






import unittest
from dataclasses import dataclass
from typing import Optional

from transformers.utils import ModelOutput


@dataclass
class        SCREAMING_SNAKE_CASE	(	lowerCAmelCase    ):
     '''simple docstring'''


     UpperCamelCase_							:						float
     UpperCamelCase_							:						Optional[float]								=		None
     UpperCamelCase_							:						Optional[float]								=		None





class        SCREAMING_SNAKE_CASE	(	unittest.TestCase    ):
     '''simple docstring'''


     def  _A				( self				:		int					):
       SCREAMING_SNAKE_CASE				:					Any		  =			ModelOutputTest(a=30					)
       self.assertEqual(x.a    ,       30					)
       self.assertIsNone(x.b					)
       self.assertIsNone(x.c					)
       with self.assertRaises(UpperCAmelCase_					):
         SCREAMING_SNAKE_CASE				:					Tuple		  =			x.d


     def  _A				( self				:		Optional[Any]					):
       SCREAMING_SNAKE_CASE				:					Any		  =			ModelOutputTest(a=30    ,       b=10					)
       self.assertEqual(x[0]    ,       30					)
       self.assertEqual(x[1]    ,       10					)
       self.assertEqual(x[:2]    ,       (30, 10)					)
       self.assertEqual(x[:]    ,       (30, 10)					)

       SCREAMING_SNAKE_CASE				:					List[Any]		  =			ModelOutputTest(a=30    ,       c=10					)
       self.assertEqual(x[0]    ,       30					)
       self.assertEqual(x[1]    ,       10					)
       self.assertEqual(x[:2]    ,       (30, 10)					)
       self.assertEqual(x[:]    ,       (30, 10)					)


     def  _A				( self				:		Any					):
       SCREAMING_SNAKE_CASE				:					str		  =			ModelOutputTest(a=30    ,       b=10					)
       self.assertEqual(x["a"]    ,       30					)
       self.assertEqual(x["b"]    ,       10					)
       with self.assertRaises(UpperCAmelCase_					):
         SCREAMING_SNAKE_CASE				:					Dict		  =			x["c"]

       SCREAMING_SNAKE_CASE				:					Optional[Any]		  =			ModelOutputTest(a=30    ,       c=10					)
       self.assertEqual(x["a"]    ,       30					)
       self.assertEqual(x["c"]    ,       10					)
       with self.assertRaises(UpperCAmelCase_					):
         SCREAMING_SNAKE_CASE				:					Any		  =			x["b"]


     def  _A				( self				:		Union[str, Any]					):
       SCREAMING_SNAKE_CASE				:					Any		  =			ModelOutputTest(a=30					)
       self.assertEqual(list(x.keys()					)    ,       ["a"]					)
       self.assertEqual(list(x.values()					)    ,       [30]					)
       self.assertEqual(list(x.items()					)    ,       [("a", 30)]					)
       self.assertEqual(list(UpperCAmelCase_					)    ,       ["a"]					)

       SCREAMING_SNAKE_CASE				:					Dict		  =			ModelOutputTest(a=30    ,       b=10					)
       self.assertEqual(list(x.keys()					)    ,       ["a", "b"]					)
       self.assertEqual(list(x.values()					)    ,       [30, 10]					)
       self.assertEqual(list(x.items()					)    ,       [("a", 30), ("b", 10)]					)
       self.assertEqual(list(UpperCAmelCase_					)    ,       ["a", "b"]					)

       SCREAMING_SNAKE_CASE				:					Dict		  =			ModelOutputTest(a=30    ,       c=10					)
       self.assertEqual(list(x.keys()					)    ,       ["a", "c"]					)
       self.assertEqual(list(x.values()					)    ,       [30, 10]					)
       self.assertEqual(list(x.items()					)    ,       [("a", 30), ("c", 10)]					)
       self.assertEqual(list(UpperCAmelCase_					)    ,       ["a", "c"]					)

       with self.assertRaises(UpperCAmelCase_					):
         SCREAMING_SNAKE_CASE				:					Any		  =			x.update({"d": 20}					)
       with self.assertRaises(UpperCAmelCase_					):
         del x["a"]
       with self.assertRaises(UpperCAmelCase_					):
         SCREAMING_SNAKE_CASE				:					int		  =			x.pop("a"					)
       with self.assertRaises(UpperCAmelCase_					):
         SCREAMING_SNAKE_CASE				:					str		  =			x.setdefault("d"    ,       32					)


     def  _A				( self				:		List[Any]					):
       SCREAMING_SNAKE_CASE				:					Any		  =			ModelOutputTest(a=30					)
       SCREAMING_SNAKE_CASE				:					Dict		  =			10
       self.assertEqual(x.a    ,       10					)
       self.assertEqual(x["a"]    ,       10					)


