


import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict







@pytest.mark.parametrize(
    '''files'''	,[
        ['''full:README.md''', '''dataset_infos.json'''],
        ['''empty:README.md''', '''dataset_infos.json'''],
        ['''dataset_infos.json'''],
        ['''full:README.md'''],
    ]	,)
def 						lowerCamelCase(   a__	,a__):
				_SCREAMING_SNAKE_CASE			  =tmp_path_factory.mktemp('''dset_infos_dir''')
				if "full:README.md" in files:
								with open(dataset_infos_dir / '''README.md'''	,'''w''') as f:
												f.write('''---\ndataset_info:\n  dataset_size: 42\n---''')
				if "empty:README.md" in files:
								with open(dataset_infos_dir / '''README.md'''	,'''w''') as f:
												f.write('''''')
    # we want to support dataset_infos.json for backward compatibility
				if "dataset_infos.json" in files:
								with open(dataset_infos_dir / '''dataset_infos.json'''	,'''w''') as f:
												f.write('''{"default": {"dataset_size": 42}}''')
				_SCREAMING_SNAKE_CASE			  =DatasetInfosDict.from_directory(UpperCamelCase__)
				assert dataset_infos
				assert dataset_infos["default"].dataset_size == 42







@pytest.mark.parametrize(
    '''dataset_info'''	,[
        DatasetInfo(),
        DatasetInfo(
            description='''foo'''	,features=Features({'''a''': Value('''int32''')})	,builder_name='''builder'''	,config_name='''config'''	,version='''1.0.0'''	,splits=[{'''name''': '''train'''}]	,download_size=42	,),
    ]	,)
def 						lowerCamelCase(   a__	,a__):
				_SCREAMING_SNAKE_CASE			  =str(UpperCamelCase__)
				dataset_info.write_to_directory(UpperCamelCase__)
				_SCREAMING_SNAKE_CASE			  =DatasetInfo.from_directory(UpperCamelCase__)
				assert dataset_info == reloaded
				assert os.path.exists(os.path.join(UpperCamelCase__	,'''dataset_info.json'''))







def 						lowerCamelCase(   ):
				_SCREAMING_SNAKE_CASE			  =DatasetInfo(
				    description='''foo'''	,citation='''bar'''	,homepage='''https://foo.bar'''	,license='''CC0'''	,features=Features({'''a''': Value('''int32''')})	,post_processed={}	,supervised_keys=()	,task_templates=[]	,builder_name='''builder'''	,config_name='''config'''	,version='''1.0.0'''	,splits=[{'''name''': '''train''', '''num_examples''': 42}]	,download_checksums={}	,download_size=1337	,post_processing_size=442	,dataset_size=1234	,size_in_bytes=1337 + 442 + 1234	,)
				_SCREAMING_SNAKE_CASE			  =dataset_info._to_yaml_dict()
				assert sorted(UpperCamelCase__) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML)
				for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
								assert key in dataset_info_yaml_dict
								assert isinstance(dataset_info_yaml_dict[key]	,(list, dict, int, str))
				_SCREAMING_SNAKE_CASE			  =yaml.safe_dump(UpperCamelCase__)
				_SCREAMING_SNAKE_CASE			  =yaml.safe_load(UpperCamelCase__)
				assert dataset_info_yaml_dict == reloaded







def 						lowerCamelCase(   ):
				_SCREAMING_SNAKE_CASE			  =DatasetInfo()
				_SCREAMING_SNAKE_CASE			  =dataset_info._to_yaml_dict()
				assert dataset_info_yaml_dict == {}







@pytest.mark.parametrize(
    '''dataset_infos_dict'''	,[
        DatasetInfosDict(),
        DatasetInfosDict({'''default''': DatasetInfo()}),
        DatasetInfosDict({'''my_config_name''': DatasetInfo()}),
        DatasetInfosDict(
            {
                '''default''': DatasetInfo(
                    description='''foo'''	,features=Features({'''a''': Value('''int32''')})	,builder_name='''builder'''	,config_name='''config'''	,version='''1.0.0'''	,splits=[{'''name''': '''train'''}]	,download_size=42	,)
            }),
        DatasetInfosDict(
            {
                '''v1''': DatasetInfo(dataset_size=42),
                '''v2''': DatasetInfo(dataset_size=1337),
            }),
    ]	,)
def 						lowerCamelCase(   a__	,a__):
				_SCREAMING_SNAKE_CASE			  =str(UpperCamelCase__)
				dataset_infos_dict.write_to_directory(UpperCamelCase__)
				_SCREAMING_SNAKE_CASE			  =DatasetInfosDict.from_directory(UpperCamelCase__)

				# the config_name of the dataset_infos_dict take over the attribute
				for config_name, dataset_info in dataset_infos_dict.items():
								_SCREAMING_SNAKE_CASE			  =config_name
								# the yaml representation doesn't include fields like description or citation
								# so we just test that we can recover what we can from the yaml
								_SCREAMING_SNAKE_CASE			  =DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict())
				assert dataset_infos_dict == reloaded

				if dataset_infos_dict:
								assert os.path.exists(os.path.join(UpperCamelCase__	,'''README.md'''))



import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union

import torch

from ..utils import BaseOutput


snake_case_						:			Optional[Any]													=							'''scheduler_config.json'''

class 						A__							(		UpperCamelCase__  ):
						UpperCAmelCase             =						1
						UpperCAmelCase             =						2
						UpperCAmelCase             =						3
						UpperCAmelCase             =						4
						UpperCAmelCase             =						5
						UpperCAmelCase             =						6
						UpperCAmelCase             =						7
						UpperCAmelCase             =						8
						UpperCAmelCase             =						9
						UpperCAmelCase             =						10
						UpperCAmelCase             =						11
						UpperCAmelCase             =						12
						UpperCAmelCase             =						13
						UpperCAmelCase             =						14

@dataclass
class 						A__							(		UpperCamelCase__  ):
						UpperCAmelCase             =						42

class 						A__							:
						UpperCAmelCase             =						SCHEDULER_CONFIG_NAME
						UpperCAmelCase             =						[]
						UpperCAmelCase             =						True




						@classmethod
						def 							__UpperCamelCase				(       cls					:      List[str]				,    _a					:      Dict[str, Any] = None				,    _a					:      Optional[str] = None				,    _a					:      Optional[Any]=False				,    **_a					:      Dict				,    )							->     Dict:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE			  =cls.load_config(
										    pretrained_model_name_or_path=_a				,    subfolder=_a				,    return_unused_kwargs=_a				,    return_commit_hash=_a				,    **_a				,    )
										return cls.from_config(_a				,    return_unused_kwargs=_a				,    **_a  )




						def 							__UpperCamelCase				(       self					:      Dict				,    _a					:      Union[str, os.PathLike]				,    _a					:      bool = False				,    **_a					:      int  )							->     Dict:


										"""simple docstring"""





										self.save_config(save_directory=_a				,    push_to_hub=_a				,    **_a  )




						@property
						def 							__UpperCamelCase				(       self					:      List[str]  )							->     List[Any]:


										"""simple docstring"""





										return self._get_compatibles()




						@classmethod
						def 							__UpperCamelCase				(       cls					:      List[Any]  )							->     str:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =list(set([cls.__name__] + cls._compatibles  )  )
										_SCREAMING_SNAKE_CASE			  =importlib.import_module(__name__.split('''.'''  )[0]  )
										_SCREAMING_SNAKE_CASE			  =[
										    getattr(_a				,    _a  ) for c in compatible_classes_str if hasattr(_a				,    _a  )
										]
										return compatible_classes