



"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


__a      =				logging.get_logger(__name__)

__a      =				{
    'SCUT-DLVCLab/lilt-roberta-en-base': (
        'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'
    ),
}
class 				lowerCamelCase  (			_lowerCAmelCase				):






					'''simple docstring'''





					_A		:			Tuple						=     '''lilt'''






					def __init__(       self:							int						,     snake_case:							Tuple=30_522						,     snake_case:							List[Any]=768						,     snake_case:							Dict=12						,     snake_case:							Optional[int]=12						,     snake_case:							Dict=3_072						,     snake_case:							List[Any]="gelu"						,     snake_case:							List[str]=0.1						,     snake_case:							Tuple=0.1						,     snake_case:							List[Any]=512						,     snake_case:							List[Any]=2						,     snake_case:							Dict=0.0_2						,     snake_case:							Any=1E-12						,     snake_case:							Union[str, Any]=0						,     snake_case:							str="absolute"						,     snake_case:							int=None						,     snake_case:							List[Any]=4						,     snake_case:							Tuple=1_024						,     **snake_case:							Union[str, Any]						,     )   ->	List[Any]:
											super().__init__(pad_token_id=A__						,     **A__						)

											snake_case_ :Dict						=			vocab_size
											snake_case_ :Any						=			hidden_size
											snake_case_ :List[Any]						=			num_hidden_layers
											snake_case_ :str						=			num_attention_heads
											snake_case_ :Union[str, Any]						=			hidden_act
											snake_case_ :Union[str, Any]						=			intermediate_size
											snake_case_ :List[Any]						=			hidden_dropout_prob
											snake_case_ :str						=			attention_probs_dropout_prob
											snake_case_ :Optional[Any]						=			max_position_embeddings
											snake_case_ :str						=			type_vocab_size
											snake_case_ :List[Any]						=			initializer_range
											snake_case_ :List[str]						=			layer_norm_eps
											snake_case_ :str						=			position_embedding_type
											snake_case_ :Any						=			classifier_dropout
											snake_case_ :List[str]						=			channel_shrink_ratio
											snake_case_ :Optional[Any]						=			max_ad_position_embeddings



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 						UpperCamelCase					(lowercase_: List[str]    ,      lowercase_: Optional[int]					)     ->      List[str]:
	A__							:    Tuple        =		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}}"""					)
	A__							:    List[Any]        =		DatasetInfosDict.from_directory(lowercase_					)
	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 						UpperCamelCase					(lowercase_: str    ,      lowercase_: DatasetInfo					)     ->      List[Any]:
	A__							:    Union[str, Any]        =		str(lowercase_					)
	dataset_info.write_to_directory(lowercase_					)
	A__							:    List[Any]        =		DatasetInfo.from_directory(lowercase_					)
	assert dataset_info == reloaded
	assert os.path.exists(os.path.join(lowercase_    ,      """dataset_info.json"""					)					)

def 						UpperCamelCase					()     ->      List[Any]:
	A__							:    Union[str, Any]        =		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    ,      )
	A__							:    Dict        =		dataset_info._to_yaml_dict()
	assert sorted(lowercase_					) == 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)					)
	A__							:    Union[str, Any]        =		yaml.safe_dump(lowercase_					)
	A__							:    List[Any]        =		yaml.safe_load(lowercase_					)
	assert dataset_info_yaml_dict == reloaded

def 						UpperCamelCase					()     ->      List[str]:
	A__							:    Optional[int]        =		DatasetInfo()
	A__							:    List[Any]        =		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 						UpperCamelCase					(lowercase_: Tuple    ,      lowercase_: DatasetInfosDict					)     ->      Optional[Any]:
	A__							:    List[Any]        =		str(lowercase_					)
	dataset_infos_dict.write_to_directory(lowercase_					)
	A__							:    Dict        =		DatasetInfosDict.from_directory(lowercase_					)

	# the config_name of the dataset_infos_dict take over the attribute
	for config_name, dataset_info in dataset_infos_dict.items():
		A__							:    Optional[int]        =		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
		A__							:    List[str]        =		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(lowercase_    ,      """README.md"""					)					)



