



import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case		:List[Any]   	=  logging.get_logger(__name__)

class 					_A (			__UpperCAmelCase					):
       UpperCamelCase__						:					str		      =		'''encoder-decoder'''
       UpperCamelCase__						:					List[Any]		      =		True



       def __init__(	self							:  Any  ,	**__SCREAMING_SNAKE_CASE							:  int):


           '''simple docstring'''

           super().__init__(**__SCREAMING_SNAKE_CASE)
           assert (
               "encoder" in kwargs and "decoder" in kwargs
           ), "Config has to be initialized with encoder and decoder config"
           __a		 =       kwargs.pop('''encoder''')
           __a		 =       encoder_config.pop('''model_type''')
           __a		 =       kwargs.pop('''decoder''')
           __a		 =       decoder_config.pop('''model_type''')

           from ..auto.configuration_auto import AutoConfig

           __a		 =       AutoConfig.for_model(__SCREAMING_SNAKE_CASE  ,	**__SCREAMING_SNAKE_CASE)
           __a		 =       AutoConfig.for_model(__SCREAMING_SNAKE_CASE  ,	**__SCREAMING_SNAKE_CASE)
           __a		 =       True



       @classmethod
       def 	_lowerCamelCase    (	cls							:  Tuple  ,	__SCREAMING_SNAKE_CASE							:  PretrainedConfig  ,	__SCREAMING_SNAKE_CASE							:  PretrainedConfig  ,	**__SCREAMING_SNAKE_CASE							:  List[Any]):


           '''simple docstring'''

           logger.info('''Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config''')
           __a		 =       True
           __a		 =       True

           return cls(encoder=encoder_config.to_dict()  ,	decoder=decoder_config.to_dict()  ,	**__SCREAMING_SNAKE_CASE)





       def 	_lowerCamelCase    (	self							:  Optional[Any]):


           '''simple docstring'''

           __a		 =       copy.deepcopy(self.__dict__)
           __a		 =       self.encoder.to_dict()
           __a		 =       self.decoder.to_dict()
           __a		 =       self.__class__.model_type
           return output










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  ,	[])





