


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   _lowercase(					__a				:						Optional[int]    ,     __a				:						Optional[int]     ):
							a__      =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__      =DatasetInfosDict.from_directory(__a     )
							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   _lowercase(					__a				:						Tuple    ,     __a				:						DatasetInfo     ):
							a__      =str(__a     )
							dataset_info.write_to_directory(__a     )
							a__      =DatasetInfo.from_directory(__a     )
							assert dataset_info == reloaded
							assert os.path.exists(os.path.join(__a    ,     'dataset_info.json'     )     )






def   _lowercase(					):
							a__      =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__      =dataset_info._to_yaml_dict()
							assert sorted(__a     ) == 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__      =yaml.safe_dump(__a     )
							a__      =yaml.safe_load(__a     )
							assert dataset_info_yaml_dict == reloaded






def   _lowercase(					):
							a__      =DatasetInfo()
							a__      =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   _lowercase(					__a				:						Any    ,     __a				:						DatasetInfosDict     ):
							a__      =str(__a     )
							dataset_infos_dict.write_to_directory(__a     )
							a__      =DatasetInfosDict.from_directory(__a     )

							# the config_name of the dataset_infos_dict take over the attribute
							for config_name, dataset_info in dataset_infos_dict.items():
														a__      =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__      =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(__a    ,     'README.md'     )     )





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCAmelCase:						str   				=       logging.get_logger(__name__)

_lowerCAmelCase:						Any   				=       {
    'google/bigbird-roberta-base': 'https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json',
    'google/bigbird-roberta-large': 'https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json',
    'google/bigbird-base-trivia-itc': 'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json',
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}




class       lowercase_					(lowercase__   ):
				snake_case	    ='big_bird'





				def __init__(				self       ,  lowercase_=50358       ,  lowercase_=768       ,  lowercase_=12       ,  lowercase_=12       ,  lowercase_=3072       ,  lowercase_="gelu_new"       ,  lowercase_=0.1       ,  lowercase_=0.1       ,  lowercase_=4096       ,  lowercase_=2       ,  lowercase_=0.02       ,  lowercase_=1e-12       ,  lowercase_=True       ,  lowercase_=0       ,  lowercase_=1       ,  lowercase_=2       ,  lowercase_=66       ,  lowercase_="block_sparse"       ,  lowercase_=True       ,  lowercase_=False       ,  lowercase_=64       ,  lowercase_=3       ,  lowercase_=None       ,  **lowercase_       ,  )  -> Any:
											super().__init__(
											    pad_token_id=lowercase_       ,  bos_token_id=lowercase_       ,  eos_token_id=lowercase_       ,  sep_token_id=lowercase_       ,  **lowercase_       ,  )

											a__      =vocab_size
											a__      =max_position_embeddings
											a__      =hidden_size
											a__      =num_hidden_layers
											a__      =num_attention_heads
											a__      =intermediate_size
											a__      =hidden_act
											a__      =hidden_dropout_prob
											a__      =attention_probs_dropout_prob
											a__      =initializer_range
											a__      =type_vocab_size
											a__      =layer_norm_eps
											a__      =use_cache

											a__      =rescale_embeddings
											a__      =attention_type
											a__      =use_bias
											a__      =block_size
											a__      =num_random_blocks
											a__      =classifier_dropout







class       lowercase_					(lowercase__   ):





				@property
				def 						__UpperCamelCase    (				self)  -> Mapping[str, Mapping[int, str]]:
											if self.task == "multiple-choice":
																		a__      ={0: 'batch', 1: 'choice', 2: 'sequence'}
											else:
																		a__      ={0: 'batch', 1: 'sequence'}
											return OrderedDict(
											    [
											        ('input_ids', dynamic_axis),
											        ('attention_mask', dynamic_axis),
											    ])

