'''simple docstring'''


import logging
import os
import sys
import threading
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

from tqdm import auto as tqdm_lib


snake_case__     :			Optional[int]      			=  threading.Lock()
snake_case__     :			Optional[logging.Handler]      			=  None

snake_case__     :			Optional[int]      			=  {
    '''debug''': logging.DEBUG,
    '''info''': logging.INFO,
    '''warning''': logging.WARNING,
    '''error''': logging.ERROR,
    '''critical''': logging.CRITICAL,
}

snake_case__     :			List[Any]      			=  logging.WARNING

snake_case__     :			Optional[int]      			=  True


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     UpperCAmelCase_							:   int   =      os.getenv('DIFFUSERS_VERBOSITY'	,     UpperCAmelCase__   )
     if env_level_str:
          if env_level_str in log_levels:
               return log_levels[env_level_str]
          else:
               logging.getLogger().warning(
                   F'''Unknown option DIFFUSERS_VERBOSITY={env_level_str}, '''
                   F'''has to be one of: { ', '.join(log_levels.keys()   ) }'''   )
     return _default_log_level


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     return __name__.split('.'   )[0]


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     return logging.getLogger(_get_library_name()   )


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     global _default_handler

     with _lock:
          if _default_handler:
               # This library has already configured the library root logger.
               return
          UpperCAmelCase_							:   Any   =      logging.StreamHandler()  # Set sys.stderr as stream.
          UpperCAmelCase_							:   Tuple   =      sys.stderr.flush

          # Apply our default configuration to the library root logger.
          UpperCAmelCase_							:   Union[str, Any]   =      _get_library_root_logger()
          library_root_logger.addHandler(_default_handler   )
          library_root_logger.setLevel(_get_default_logging_level()   )
          UpperCAmelCase_							:   Any   =      False


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     global _default_handler

     with _lock:
          if not _default_handler:
               return

          UpperCAmelCase_							:   Dict   =      _get_library_root_logger()
          library_root_logger.removeHandler(_default_handler   )
          library_root_logger.setLevel(logging.NOTSET   )
          UpperCAmelCase_							:   List[str]   =      None


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     return log_levels


def 					_lowerCamelCase    (      lowerCamelCase_					:							Optional[str] = None   ):



     """simple docstring"""





     if name is None:
          UpperCAmelCase_							:   Dict   =      _get_library_name()

     _configure_library_root_logger()
     return logging.getLogger(UpperCAmelCase__   )


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     _configure_library_root_logger()
     return _get_library_root_logger().getEffectiveLevel()


def 					_lowerCamelCase    (      lowerCamelCase_					:							int   ):



     """simple docstring"""





     _configure_library_root_logger()
     _get_library_root_logger().setLevel(UpperCAmelCase__   )


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     return set_verbosity(UpperCAmelCase__   )


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     return set_verbosity(UpperCAmelCase__   )


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     return set_verbosity(UpperCAmelCase__   )


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     return set_verbosity(UpperCAmelCase__   )


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     _configure_library_root_logger()

     assert _default_handler is not None
     _get_library_root_logger().removeHandler(_default_handler   )


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     _configure_library_root_logger()

     assert _default_handler is not None
     _get_library_root_logger().addHandler(_default_handler   )


def 					_lowerCamelCase    (      lowerCamelCase_					:							logging.Handler   ):



     """simple docstring"""





     _configure_library_root_logger()

     assert handler is not None
     _get_library_root_logger().addHandler(UpperCAmelCase__   )


def 					_lowerCamelCase    (      lowerCamelCase_					:							logging.Handler   ):



     """simple docstring"""





     _configure_library_root_logger()

     assert handler is not None and handler not in _get_library_root_logger().handlers
     _get_library_root_logger().removeHandler(UpperCAmelCase__   )


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     _configure_library_root_logger()
     UpperCAmelCase_							:   Union[str, Any]   =      False


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     _configure_library_root_logger()
     UpperCAmelCase_							:   Dict   =      True


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     UpperCAmelCase_							:   int   =      _get_library_root_logger().handlers

     for handler in handlers:
          UpperCAmelCase_							:   Tuple   =      logging.Formatter('[%(levelname)s|%(filename)s:%(lineno)s] %(asctime)s >> %(message)s'   )
          handler.setFormatter(UpperCAmelCase__   )


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     UpperCAmelCase_							:   List[str]   =      _get_library_root_logger().handlers

     for handler in handlers:
          handler.setFormatter(UpperCAmelCase__   )


def 					_lowerCamelCase    (      self					:							Optional[int]	,     *lowerCamelCase_					:							Optional[Any]	,     **lowerCamelCase_					:							Any   ):



     """simple docstring"""





     UpperCAmelCase_							:   Any   =      os.getenv('DIFFUSERS_NO_ADVISORY_WARNINGS'	,     UpperCAmelCase__   )
     if no_advisory_warnings:
          return
     self.warning(*UpperCAmelCase__	,     **UpperCAmelCase__   )


snake_case__     :			str      			=  warning_advice






class      __SCREAMING_SNAKE_CASE						:







  '''simple docstring'''






  def __init__( self      ,		*snake_case_      ,		**snake_case_						):  # pylint: disable=unused-argument




       '''simple docstring'''

       UpperCAmelCase_							:   Union[str, Any]   =      args[0] if args else None


  def __iter__( self						):




