

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


_UpperCAmelCase            =		logging.get_logger(__name__)

_UpperCAmelCase            =		{
    """alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}





class UpperCAmelCase						( __A  ):


				'''simple docstring'''






				lowerCamelCase_    = '''mgp-str'''
				def __init__(						self		,     lowercase=[3_2, 1_2_8]		,     lowercase=4		,     lowercase=3		,     lowercase=2_7		,     lowercase=3_8		,     lowercase=5_0_2_5_7		,     lowercase=3_0_5_2_2		,     lowercase=7_6_8		,     lowercase=1_2		,     lowercase=1_2		,     lowercase=4.0		,     lowercase=True		,     lowercase=False		,     lowercase=1E-5		,     lowercase=0.0		,     lowercase=0.0		,     lowercase=0.0		,     lowercase=False		,     lowercase=0.02		,     **lowercase		,     ):



						"""simple docstring"""





						super().__init__(**lowercase )

						A_		:    List[str]         =				image_size
						A_		:    str         =				patch_size
						A_		:    Optional[Any]         =				num_channels
						A_		:    List[Any]         =				max_token_length
						A_		:    str         =				num_character_labels
						A_		:    Optional[int]         =				num_bpe_labels
						A_		:    Optional[int]         =				num_wordpiece_labels
						A_		:    Any         =				hidden_size
						A_		:    Optional[int]         =				num_hidden_layers
						A_		:    List[Any]         =				num_attention_heads
						A_		:    Union[str, Any]         =				mlp_ratio
						A_		:    Optional[int]         =				distilled
						A_		:    Tuple         =				layer_norm_eps
						A_		:    int         =				drop_rate
						A_		:    Dict         =				qkv_bias
						A_		:    str         =				attn_drop_rate
						A_		:    int         =				drop_path_rate
						A_		:    Optional[Any]         =				output_aa_attentions
						A_		:    Optional[int]         =				initializer_range







from __future__ import annotations

import requests

_UpperCAmelCase            =		set(
    """approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories created_utc downs
edited gilded gildings hidden hide_score is_created_from_ads_ui is_meta
is_original_content is_reddit_media_domain is_video link_flair_css_class
link_flair_richtext link_flair_text link_flair_text_color media_embed mod_reason_title
name permalink pwls quarantine saved score secure_media secure_media_embed selftext
subreddit subreddit_name_prefixed subreddit_type thumbnail title top_awarded_type
total_awards_received ups upvote_ratio url user_reports""".split()
)




def     UpperCamelCase						(	__lowercase						:			str						,__lowercase						:			int = 1						,__lowercase						:			str = "new"						,__lowercase						:			list | None = None     ):
		'''simple docstring'''




		A_		:    Tuple         =				wanted_data or []
		if invalid_search_terms := ", ".join(sorted(set(__lowercase     ) - valid_terms     )     ):
				A_		:    int         =				f'''Invalid search term: {invalid_search_terms}'''
				raise ValueError(__lowercase     )
		A_		:    Optional[int]         =				requests.get(
		    f'''https://reddit.com/r/{subreddit}/{age}.json?limit={limit}'''						,headers={'User-agent': 'A random string'}						,)
		if response.status_code == 4_29:
				raise requests.HTTPError

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

		A_		:    Union[str, Any]         =				{}
		for id_ in range(__lowercase     ):
				A_		:    List[str]         =				{
				    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"""]))






