mainly for integration tests.

      :param key: Identifier of the metric.

      :returns: The values of the metric over the course of training. Log entries that do not contain the key are skipped.



   .. py:method:: finish()

      Stores all logs from the training to the disk.



   .. py:method:: flush()

      Composes a log entry with all metrics that were calculated for the current training state. This method is
      called after every update and if no metrics were logged, it simply does nothing.



   .. py:method:: add_scalar(key, value, logger = None, format_str = None)

      Adds a scalar value to the log.
      :param key: Metric identifier.
      :param value: Scalar tensor or float with the value that should be logged.
      :param logger: If defined, will log the value to stdout.
      :param format_str: If defined, will alter the log to stdout to be in the provided format.



   .. py:method:: add_nonscalar(key, value)

      Adds a non-scalar value to the log.
      :param key: Metric identifier.
      :param value: Non-scalar value that should be logged (e.g., wandb.Image, wandb.Histogram, ...).