


'''simple docstring'''

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


a_						:       Dict      			=				(
    """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 __snake_case      (   UpperCAmelCase_		:		Union[str, Any]      ,       UpperCAmelCase_		:		Any	):
 warnings.warn(UpperCAmelCase_      ,       UpperCAmelCase_	)
 requires_backends(UpperCAmelCase_      ,       "sklearn"	)
 return (preds == labels).mean()





def __snake_case      (   UpperCAmelCase_		:		Any      ,       UpperCAmelCase_		:		Tuple	):
 warnings.warn(UpperCAmelCase_      ,       UpperCAmelCase_	)
 requires_backends(UpperCAmelCase_      ,       "sklearn"	)
 lowerCamelCase_  				=						simple_accuracy(UpperCAmelCase_      ,       UpperCAmelCase_	)
 lowerCamelCase_  				=						fa_score(y_true=UpperCAmelCase_      ,       y_pred=UpperCAmelCase_	)
 return {
     "acc": acc,
     "f1": fa,
     "acc_and_f1": (acc + fa) / 2,
 }





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





def __snake_case      (   UpperCAmelCase_		:		Any      ,       UpperCAmelCase_		:		Optional[Any]      ,       UpperCAmelCase_		:		Optional[int]	):
 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 __snake_case      (   UpperCAmelCase_		:		Any      ,       UpperCAmelCase_		:		Optional[int]      ,       UpperCAmelCase_		:		Optional[int]	):
 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_	)







'''simple docstring'''

import contextlib
import os
import sqlitea

import pytest

from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy





def __snake_case      (   UpperCAmelCase_		:		Optional[int]      ,       UpperCAmelCase_		:		Dict	):
 assert isinstance(UpperCAmelCase_      ,       UpperCAmelCase_	)
 assert dataset.num_rows == 4
 assert dataset.num_columns == 3
 assert dataset.column_names == ["col_1", "col_2", "col_3"]
 for feature, expected_dtype in expected_features.items():
  assert dataset.features[feature].dtype == expected_dtype





@require_sqlalchemy
@pytest.mark.parametrize("keep_in_memory"      ,       [False, True]	)
def __snake_case      (   UpperCAmelCase_		:		Any      ,       UpperCAmelCase_		:		Any      ,       UpperCAmelCase_		:		List[str]      ,       UpperCAmelCase_		:		Union[str, Any]	):
 lowerCamelCase_  				=						tmp_path / "cache"
 lowerCamelCase_  				=						{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
  lowerCamelCase_  				=						SqlDatasetReader(
      "dataset"      ,       "sqlite:///" + sqlite_path      ,       cache_dir=UpperCAmelCase_      ,       keep_in_memory=UpperCAmelCase_	).read()
 _check_sql_dataset(UpperCAmelCase_      ,       UpperCAmelCase_	)





@require_sqlalchemy
@pytest.mark.parametrize(
    "features"      ,       [
        None,
        {"col_1": "string", "col_2": "int64", "col_3": "float64"},
        {"col_1": "string", "col_2": "string", "col_3": "string"},
        {"col_1": "int32", "col_2": "int32", "col_3": "int32"},
        {"col_1": "float32", "col_2": "float32", "col_3": "float32"},
    ]      ,       )
def __snake_case      (   UpperCAmelCase_		:		Any      ,       UpperCAmelCase_		:		Optional[Any]      ,       UpperCAmelCase_		:		List[str]      ,       UpperCAmelCase_		:		str	):
 lowerCamelCase_  				=						tmp_path / "cache"
 lowerCamelCase_  				=						{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 lowerCamelCase_  				=						features.copy() if features else default_expected_features
 lowerCamelCase_  				=						(
     Features({feature: Value(UpperCAmelCase_	) for feature, dtype in features.items()}	) if features is not None else None
 )
 lowerCamelCase_  				=						SqlDatasetReader("dataset"      ,       "sqlite:///" + sqlite_path      ,       features=UpperCAmelCase_      ,       cache_dir=UpperCAmelCase_	).read()
 _check_sql_dataset(UpperCAmelCase_      ,       UpperCAmelCase_	)





def __snake_case      (   UpperCAmelCase_		:		Union[str, Any]	):
 with contextlib.closing(sqlitea.connect(UpperCAmelCase_	)	) as con:
  lowerCamelCase_  				=						con.cursor()
  cur.execute("SELECT * FROM dataset"	)
  for row in cur:
   yield row





@require_sqlalchemy
def __snake_case      (   UpperCAmelCase_		:		Dict      ,       UpperCAmelCase_		:		Optional[Any]      ,       UpperCAmelCase_		:		List[str]	):
 lowerCamelCase_  				=						tmp_path / "cache"
 lowerCamelCase_  				=						os.path.join(UpperCAmelCase_      ,       "tmp.sql"	)
 lowerCamelCase_  				=						SqlDatasetReader("dataset"      ,       "sqlite:///" + sqlite_path      ,       cache_dir=UpperCAmelCase_	).read()
 SqlDatasetWriter(UpperCAmelCase_      ,       "dataset"      ,       "sqlite:///" + output_sqlite_path      ,       num_proc=1	).write()

 lowerCamelCase_  				=						iter_sql_file(UpperCAmelCase_	)
 lowerCamelCase_  				=						iter_sql_file(UpperCAmelCase_	)

 for rowa, rowa in zip(UpperCAmelCase_      ,       UpperCAmelCase_	):
  assert rowa == rowa





@require_sqlalchemy
def __snake_case      (   UpperCAmelCase_		:		Union[str, Any]      ,       UpperCAmelCase_		:		Union[str, Any]      ,       UpperCAmelCase_		:		Tuple	):
 lowerCamelCase_  				=						tmp_path / "cache"
 lowerCamelCase_  				=						os.path.join(UpperCAmelCase_      ,       "tmp.sql"	)
 lowerCamelCase_  				=						SqlDatasetReader("dataset"      ,       "sqlite:///" + sqlite_path      ,       cache_dir=UpperCAmelCase_	).read()
 SqlDatasetWriter(UpperCAmelCase_      ,       "dataset"      ,       "sqlite:///" + output_sqlite_path      ,       num_proc=2	).write()

 lowerCamelCase_  				=						iter_sql_file(UpperCAmelCase_	)
 lowerCamelCase_  				=						iter_sql_file(UpperCAmelCase_	)

 for rowa, rowa in zip(UpperCAmelCase_      ,       UpperCAmelCase_	):
  assert rowa == rowa







@require_sqlalchemy
def __snake_case      (   UpperCAmelCase_		:		Any      ,       UpperCAmelCase_		:		Tuple      ,       UpperCAmelCase_		:		Tuple	):
 lowerCamelCase_  				=						tmp_path / "cache"
 lowerCamelCase_  				=						os.path.join(UpperCAmelCase_      ,       "tmp.sql"	)
 lowerCamelCase_  				=						SqlDatasetReader("dataset"      ,       "sqlite:///" + sqlite_path      ,       cache_dir=UpperCAmelCase_	).read()
 with pytest.raises(UpperCAmelCase_	):
  SqlDatasetWriter(UpperCAmelCase_      ,       "dataset"      ,       "sqlite:///" + output_sqlite_path      ,       num_proc=0	).write()