     def  _A				( self				:		Optional[int]					):
       SCREAMING_SNAKE_CASE				:					List[str]		  =			ModelOutputTest(a=30					)
       SCREAMING_SNAKE_CASE				:					Union[str, Any]		  =			10
       self.assertEqual(x.a    ,       10					)
       self.assertEqual(x["a"]    ,       10					)


     def  _A				( self				:		Optional[int]					):
       SCREAMING_SNAKE_CASE				:					str		  =			ModelOutputTest({"a": 30, "b": 10}					)
       self.assertEqual(list(x.keys()					)    ,       ["a", "b"]					)
       self.assertEqual(x.a    ,       30					)
       self.assertEqual(x.b    ,       10					)






     def  _A				( self				:		List[str]					):
       SCREAMING_SNAKE_CASE				:					List[Any]		  =			ModelOutputTest([("a", 30), ("b", 10)]					)
       self.assertEqual(list(x.keys()					)    ,       ["a", "b"]					)
       self.assertEqual(x.a    ,       30					)
       self.assertEqual(x.b    ,       10					)

       with self.assertRaises(UpperCAmelCase_					):
         SCREAMING_SNAKE_CASE				:					Tuple		  =			ModelOutputTest([("a", 30), (10, 10)]					)

       SCREAMING_SNAKE_CASE				:					Optional[Any]		  =			ModelOutputTest(a=(30, 30)					)
       self.assertEqual(list(x.keys()					)    ,       ["a"]					)
       self.assertEqual(x.a    ,       (30, 30)					)














import csv
import os

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases


def      lowerCamelCase__	(   lowercase  ,   lowercase ):

  """simple docstring"""






  assert isinstance(lowercase  ,   lowercase )
  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


@pytest.mark.parametrize("keep_in_memory"  ,   [False, True] )
def      lowerCamelCase__	(   lowercase  ,   lowercase  ,   lowercase ):

  """simple docstring"""






  SCREAMING_SNAKE_CASE				:					Union[str, Any]		  =			tmp_path / "cache"
  SCREAMING_SNAKE_CASE				:					Dict		  =			{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    SCREAMING_SNAKE_CASE				:					Optional[Any]		  =			CsvDatasetReader(lowercase  ,   cache_dir=lowercase  ,   keep_in_memory=lowercase ).read()
  _check_csv_dataset(lowercase  ,   lowercase )


@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      lowerCamelCase__	(   lowercase  ,   lowercase  ,   lowercase ):

  """simple docstring"""






  SCREAMING_SNAKE_CASE				:					Any		  =			tmp_path / "cache"
  # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
  SCREAMING_SNAKE_CASE				:					Optional[Any]		  =			{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
  SCREAMING_SNAKE_CASE				:					Any		  =			features.copy() if features else default_expected_features
  SCREAMING_SNAKE_CASE				:					List[Any]		  =			(
      Features({feature: Value(lowercase ) for feature, dtype in features.items()} ) if features is not None else None
  )
  SCREAMING_SNAKE_CASE				:					Tuple		  =			CsvDatasetReader(lowercase  ,   features=lowercase  ,   cache_dir=lowercase ).read()
  _check_csv_dataset(lowercase  ,   lowercase )


@pytest.mark.parametrize("split"  ,   [None, NamedSplit("train" ), "train", "test"] )
def      lowerCamelCase__	(   lowercase  ,   lowercase  ,   lowercase ):

  """simple docstring"""






  SCREAMING_SNAKE_CASE				:					Dict		  =			tmp_path / "cache"
  SCREAMING_SNAKE_CASE				:					Dict		  =			{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
  SCREAMING_SNAKE_CASE				:					List[Any]		  =			CsvDatasetReader(lowercase  ,   cache_dir=lowercase  ,   split=lowercase ).read()
  _check_csv_dataset(lowercase  ,   lowercase )
  assert dataset.split == split if split else "train"


@pytest.mark.parametrize("path_type"  ,   [str, list] )
def      lowerCamelCase__	(   lowercase  ,   lowercase  ,   lowercase ):

  """simple docstring"""






  if issubclass(lowercase  ,   lowercase ):
    SCREAMING_SNAKE_CASE				:					Tuple		  =			csv_path
  elif issubclass(lowercase  ,   lowercase ):
    SCREAMING_SNAKE_CASE				:					int		  =			[csv_path]
  SCREAMING_SNAKE_CASE				:					Any		  =			tmp_path / "cache"
  SCREAMING_SNAKE_CASE				:					Optional[int]		  =			{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
  SCREAMING_SNAKE_CASE				:					Tuple		  =			CsvDatasetReader(lowercase  ,   cache_dir=lowercase ).read()
  _check_csv_dataset(lowercase  ,   lowercase )


def      lowerCamelCase__	(   lowercase  ,   lowercase  ,   lowercase=("train",) ):

  """simple docstring"""






  assert isinstance(lowercase  ,   lowercase )
  for split in splits:
    SCREAMING_SNAKE_CASE				:					str		  =			dataset_dict[split]
    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


