
"""simple docstring"""
import copy
import os
from typing import Union

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


_a      :			Any					=							logging.get_logger(__name__)

_a      :			Any					=							{
    """BAAI/AltCLIP""": """https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json""",
    # See all AltCLIP models at https://huggingface.co/models?filter=altclip
}






class      _UpperCAmelCase				(					_UpperCamelCase):
       __lowercase							: List[str]  =					"altclip_text_model"
       def __init__(    self						,    snake_case_=25_00_02						,    snake_case_=10_24						,    snake_case_=24						,    snake_case_=16						,    snake_case_=40_96						,    snake_case_="gelu"						,    snake_case_=0.1						,    snake_case_=0.1						,    snake_case_=5_14						,    snake_case_=1						,    snake_case_=0.02						,    snake_case_=0.02						,    snake_case_=1E-05						,    snake_case_=1						,    snake_case_=0						,    snake_case_=2						,    snake_case_="absolute"						,    snake_case_=True						,    snake_case_=7_68						,    **snake_case_						,    ):
         super().__init__(pad_token_id=__a						,    bos_token_id=__a						,    eos_token_id=__a						,    **__a     )

         _snake_case     :						Union[str, Any]						=   vocab_size
         _snake_case     :						Optional[int]						=   hidden_size
         _snake_case     :						Tuple						=   num_hidden_layers
         _snake_case     :						Tuple						=   num_attention_heads
         _snake_case     :						int						=   hidden_act
         _snake_case     :						Any						=   intermediate_size
         _snake_case     :						Union[str, Any]						=   hidden_dropout_prob
         _snake_case     :						Dict						=   attention_probs_dropout_prob
         _snake_case     :						List[str]						=   max_position_embeddings
         _snake_case     :						List[str]						=   type_vocab_size
         _snake_case     :						Dict						=   initializer_range
         _snake_case     :						List[str]						=   initializer_factor
         _snake_case     :						Union[str, Any]						=   layer_norm_eps
         _snake_case     :						Tuple						=   position_embedding_type
         _snake_case     :						Optional[Any]						=   use_cache
         _snake_case     :						Optional[int]						=   project_dim






class      _UpperCAmelCase				(					_UpperCamelCase):
       __lowercase							: List[str]  =					"altclip_vision_model"
       def __init__(    self						,    snake_case_=7_68						,    snake_case_=30_72						,    snake_case_=5_12						,    snake_case_=12						,    snake_case_=12						,    snake_case_=3						,    snake_case_=2_24						,    snake_case_=32						,    snake_case_="quick_gelu"						,    snake_case_=1E-5						,    snake_case_=0.0						,    snake_case_=0.02						,    snake_case_=1.0						,    **snake_case_						,    ):
         super().__init__(**__a     )

         _snake_case     :						int						=   hidden_size
         _snake_case     :						Optional[int]						=   intermediate_size
         _snake_case     :						Any						=   projection_dim
         _snake_case     :						Tuple						=   num_hidden_layers
         _snake_case     :						List[str]						=   num_attention_heads
         _snake_case     :						List[Any]						=   num_channels
         _snake_case     :						Dict						=   patch_size
         _snake_case     :						Any						=   image_size
         _snake_case     :						List[str]						=   initializer_range
         _snake_case     :						List[str]						=   initializer_factor
         _snake_case     :						Optional[Any]						=   attention_dropout
         _snake_case     :						Union[str, Any]						=   layer_norm_eps
         _snake_case     :						Dict						=   hidden_act


       @classmethod
       def 					lowerCamelCase__	(    cls						,    snake_case_						,    **snake_case_     ):
         cls._set_token_in_kwargs(__a     )

         _snake_case     :						int						=   cls.get_config_dict(__a						,    **__a     )

         # get the vision config dict if we are loading from AltCLIPConfig
         if config_dict.get("model_type"     ) == "altclip":
           _snake_case     :						Tuple						=   config_dict["vision_config"]

         if "model_type" in config_dict and hasattr(cls						,    "model_type"     ) and config_dict["model_type"] != cls.model_type:
           logger.warning(
               F'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
               F'{cls.model_type}. This is not supported for all configurations of models and can yield errors.'     )

         return cls.from_dict(__a						,    **__a     )






class      _UpperCAmelCase				(					_UpperCamelCase):
       __lowercase							: Any  =					"altclip"
       __lowercase							: List[str]  =					True
       def __init__(    self						,    snake_case_=None						,    snake_case_=None						,    snake_case_=7_68						,    snake_case_=2.6592						,    **snake_case_     ):
         # If `_config_dict` exist, we use them for the backward compatibility.
         # We pop out these 2 attributes before calling `super().__init__` to avoid them being saved (which causes a lot
         # of confusion!).
         _snake_case     :						Tuple						=   kwargs.pop("text_config_dict"						,    __a     )
         _snake_case     :						Tuple						=   kwargs.pop("vision_config_dict"						,    __a     )

         super().__init__(**__a     )

