



import json
import os
import tempfile

from transformers.testing_utils import check_json_file_has_correct_format

class 					_A :
       UpperCamelCase__						:					Union[str, Any]		      =		None



       def 	_lowerCamelCase    (	self							:  Dict):


           '''simple docstring'''

           __a		 =       self.feature_extraction_class(**self.feat_extract_dict)
           __a		 =       json.loads(feat_extract.to_json_string())
           for key, value in self.feat_extract_dict.items():
               self.assertEqual(obj[key]  ,	__SCREAMING_SNAKE_CASE)



       def 	_lowerCamelCase    (	self							:  Tuple):


           '''simple docstring'''

           __a		 =       self.feature_extraction_class(**self.feat_extract_dict)

           with tempfile.TemporaryDirectory() as tmpdirname:
               __a		 =       os.path.join(__SCREAMING_SNAKE_CASE  ,	'''feat_extract.json''')
               feat_extract_first.to_json_file(__SCREAMING_SNAKE_CASE)
               __a		 =       self.feature_extraction_class.from_json_file(__SCREAMING_SNAKE_CASE)

           self.assertEqual(feat_extract_second.to_dict()  ,	feat_extract_first.to_dict())



       def 	_lowerCamelCase    (	self							:  Dict):


           '''simple docstring'''

           __a		 =       self.feature_extraction_class(**self.feat_extract_dict)

           with tempfile.TemporaryDirectory() as tmpdirname:
               __a		 =       feat_extract_first.save_pretrained(__SCREAMING_SNAKE_CASE)[0]
               check_json_file_has_correct_format(__SCREAMING_SNAKE_CASE)
               __a		 =       self.feature_extraction_class.from_pretrained(__SCREAMING_SNAKE_CASE)

           self.assertEqual(feat_extract_second.to_dict()  ,	feat_extract_first.to_dict())





       def 	_lowerCamelCase    (	self							:  str):


           '''simple docstring'''

           __a		 =       self.feature_extraction_class()
           self.assertIsNotNone(__SCREAMING_SNAKE_CASE)










from unittest import TestCase

from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset

class 					_A (			__UpperCAmelCase					):



       def 	_lowerCamelCase    (	self							:  int):


           '''simple docstring'''

           return [
               {"col_1": 3, "col_2": "a"},
               {"col_1": 2, "col_2": "b"},
               {"col_1": 1, "col_2": "c"},
               {"col_1": 0, "col_2": "d"},
           ]



       def 	_lowerCamelCase    (	self							:  Tuple):


           '''simple docstring'''

           __a		 =       {'''col_1''': [3, 2, 1, 0], '''col_2''': ['''a''', '''b''', '''c''', '''d''']}
           return Dataset.from_dict(__SCREAMING_SNAKE_CASE)



       def 	_lowerCamelCase    (	self							:  Any):


           '''simple docstring'''

           __a		 =       self._create_example_records()
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           self.assertListEqual(dset.column_names  ,	['''col_1''', '''col_2'''])
           for i, r in enumerate(__SCREAMING_SNAKE_CASE):
               self.assertDictEqual(__SCREAMING_SNAKE_CASE  ,	example_records[i])



       def 	_lowerCamelCase    (	self							:  Optional[Any]):


           '''simple docstring'''

           __a		 =       self._create_example_records()
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           __a		 =       Dataset.from_dict({k: [r[k] for r in example_records] for k in example_records[0]})
           self.assertEqual(dset.info  ,	dset_from_dict.info)



       def 	_lowerCamelCase    (	self							:  int):  # checks what happens with missing columns


           '''simple docstring'''

           __a		 =       [{'''col_1''': 1}, {'''col_2''': '''x'''}]
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           self.assertDictEqual(dset[0]  ,	{'''col_1''': 1})
           self.assertDictEqual(dset[1]  ,	{'''col_1''': None})  # NB: first record is used for columns



       def 	_lowerCamelCase    (	self							:  Optional[Any]):  # checks if the type can be inferred from the second record


           '''simple docstring'''

           __a		 =       [{'''col_1''': []}, {'''col_1''': [1, 2]}]
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           self.assertEqual(dset.info.features['''col_1''']  ,	Sequence(Value('''int64''')))





       def 	_lowerCamelCase    (	self							:  List[Any]):


           '''simple docstring'''

           __a		 =       Dataset.from_list([])
           self.assertEqual(len(__SCREAMING_SNAKE_CASE)  ,	0)
           self.assertListEqual(dset.column_names  ,	[])





