@@ -82,16 +82,35 @@ def default(self, o):
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class EvaluationTracker :
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- """
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- Keeps track of the overall evaluation process and relevant informations.
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+ """Keeps track of the overall evaluation process and relevant information.
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- The [`EvaluationTracker`] contains specific loggers for experiments details
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- ([`DetailsLogger`]), metrics ([`MetricsLogger`]), task versions
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- ([`VersionsLogger`]) as well as for the general configurations of both the
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- specific task ([`TaskConfigLogger`]) and overall evaluation run
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- ([`GeneralConfigLogger`]). It compiles the data from these loggers and
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+ The [`~logging.evaluation_tracker. EvaluationTracker`] contains specific loggers for experiments details
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+ ([`~logging.evaluation_tracker. DetailsLogger`]), metrics ([`~logging.evaluation_tracker. MetricsLogger`]), task versions
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+ ([`~logging.evaluation_tracker. VersionsLogger`]) as well as for the general configurations of both the
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+ specific task ([`~logging.evaluation_tracker. TaskConfigLogger`]) and overall evaluation run
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+ ([`~logging.evaluation_tracker. GeneralConfigLogger`]). It compiles the data from these loggers and
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writes it to files, which can be published to the Hugging Face hub if
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requested.
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+
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+ Args:
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+ output_dir (`str`): Local folder path where you want results to be saved.
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+ save_details (`bool`, defaults to True): If True, details are saved to the `output_dir`.
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+ push_to_hub (`bool`, defaults to False): If True, details are pushed to the hub.
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+ Results are pushed to `{hub_results_org}/details__{sanitized model_name}` for the model `model_name`, a public dataset,
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+ if `public` is True else `{hub_results_org}/details__{sanitized model_name}_private`, a private dataset.
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+ push_to_tensorboard (`bool`, defaults to False): If True, will create and push the results for a tensorboard folder on the hub.
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+ hub_results_org (`str`, *optional*): The organisation to push the results to.
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+ See more details about the datasets organisation in [`EvaluationTracker.save`].
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+ tensorboard_metric_prefix (`str`, defaults to "eval"): Prefix for the metrics in the tensorboard logs.
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+ public (`bool`, defaults to False): If True, results and details are pushed to public orgs.
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+ nanotron_run_info ([`~nanotron.config.GeneralArgs`], *optional*): Reference to information about Nanotron models runs.
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+
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+ **Attributes**:
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+ - **details_logger** ([`~logging.info_loggers.DetailsLogger`]) -- Logger for experiment details.
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+ - **metrics_logger** ([`~logging.info_loggers.MetricsLogger`]) -- Logger for experiment metrics.
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+ - **versions_logger** ([`~logging.info_loggers.VersionsLogger`]) -- Logger for task versions.
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+ - **general_config_logger** ([`~logging.info_loggers.GeneralConfigLogger`]) -- Logger for general configuration.
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+ - **task_config_logger** ([`~logging.info_loggers.TaskConfigLogger`]) -- Logger for task configuration.
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"""
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def __init__ (
@@ -105,23 +124,7 @@ def __init__(
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public : bool = False ,
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nanotron_run_info : "GeneralArgs" = None ,
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) -> None :
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- """
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- Creates all the necessary loggers for evaluation tracking.
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-
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- Args:
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- output_dir (str): Local folder path where you want results to be saved
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- save_details (bool): If True, details are saved to the output_dir
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- push_to_hub (bool): If True, details are pushed to the hub.
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- Results are pushed to `{hub_results_org}/details__{sanitized model_name}` for the model `model_name`, a public dataset,
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- if `public` is True else `{hub_results_org}/details__{sanitized model_name}_private`, a private dataset.
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- push_results_to_tensorboard (bool): If True, will create and push the results for a tensorboard folder on the hub
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- hub_results_org (str): The organisation to push the results to. See
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- more details about the datasets organisation in
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- [`EvaluationTracker.save`]
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- tensorboard_metric_prefix (str): Prefix for the metrics in the tensorboard logs
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- public (bool): If True, results and details are pushed in private orgs
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- nanotron_run_info (GeneralArgs): Reference to informations about Nanotron models runs
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- """
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+ """Creates all the necessary loggers for evaluation tracking."""
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self .details_logger = DetailsLogger ()
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self .metrics_logger = MetricsLogger ()
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self .versions_logger = VersionsLogger ()
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