@pytest.mark.parametrize("keep_in_memory"  ,   [False, True] )
def      lowerCamelCase__	(   lowercase  ,   lowercase  ,   lowercase ):

  """simple docstring"""






  SCREAMING_SNAKE_CASE				:					Union[str, Any]		  =			tmp_path / "cache"
  SCREAMING_SNAKE_CASE				:					Union[str, Any]		  =			{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    SCREAMING_SNAKE_CASE				:					Optional[Any]		  =			CsvDatasetReader({"train": csv_path}  ,   cache_dir=lowercase  ,   keep_in_memory=lowercase ).read()
  _check_csv_datasetdict(lowercase  ,   lowercase )


@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      lowerCamelCase__	(   lowercase  ,   lowercase  ,   lowercase ):

  """simple docstring"""






  SCREAMING_SNAKE_CASE				:					int		  =			tmp_path / "cache"
  # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
  SCREAMING_SNAKE_CASE				:					Any		  =			{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
  SCREAMING_SNAKE_CASE				:					Optional[Any]		  =			features.copy() if features else default_expected_features
  SCREAMING_SNAKE_CASE				:					List[Any]		  =			(
      Features({feature: Value(lowercase ) for feature, dtype in features.items()} ) if features is not None else None
  )
  SCREAMING_SNAKE_CASE				:					Optional[Any]		  =			CsvDatasetReader({"train": csv_path}  ,   features=lowercase  ,   cache_dir=lowercase ).read()
  _check_csv_datasetdict(lowercase  ,   lowercase )


@pytest.mark.parametrize("split"  ,   [None, NamedSplit("train" ), "train", "test"] )
def      lowerCamelCase__	(   lowercase  ,   lowercase  ,   lowercase ):

  """simple docstring"""






  if split:
    SCREAMING_SNAKE_CASE				:					Dict		  =			{split: csv_path}
  else:
    SCREAMING_SNAKE_CASE				:					str		  =			{"train": csv_path, "test": csv_path}
  SCREAMING_SNAKE_CASE				:					Optional[Any]		  =			tmp_path / "cache"
  SCREAMING_SNAKE_CASE				:					Dict		  =			{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
  SCREAMING_SNAKE_CASE				:					Tuple		  =			CsvDatasetReader(lowercase  ,   cache_dir=lowercase ).read()
  _check_csv_datasetdict(lowercase  ,   lowercase  ,   splits=list(path.keys() ) )
  assert all(dataset[split].split == split for split in path.keys() )


def      lowerCamelCase__	(   lowercase ):

  """simple docstring"""






  with open(lowercase  ,   encoding="utf-8" ) as csvfile:
    yield from csv.reader(lowercase )


def      lowerCamelCase__	(   lowercase  ,   lowercase ):

  """simple docstring"""






  SCREAMING_SNAKE_CASE				:					List[Any]		  =			tmp_path / "cache"
  SCREAMING_SNAKE_CASE				:					Optional[int]		  =			os.path.join(lowercase  ,   "tmp.csv" )
  SCREAMING_SNAKE_CASE				:					Optional[int]		  =			CsvDatasetReader({"train": csv_path}  ,   cache_dir=lowercase ).read()
  CsvDatasetWriter(dataset["train"]  ,   lowercase  ,   num_proc=1 ).write()

  SCREAMING_SNAKE_CASE				:					Optional[Any]		  =			iter_csv_file(lowercase )
  SCREAMING_SNAKE_CASE				:					Optional[Any]		  =			iter_csv_file(lowercase )

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


def      lowerCamelCase__	(   lowercase  ,   lowercase ):

  """simple docstring"""






  SCREAMING_SNAKE_CASE				:					Union[str, Any]		  =			tmp_path / "cache"
  SCREAMING_SNAKE_CASE				:					List[Any]		  =			os.path.join(lowercase  ,   "tmp.csv" )
  SCREAMING_SNAKE_CASE				:					List[str]		  =			CsvDatasetReader({"train": csv_path}  ,   cache_dir=lowercase ).read()
  CsvDatasetWriter(dataset["train"]  ,   lowercase  ,   num_proc=2 ).write()

  SCREAMING_SNAKE_CASE				:					Dict		  =			iter_csv_file(lowercase )
  SCREAMING_SNAKE_CASE				:					Tuple		  =			iter_csv_file(lowercase )

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


def      lowerCamelCase__	(   lowercase  ,   lowercase ):

  """simple docstring"""






  SCREAMING_SNAKE_CASE				:					Optional[Any]		  =			tmp_path / "cache"
  SCREAMING_SNAKE_CASE				:					Union[str, Any]		  =			os.path.join(lowercase  ,   "tmp.csv" )
  SCREAMING_SNAKE_CASE				:					List[str]		  =			CsvDatasetReader({"train": csv_path}  ,   cache_dir=lowercase ).read()
  with pytest.raises(lowercase ):
    CsvDatasetWriter(dataset["train"]  ,   lowercase  ,   num_proc=0 )






