




"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


a							      =     {
    '''configuration_graphormer''': ['''GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GraphormerConfig'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a							      =     [
           '''GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''GraphormerForGraphClassification''',
           '''GraphormerModel''',
           '''GraphormerPreTrainedModel''',
       ]


if TYPE_CHECKING:
       from .configuration_graphormer import GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, GraphormerConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_graphormer import (
                  GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  GraphormerForGraphClassification,
                  GraphormerModel,
                  GraphormerPreTrainedModel,
              )


else:
       import sys

       a							      =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





import warnings

from ...utils import is_sklearn_available, requires_backends


if is_sklearn_available():
     from scipy.stats import pearsonr, spearmanr
     from sklearn.metrics import fa_score, matthews_corrcoef


snake_case							:       List[str]										=	(
    '''This metric will be removed from the library soon, metrics should be handled with the 🤗 Evaluate '''
    '''library. You can have a look at this example script for pointers: '''
    '''https://github.com/huggingface/transformers/blob/main/examples/pytorch/text-classification/run_glue.py'''
)
def 							__lowerCamelCase		(					UpperCAmelCase_		:						List[str]					,    UpperCAmelCase_		:						Optional[Any]		):




      """simple docstring"""





      warnings.warn(UpperCAmelCase_					,    UpperCAmelCase_		)
      requires_backends(UpperCAmelCase_					,    '''sklearn'''		)
      return (preds == labels).mean()
def 							__lowerCamelCase		(					UpperCAmelCase_		:						str					,    UpperCAmelCase_		:						int		):




      """simple docstring"""





      warnings.warn(UpperCAmelCase_					,    UpperCAmelCase_		)
      requires_backends(UpperCAmelCase_					,    '''sklearn'''		)
      a		:Dict									=			simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)
      a		:Any									=			fa_score(y_true=UpperCAmelCase_					,    y_pred=UpperCAmelCase_		)
      return {
          "acc": acc,
          "f1": fa,
          "acc_and_f1": (acc + fa) / 2,
      }
def 							__lowerCamelCase		(					UpperCAmelCase_		:						Dict					,    UpperCAmelCase_		:						List[Any]		):




      """simple docstring"""





      warnings.warn(UpperCAmelCase_					,    UpperCAmelCase_		)
      requires_backends(UpperCAmelCase_					,    '''sklearn'''		)
      a		:str									=			pearsonr(UpperCAmelCase_					,    UpperCAmelCase_		)[0]
      a		:Union[str, Any]									=			spearmanr(UpperCAmelCase_					,    UpperCAmelCase_		)[0]
      return {
          "pearson": pearson_corr,
          "spearmanr": spearman_corr,
          "corr": (pearson_corr + spearman_corr) / 2,
      }
def 							__lowerCamelCase		(					UpperCAmelCase_		:						int					,    UpperCAmelCase_		:						int					,    UpperCAmelCase_		:						Dict		):




      """simple docstring"""





      warnings.warn(UpperCAmelCase_					,    UpperCAmelCase_		)
      requires_backends(UpperCAmelCase_					,    '''sklearn'''		)
      assert len(UpperCAmelCase_		) == len(UpperCAmelCase_		), F'''Predictions and labels have mismatched lengths {len(UpperCAmelCase_		)} and {len(UpperCAmelCase_		)}'''
      if task_name == "cola":
            return {"mcc": matthews_corrcoef(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "sst-2":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "mrpc":
            return acc_and_fa(UpperCAmelCase_					,    UpperCAmelCase_		)
      elif task_name == "sts-b":
            return pearson_and_spearman(UpperCAmelCase_					,    UpperCAmelCase_		)
      elif task_name == "qqp":
            return acc_and_fa(UpperCAmelCase_					,    UpperCAmelCase_		)
      elif task_name == "mnli":
            return {"mnli/acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "mnli-mm":
            return {"mnli-mm/acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "qnli":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "rte":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "wnli":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      elif task_name == "hans":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      else:
            raise KeyError(UpperCAmelCase_		)






def 							__lowerCamelCase		(					UpperCAmelCase_		:						List[str]					,    UpperCAmelCase_		:						int					,    UpperCAmelCase_		:						List[Any]		):




      """simple docstring"""





      warnings.warn(UpperCAmelCase_					,    UpperCAmelCase_		)
      requires_backends(UpperCAmelCase_					,    '''sklearn'''		)
      if len(UpperCAmelCase_		) != len(UpperCAmelCase_		):
            raise ValueError(F'''Predictions and labels have mismatched lengths {len(UpperCAmelCase_		)} and {len(UpperCAmelCase_		)}'''		)
      if task_name == "xnli":
            return {"acc": simple_accuracy(UpperCAmelCase_					,    UpperCAmelCase_		)}
      else:
            raise KeyError(UpperCAmelCase_		)





