
"""simple docstring"""

import unittest

from diffusers import __version__
from diffusers.utils import deprecate






class 			_lowercase  (							unittest.TestCase						):
	lowercase_								=      '.'.join([str(int(__version__.split('.'						)[0]						) + 1						)] + __version__.split('.'						)[1:]						)
	lowercase_								=      '0.0.1'




	def      _UpperCamelCase       (					self   )						->				List[str]:
			lowerCamelCase	:     int            =       {'deprecated_arg': 4}

			with self.assertWarns(UpperCAmelCase_   ) as warning:
					lowerCamelCase	:     Tuple            =       deprecate('deprecated_arg'						,					self.higher_version						,					'message'						,					take_from=UpperCAmelCase_   )

			assert output == 4
			assert (
			    str(warning.warning   )
			    == F"""The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}."""
			    " message"
			)




	def      _UpperCamelCase       (					self   )						->				Any:
			lowerCamelCase	:     int            =       {'deprecated_arg': 4}

			with self.assertWarns(UpperCAmelCase_   ) as warning:
					lowerCamelCase	:     int            =       deprecate(('deprecated_arg', self.higher_version, 'message')						,					take_from=UpperCAmelCase_   )

			assert output == 4
			assert (
			    str(warning.warning   )
			    == F"""The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}."""
			    " message"
			)




	def      _UpperCamelCase       (					self   )						->				Dict:
			lowerCamelCase	:     Any            =       {'deprecated_arg_1': 4, 'deprecated_arg_2': 8}
			with self.assertWarns(UpperCAmelCase_   ) as warning:
					lowerCamelCase      ,       lowerCamelCase	:     Dict            =       deprecate(
					    ('deprecated_arg_1', self.higher_version, 'Hey')						,					('deprecated_arg_2', self.higher_version, 'Hey')						,					take_from=UpperCAmelCase_						,					)
			assert output_a == 4
			assert output_a == 8
			assert (
			    str(warning.warnings[0].message   )
			    == "The `deprecated_arg_1` argument is deprecated and will be removed in version"
			    F""" {self.higher_version}. Hey"""
			)
			assert (
			    str(warning.warnings[1].message   )
			    == "The `deprecated_arg_2` argument is deprecated and will be removed in version"
			    F""" {self.higher_version}. Hey"""
			)




	def      _UpperCamelCase       (					self   )						->				Union[str, Any]:
			lowerCamelCase	:     Any            =       {'deprecated_arg': 4}

			with self.assertRaises(UpperCAmelCase_   ) as error:
					deprecate(('wrong_arg', self.higher_version, 'message')						,					take_from=UpperCAmelCase_   )

			assert "test_deprecate_function_incorrect_arg in" in str(error.exception   )
			assert "line" in str(error.exception   )
			assert "got an unexpected keyword argument `deprecated_arg`" in str(error.exception   )




	def      _UpperCamelCase       (					self   )						->				List[str]:
			with self.assertWarns(UpperCAmelCase_   ) as warning:
					deprecate(('deprecated_arg', self.higher_version, 'message')   )

			assert (
			    str(warning.warning   )
			    == F"""`deprecated_arg` is deprecated and will be removed in version {self.higher_version}. message"""
			)




	def      _UpperCamelCase       (					self   )						->				int:
			with self.assertWarns(UpperCAmelCase_   ) as warning:
					deprecate(
					    ('deprecated_arg_1', self.higher_version, 'Hey')						,					('deprecated_arg_2', self.higher_version, 'Hey')						,					)
			assert (
			    str(warning.warnings[0].message   )
			    == F"""`deprecated_arg_1` is deprecated and will be removed in version {self.higher_version}. Hey"""
			)
			assert (
			    str(warning.warnings[1].message   )
			    == F"""`deprecated_arg_2` is deprecated and will be removed in version {self.higher_version}. Hey"""
			)




	def      _UpperCamelCase       (					self   )						->				Union[str, Any]:






			class 			_lowercase  :
				lowercase_								=      5

			with self.assertWarns(UpperCAmelCase_   ) as warning:
					lowerCamelCase	:     Tuple            =       deprecate(('arg', self.higher_version, 'message')						,					take_from=Args()   )

			assert arg == 5
			assert (
			    str(warning.warning   )
			    == F"""The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"""
			)




	def      _UpperCamelCase       (					self   )						->				Any:






