

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases


def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						assert isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			)
						assert dataset.num_rows == 4
						assert dataset.num_columns == 1
						assert dataset.column_names == ["text"]
						for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype


@pytest.mark.parametrize('''keep_in_memory'''    ,						[False, True]			)
def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						snake_case_  =      tmp_path / '''cache'''
						snake_case_  =      {'''text''': '''string'''}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												snake_case_  =      TextDatasetReader(SCREAMING_SNAKE_CASE__    ,						cache_dir=SCREAMING_SNAKE_CASE__    ,						keep_in_memory=SCREAMING_SNAKE_CASE__			).read()
						_check_text_dataset(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			)


@pytest.mark.parametrize(
    '''features'''    ,						[
        None,
        {'''text''': '''string'''},
        {'''text''': '''int32'''},
        {'''text''': '''float32'''},
    ]    ,						)
def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						snake_case_  =      tmp_path / '''cache'''
						snake_case_  =      {'''text''': '''string'''}
						snake_case_  =      features.copy() if features else default_expected_features
						snake_case_  =      (
						    Features({feature: Value(SCREAMING_SNAKE_CASE__			) for feature, dtype in features.items()}			) if features is not None else None
						)
						snake_case_  =      TextDatasetReader(SCREAMING_SNAKE_CASE__    ,						features=SCREAMING_SNAKE_CASE__    ,						cache_dir=SCREAMING_SNAKE_CASE__			).read()
						_check_text_dataset(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			)


@pytest.mark.parametrize('''split'''    ,						[None, NamedSplit('''train'''			), '''train''', '''test''']			)
def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						snake_case_  =      tmp_path / '''cache'''
						snake_case_  =      {'''text''': '''string'''}
						snake_case_  =      TextDatasetReader(SCREAMING_SNAKE_CASE__    ,						cache_dir=SCREAMING_SNAKE_CASE__    ,						split=SCREAMING_SNAKE_CASE__			).read()
						_check_text_dataset(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			)
						assert dataset.split == split if split else "train"


@pytest.mark.parametrize('''path_type'''    ,						[str, list]			)
def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						if issubclass(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
												snake_case_  =      text_path
						elif issubclass(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
												snake_case_  =      [text_path]
						snake_case_  =      tmp_path / '''cache'''
						snake_case_  =      {'''text''': '''string'''}
						snake_case_  =      TextDatasetReader(SCREAMING_SNAKE_CASE__    ,						cache_dir=SCREAMING_SNAKE_CASE__			).read()
						_check_text_dataset(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			)


def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__=("train",)			):
						assert isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			)
						for split in splits:
												snake_case_  =      dataset_dict[split]
												assert dataset.num_rows == 4
												assert dataset.num_columns == 1
												assert dataset.column_names == ["text"]
												for feature, expected_dtype in expected_features.items():
																		assert dataset.features[feature].dtype == expected_dtype


@pytest.mark.parametrize('''keep_in_memory'''    ,						[False, True]			)
def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						snake_case_  =      tmp_path / '''cache'''
						snake_case_  =      {'''text''': '''string'''}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												snake_case_  =      TextDatasetReader({'''train''': text_path}    ,						cache_dir=SCREAMING_SNAKE_CASE__    ,						keep_in_memory=SCREAMING_SNAKE_CASE__			).read()
						_check_text_datasetdict(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			)


@pytest.mark.parametrize(
    '''features'''    ,						[
        None,
        {'''text''': '''string'''},
        {'''text''': '''int32'''},
        {'''text''': '''float32'''},
    ]    ,						)
def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						snake_case_  =      tmp_path / '''cache'''
						# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
						snake_case_  =      {'''text''': '''string'''}
						snake_case_  =      features.copy() if features else default_expected_features
						snake_case_  =      (
						    Features({feature: Value(SCREAMING_SNAKE_CASE__			) for feature, dtype in features.items()}			) if features is not None else None
						)
						snake_case_  =      TextDatasetReader({'''train''': text_path}    ,						features=SCREAMING_SNAKE_CASE__    ,						cache_dir=SCREAMING_SNAKE_CASE__			).read()
						_check_text_datasetdict(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			)


@pytest.mark.parametrize('''split'''    ,						[None, NamedSplit('''train'''			), '''train''', '''test''']			)
def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						if split:
												snake_case_  =      {split: text_path}
						else:
												snake_case_  =      '''train'''
												snake_case_  =      {'''train''': text_path, '''test''': text_path}
						snake_case_  =      tmp_path / '''cache'''
						snake_case_  =      {'''text''': '''string'''}
						snake_case_  =      TextDatasetReader(SCREAMING_SNAKE_CASE__    ,						cache_dir=SCREAMING_SNAKE_CASE__			).read()
						_check_text_datasetdict(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						splits=list(path.keys()			)			)
						assert all(dataset[split].split == split for split in path.keys()			)



'''simple docstring'''

import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class     __lowerCAmelCase		(lowercase_    ,	unittest.TestCase	):





      '''simple docstring'''






      lowerCAmelCase__   :	str       =				RoFormerTokenizer
      lowerCAmelCase__   :	Dict       =				RoFormerTokenizerFast
      lowerCAmelCase__   :	List[str]       =				True
      lowerCAmelCase__   :	List[str]       =				True



      def  UpperCamelCase__						(self       :       Dict					):

             '''simple docstring'''







             super().setUp()



      def  UpperCamelCase__						(self       :       List[str]  ,		**UpperCamelCase       :       Dict					):

             '''simple docstring'''







             return self.tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''  ,		**UpperCamelCase					)



      def  UpperCamelCase__						(self       :       List[str]  ,		**UpperCamelCase       :       int					):

             '''simple docstring'''







             return self.rust_tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''  ,		**UpperCamelCase					)



      def  UpperCamelCase__						(self       :       List[str]					):

             '''simple docstring'''







             lowercase__      =					'''永和服装饰品有限公司,今天天气非常好'''
             lowercase__      =					'''永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'''
             return input_text, output_text



      def  UpperCamelCase__						(self       :       int					):

             '''simple docstring'''







             lowercase__      =					self.get_tokenizer()
             lowercase__     ,lowercase__      =					self.get_chinese_input_output_texts()
             lowercase__      =					tokenizer.tokenize(UpperCamelCase					)

             self.assertListEqual(UpperCamelCase  ,		output_text.split()					)

             lowercase__      =					tokens + [tokenizer.unk_token]
             lowercase__      =					[22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
             self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase					)  ,		UpperCamelCase					)



      def  UpperCamelCase__						(self       :       Union[str, Any]					):

             '''simple docstring'''







             lowercase__      =					self.get_rust_tokenizer()
             lowercase__     ,lowercase__      =					self.get_chinese_input_output_texts()
             lowercase__      =					tokenizer.tokenize(UpperCamelCase					)
             self.assertListEqual(UpperCamelCase  ,		output_text.split()					)
             lowercase__      =					tokens + [tokenizer.unk_token]
             lowercase__      =					[22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
             self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase					)  ,		UpperCamelCase					)



      def  UpperCamelCase__						(self       :       str					):

             '''simple docstring'''







             pass



      def  UpperCamelCase__						(self       :       Any					):

             '''simple docstring'''







             pass






      def  UpperCamelCase__						(self       :       Union[str, Any]					):

             '''simple docstring'''







             pass