         # Instead of simply assigning `[text|vision]_config_dict` to `[text|vision]_config`, we use the values in
         # `[text|vision]_config_dict` to update the values in `[text|vision]_config`. The values should be same in most
         # cases, but we don't want to break anything regarding `_config_dict` that existed before commit `8827e1b2`.
         if text_config_dict is not None:
           if text_config is None:
             _snake_case     :						int						=   {}

           # This is the complete result when using `text_config_dict`.
           _snake_case     :						Any						=   AltCLIPTextConfig(**__a     ).to_dict()

           # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
           for key, value in _text_config_dict.items():
             if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
               # If specified in `text_config_dict`
               if key in text_config_dict:
                 _snake_case     :						Optional[int]						=   (
                     F'`{key}` is found in both `text_config_dict` and `text_config` but with different values. '
                     F'The value `text_config_dict["{key}"]` will be used instead.'
                 )
               # If inferred from default argument values (just to be super careful)
               else:
                 _snake_case     :						Union[str, Any]						=   (
                     F'`text_config_dict` is provided which will be used to initialize `AltCLIPTextConfig`. The '
                     F'value `text_config["{key}"]` will be overriden.'
                 )
               logger.warning(__a     )

            # Update all values in `text_config` with the ones in `_text_config_dict`.
           text_config.update(_text_config_dict     )

         if vision_config_dict is not None:
           if vision_config is None:
             _snake_case     :						int						=   {}

           # This is the complete result when using `vision_config_dict`.
           _snake_case     :						List[Any]						=   AltCLIPVisionConfig(**__a     ).to_dict()
           # convert keys to string instead of integer
           if "id2label" in _vision_config_dict:
             _snake_case     :						Dict						=   {
                 str(__a     ): value for key, value in _vision_config_dict["id2label"].items()
             }

           # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
           for key, value in _vision_config_dict.items():
             if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
               # If specified in `vision_config_dict`
               if key in vision_config_dict:
                 _snake_case     :						Optional[int]						=   (
                     F'`{key}` is found in both `vision_config_dict` and `vision_config` but with different '
                     F'values. The value `vision_config_dict["{key}"]` will be used instead.'
                 )
               # If inferred from default argument values (just to be super careful)
               else:
                 _snake_case     :						Optional[Any]						=   (
                     F'`vision_config_dict` is provided which will be used to initialize `AltCLIPVisionConfig`. '
                     F'The value `vision_config["{key}"]` will be overriden.'
                 )
               logger.warning(__a     )

            # Update all values in `vision_config` with the ones in `_vision_config_dict`.
           vision_config.update(_vision_config_dict     )

         if text_config is None:
           _snake_case     :						Optional[Any]						=   {}
           logger.info("`text_config` is `None`. Initializing the `AltCLIPTextConfig` with default values."     )

         if vision_config is None:
           _snake_case     :						Dict						=   {}
           logger.info("`vision_config` is `None`. initializing the `AltCLIPVisionConfig` with default values."     )

         _snake_case     :						Union[str, Any]						=   AltCLIPTextConfig(**__a     )
         _snake_case     :						Dict						=   AltCLIPVisionConfig(**__a     )

         _snake_case     :						Any						=   projection_dim
         _snake_case     :						Union[str, Any]						=   logit_scale_init_value
         _snake_case     :						Optional[Any]						=   1.0
       @classmethod
       def 					lowerCamelCase__	(    cls						,    snake_case_						,    snake_case_						,    **snake_case_     ):
         return cls(text_config=text_config.to_dict()						,    vision_config=vision_config.to_dict()						,    **__a     )


       def 					lowerCamelCase__	(    self     ):
         _snake_case     :						Union[str, Any]						=   copy.deepcopy(self.__dict__     )
         _snake_case     :						List[str]						=   self.text_config.to_dict()
         _snake_case     :						int						=   self.vision_config.to_dict()
         _snake_case     :						Optional[int]						=   self.__class__.model_type
         return output



"""simple docstring"""
from __future__ import annotations

import requests

_a      :			List[str]					=							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 				a__   (   a   :				str       ,     a   :				int = 1       ,     a   :				str = "new"       ,     a   :				list | None = None		):

  """simple docstring"""







  _snake_case     :						Any						=   wanted_data or []
  if invalid_search_terms := ", ".join(sorted(set(a		) - valid_terms		)		):
    _snake_case     :						Optional[int]						=   f'Invalid search term: {invalid_search_terms}'
    raise ValueError(a		)
  _snake_case     :						int						=   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[Any]						=   response.json()
  if not wanted_data:
    return {id_: data["data"]["children"][id_] for id_ in range(a		)}

  _snake_case     :						Tuple						=   {}
  for id_ in range(a		):
    _snake_case     :						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"""]))