       '''simple docstring'''

       return iter(self._iterator						)


  def __getattr__( self      ,		snake_case_						):




       '''simple docstring'''

       def empty_fn(*snake_case_      ,		**snake_case_						):  # pylint: disable=unused-argument
            return

       return empty_fn


  def __enter__( self						):




       '''simple docstring'''

       return self






  def __exit__( self      ,		snake_case_      ,		snake_case_      ,		snake_case_						):




       '''simple docstring'''

       return







class      __SCREAMING_SNAKE_CASE						:







  '''simple docstring'''






  def __call__( self      ,		*snake_case_      ,		**snake_case_						):




       '''simple docstring'''

       if _tqdm_active:
            return tqdm_lib.tqdm(*_UpperCamelCase      ,		**_UpperCamelCase						)
       else:
            return EmptyTqdm(*_UpperCamelCase      ,		**_UpperCamelCase						)


  def _UpperCamelCase     ( self      ,		*snake_case_      ,		**snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:   List[Any]   =      None
       if _tqdm_active:
            return tqdm_lib.tqdm.set_lock(*_UpperCamelCase      ,		**_UpperCamelCase						)






  def _UpperCamelCase     ( self						):




       '''simple docstring'''

       if _tqdm_active:
            return tqdm_lib.tqdm.get_lock()







snake_case__     :			Tuple      			=  _tqdm_cls()


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     global _tqdm_active
     return bool(_tqdm_active   )


def 					_lowerCamelCase    (      ):



     """simple docstring"""





     global _tqdm_active
     UpperCAmelCase_							:   str   =      True





def 					_lowerCamelCase    (      ):



     """simple docstring"""





     global _tqdm_active
     UpperCAmelCase_							:   Tuple   =      False







from sklearn.metrics import mean_absolute_error

import datasets


_lowerCamelCase    :      Any	 =						'''\
@article{scikit-learn,
 title={Scikit-learn: Machine Learning in {P}ython},
 author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
         and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
         and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
         Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
 journal={Journal of Machine Learning Research},
 volume={12},
 pages={2825--2830},
 year={2011}
}
'''

_lowerCamelCase    :      str	 =						'''\
Mean Absolute Error (MAE) is the mean of the magnitude of difference between the predicted and actual
values.
'''


_lowerCamelCase    :      List[str]	 =						'''
Args:
    predictions: array-like of shape (n_samples,) or (n_samples, n_outputs)
        Estimated target values.
    references: array-like of shape (n_samples,) or (n_samples, n_outputs)
        Ground truth (correct) target values.
    sample_weight: array-like of shape (n_samples,), default=None
        Sample weights.
    multioutput: {"raw_values", "uniform_average"} or array-like of shape (n_outputs,), default="uniform_average"
        Defines aggregating of multiple output values. Array-like value defines weights used to average errors.

                 "raw_values" : Returns a full set of errors in case of multioutput input.

                 "uniform_average" : Errors of all outputs are averaged with uniform weight.

Returns:
    mae : mean absolute error.
        If multioutput is "raw_values", then mean absolute error is returned for each output separately. If multioutput is "uniform_average" or an ndarray of weights, then the weighted average of all output errors is returned.
        MAE output is non-negative floating point. The best value is 0.0.
Examples:

    >>> mae_metric = datasets.load_metric("mae")
    >>> predictions = [2.5, 0.0, 2, 8]
    >>> references = [3, -0.5, 2, 7]
    >>> results = mae_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'mae\': 0.5}

    If you\'re using multi-dimensional lists, then set the config as follows :

    >>> mae_metric = datasets.load_metric("mae", "multilist")
    >>> predictions = [[0.5, 1], [-1, 1], [7, -6]]
    >>> references = [[0, 2], [-1, 2], [8, -5]]
    >>> results = mae_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'mae\': 0.75}
    >>> results = mae_metric.compute(predictions=predictions, references=references, multioutput=\'raw_values\')
    >>> print(results)
    {\'mae\': array([0.5, 1. ])}
'''


@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION ,				_KWARGS_DESCRIPTION   )
class   lowercase			(   datasets.Metric   ):




							def 		__snake_case(  self      :    int					)    -> str:



												'''simple docstring'''

												return datasets.MetricInfo(
												    description=_DESCRIPTION		,							citation=_CITATION		,							inputs_description=_KWARGS_DESCRIPTION		,							features=datasets.Features(self._get_feature_types()					)		,							reference_urls=[
												        "https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html"
												    ]		,							)




							def 		__snake_case(  self      :    int					)    -> Tuple:



												'''simple docstring'''

												if self.config_name == "multilist":
																	return {
																	    "predictions": datasets.Sequence(datasets.Value("float"					)					),
																	    "references": datasets.Sequence(datasets.Value("float"					)					),
																	}
												else:
																	return {
																	    "predictions": datasets.Value("float"					),
																	    "references": datasets.Value("float"					),
																	}





							def 		__snake_case(  self      :    Tuple		,							_UpperCamelCase      :    List[str]		,							_UpperCamelCase      :    List[Any]		,							_UpperCamelCase      :    str=None		,							_UpperCamelCase      :    Any="uniform_average"					)    -> int:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE				=				mean_absolute_error(_UpperCamelCase		,							_UpperCamelCase		,							sample_weight=_UpperCamelCase		,							multioutput=_UpperCamelCase					)

												return {"mae": mae_score}