			class 			_lowercase  :
				lowercase_								=      5
				lowercase_								=      7

			with self.assertWarns(UpperCAmelCase_   ) as warning:
					lowerCamelCase      ,       lowerCamelCase	:     Tuple            =       deprecate(
					    ('arg', self.higher_version, 'message')						,					('foo', self.higher_version, 'message')						,					('does not exist', self.higher_version, 'message')						,					take_from=Args()						,					)

			assert arg_a == 5
			assert arg_a == 7
			assert (
			    str(warning.warning   )
			    == F"""The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"""
			)
			assert (
			    str(warning.warnings[0].message   )
			    == F"""The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"""
			)
			assert (
			    str(warning.warnings[1].message   )
			    == F"""The `foo` attribute is deprecated and will be removed in version {self.higher_version}. message"""
			)




	def      _UpperCamelCase       (					self   )						->				Any:
			lowerCamelCase	:     Any            =       {'deprecated_arg': 4}

			with self.assertRaises(UpperCAmelCase_   ) as error:
					deprecate(('wrong_arg', self.lower_version, 'message')						,					take_from=UpperCAmelCase_   )

			assert (
			    str(error.exception   )
			    == "The deprecation tuple ('wrong_arg', '0.0.1', 'message') should be removed since diffusers' version"
			    F""" {__version__} is >= {self.lower_version}"""
			)




	def      _UpperCamelCase       (					self   )						->				Union[str, Any]:
			with self.assertWarns(UpperCAmelCase_   ) as warning:
					deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')						,					standard_warn=UpperCAmelCase_   )

			assert str(warning.warning   ) == "This message is better!!!"




	def      _UpperCamelCase       (					self   )						->				str:
			with self.assertWarns(UpperCAmelCase_   ) as warning:
					deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')						,					standard_warn=UpperCAmelCase_   )
			assert str(warning.warning   ) == "This message is better!!!"
			assert "diffusers/tests/others/test_utils.py" in warning.filename








"""simple docstring"""

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 						UpperCAmelCase   (						a_,		a_     ):





		'''simple docstring'''


		assert isinstance(a_,		a_     )
		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 						UpperCAmelCase   (						a_,		a_,		a_     ):





		'''simple docstring'''


		lowerCamelCase	:     List[Any]            =       tmp_path / 'cache'
		lowerCamelCase	:     Optional[int]            =       {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
		with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
				lowerCamelCase	:     Tuple            =       CsvDatasetReader(a_,		cache_dir=a_,		keep_in_memory=a_     ).read()
		_check_csv_dataset(a_,		a_     )
@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 						UpperCAmelCase   (						a_,		a_,		a_     ):





		'''simple docstring'''


		lowerCamelCase	:     int            =       tmp_path / 'cache'
		# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
		lowerCamelCase	:     List[str]            =       {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
		lowerCamelCase	:     str            =       features.copy() if features else default_expected_features
		lowerCamelCase	:     List[Any]            =       (
		    Features({feature: Value(a_     ) for feature, dtype in features.items()}     ) if features is not None else None
		)
		lowerCamelCase	:     Union[str, Any]            =       CsvDatasetReader(a_,		features=a_,		cache_dir=a_     ).read()
		_check_csv_dataset(a_,		a_     )
@pytest.mark.parametrize('split',		[None, NamedSplit('train'     ), 'train', 'test']     )
def 						UpperCAmelCase   (						a_,		a_,		a_     ):





		'''simple docstring'''


		lowerCamelCase	:     Any            =       tmp_path / 'cache'
		lowerCamelCase	:     Dict            =       {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
		lowerCamelCase	:     Dict            =       CsvDatasetReader(a_,		cache_dir=a_,		split=a_     ).read()
		_check_csv_dataset(a_,		a_     )
		assert dataset.split == split if split else "train"
@pytest.mark.parametrize('path_type',		[str, list]     )
def 						UpperCAmelCase   (						a_,		a_,		a_     ):





		'''simple docstring'''


		if issubclass(a_,		a_     ):
				lowerCamelCase	:     Dict            =       csv_path
		elif issubclass(a_,		a_     ):
				lowerCamelCase	:     Tuple            =       [csv_path]
		lowerCamelCase	:     Optional[Any]            =       tmp_path / 'cache'
		lowerCamelCase	:     Tuple            =       {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
		lowerCamelCase	:     List[Any]            =       CsvDatasetReader(a_,		cache_dir=a_     ).read()
		_check_csv_dataset(a_,		a_     )
def 						UpperCAmelCase   (						a_,		a_,		a_=("train",)     ):





