from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


__SCREAMING_SNAKE_CASE						:   Any         =			logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE						:   Dict         =			{
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

__SCREAMING_SNAKE_CASE						:   Optional[int]         =			{
    'vocab_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'
    },
    'merges_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'
    },
    'tokenizer_config_file': {
        'facebook/blenderbot_small-90M': (
            'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'
        )
    },
}

__SCREAMING_SNAKE_CASE						:   List[Any]         =			{
    'facebook/blenderbot_small-90M': 5_1_2,
}



class        lowercase_   (					snake_case_		):
							_lowerCamelCase						=		VOCAB_FILES_NAMES
							_lowerCamelCase						=		PRETRAINED_VOCAB_FILES_MAP
							_lowerCamelCase						=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							_lowerCamelCase						=		BlenderbotSmallTokenizer



							def __init__(						self				,    lowercase_=None				,    lowercase_=None				,    lowercase_="<|endoftext|>"				,    lowercase_="<|endoftext|>"				,    lowercase_="<|endoftext|>"				,    lowercase_=False				,    lowercase_=True				,    **lowercase_				,    ):
													super().__init__(
													    ByteLevelBPETokenizer(
													        vocab=lowercase_				,    merges=lowercase_				,    add_prefix_space=lowercase_				,    trim_offsets=lowercase_				,    )				,    bos_token=lowercase_				,    eos_token=lowercase_				,    unk_token=lowercase_				,    **lowercase_				,    )
													_snake_case						:					str    =   add_prefix_space



							def 	UpperCamelCase	(						self				,    lowercase_				,    lowercase_=None    ):
													_snake_case						:					List[str]    =   [self.bos_token_id] + token_ids_a + [self.eos_token_id]
													if token_ids_a is None:
																			return output

													return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]



							def 	UpperCamelCase	(						self				,    lowercase_				,    lowercase_ = None    ):
													_snake_case						:					int    =   [self.sep_token_id]
													_snake_case						:					int    =   [self.cls_token_id]

													if token_ids_a is None:
																			return len(cls + token_ids_a + sep    ) * [0]
													return len(cls + token_ids_a + sep + sep + token_ids_a + sep    ) * [0]
from __future__ import annotations

import requests

__SCREAMING_SNAKE_CASE						:   Tuple         =			set(
    'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories created_utc downs\nedited gilded gildings hidden hide_score is_created_from_ads_ui is_meta\nis_original_content is_reddit_media_domain is_video link_flair_css_class\nlink_flair_richtext link_flair_text link_flair_text_color media_embed mod_reason_title\nname permalink pwls quarantine saved score secure_media secure_media_embed selftext\nsubreddit subreddit_name_prefixed subreddit_type thumbnail title top_awarded_type\ntotal_awards_received ups upvote_ratio url user_reports'.split()
)
def  snake_case						(__lowercase ,      __lowercase = 1 ,      __lowercase = "new" ,      __lowercase = None						)	->	dict:

						'''simple docstring'''



						_snake_case						:					Union[str, Any]    =   wanted_data or []
						if invalid_search_terms := ", ".join(sorted(set(__lowercase						) - valid_terms						)						):
												_snake_case						:					List[str]    =   F"""Invalid search term: {invalid_search_terms}"""
												raise ValueError(__lowercase						)
						_snake_case						:					Any    =   requests.get(
						    F"""https://reddit.com/r/{subreddit}/{age}.json?limit={limit}""" ,      headers={"User-agent": "A random string"} ,      )
						if response.status_code == 429:
												raise requests.HTTPError

						_snake_case						:					Optional[int]    =   response.json()
						if not wanted_data:
												return {id_: data["data"]["children"][id_] for id_ in range(__lowercase						)}

						_snake_case						:					Union[str, Any]    =   {}
						for id_ in range(__lowercase						):
												_snake_case						:					Dict    =   {
												    item: data["data"]["children"][id_]["data"][item] for item in wanted_data
												}
						return data_dict


if __name__ == "__main__":
				# If you get Error 429, that means you are rate limited.Try after some time
				print(get_subreddit_data('learnpython', wanted_data=['title', 'url', 'selftext']))