		'''simple docstring'''


		assert isinstance(a_,		a_     )
		for split in splits:
				lowerCamelCase	:     Any            =       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 						UpperCAmelCase   (						a_,		a_,		a_     ):





		'''simple docstring'''


		lowerCamelCase	:     Any            =       tmp_path / 'cache'
		lowerCamelCase	:     int            =       {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
		with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
				lowerCamelCase	:     int            =       CsvDatasetReader({'train': csv_path},		cache_dir=a_,		keep_in_memory=a_     ).read()
		_check_csv_datasetdict(a_,		a_     )
@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 						UpperCAmelCase   (						a_,		a_,		a_     ):





		'''simple docstring'''


		lowerCamelCase	:     str            =       tmp_path / 'cache'
		# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
		lowerCamelCase	:     Dict            =       {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
		lowerCamelCase	:     str            =       features.copy() if features else default_expected_features
		lowerCamelCase	:     Any            =       (
		    Features({feature: Value(a_     ) for feature, dtype in features.items()}     ) if features is not None else None
		)
		lowerCamelCase	:     Optional[Any]            =       CsvDatasetReader({'train': csv_path},		features=a_,		cache_dir=a_     ).read()
		_check_csv_datasetdict(a_,		a_     )
@pytest.mark.parametrize('split',		[None, NamedSplit('train'     ), 'train', 'test']     )
def 						UpperCAmelCase   (						a_,		a_,		a_     ):





		'''simple docstring'''


		if split:
				lowerCamelCase	:     List[Any]            =       {split: csv_path}
		else:
				lowerCamelCase	:     Any            =       {'train': csv_path, 'test': csv_path}
		lowerCamelCase	:     List[Any]            =       tmp_path / 'cache'
		lowerCamelCase	:     Union[str, Any]            =       {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
		lowerCamelCase	:     Union[str, Any]            =       CsvDatasetReader(a_,		cache_dir=a_     ).read()
		_check_csv_datasetdict(a_,		a_,		splits=list(path.keys()     )     )
		assert all(dataset[split].split == split for split in path.keys()     )
def 						UpperCAmelCase   (						a_     ):





		'''simple docstring'''


		with open(a_,		encoding='utf-8'     ) as csvfile:
				yield from csv.reader(a_     )
def 						UpperCAmelCase   (						a_,		a_     ):





		'''simple docstring'''


		lowerCamelCase	:     Optional[int]            =       tmp_path / 'cache'
		lowerCamelCase	:     int            =       os.path.join(a_,		'tmp.csv'     )
		lowerCamelCase	:     List[str]            =       CsvDatasetReader({'train': csv_path},		cache_dir=a_     ).read()
		CsvDatasetWriter(dataset['train'],		a_,		num_proc=1     ).write()

		lowerCamelCase	:     Tuple            =       iter_csv_file(a_     )
		lowerCamelCase	:     Tuple            =       iter_csv_file(a_     )

		for rowa, rowa in zip(a_,		a_     ):
				assert rowa == rowa
def 						UpperCAmelCase   (						a_,		a_     ):





		'''simple docstring'''


		lowerCamelCase	:     Optional[Any]            =       tmp_path / 'cache'
		lowerCamelCase	:     Optional[Any]            =       os.path.join(a_,		'tmp.csv'     )
		lowerCamelCase	:     Dict            =       CsvDatasetReader({'train': csv_path},		cache_dir=a_     ).read()
		CsvDatasetWriter(dataset['train'],		a_,		num_proc=2     ).write()

		lowerCamelCase	:     int            =       iter_csv_file(a_     )
		lowerCamelCase	:     Optional[int]            =       iter_csv_file(a_     )

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





def 						UpperCAmelCase   (						a_,		a_     ):





		'''simple docstring'''


		lowerCamelCase	:     Tuple            =       tmp_path / 'cache'
		lowerCamelCase	:     Optional[Any]            =       os.path.join(a_,		'tmp.csv'     )
		lowerCamelCase	:     Optional[int]            =       CsvDatasetReader({'train': csv_path},		cache_dir=a_     ).read()
		with pytest.raises(a_     ):
				CsvDatasetWriter(dataset['train'],		a_,		num_proc=0     )






