"""simple docstring"""





import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
       _UpperCamelCase   :						str      =    '''pt'''
elif is_tf_available():
       _UpperCamelCase   :						Optional[Any]      =    '''tf'''
else:
       _UpperCamelCase   :						Tuple      =    '''jax'''


class      UpperCAmelCase_	(    _lowercase ,							unittest.TestCase):
      lowerCamelCase__		:    Dict   =  PerceiverTokenizer
      lowerCamelCase__		:    Optional[int]   =  False


      def 		_UpperCAmelCase       (   self							)       ->					List[Any]:
             super().setUp()
             lowercase__			:		Optional[int]       =	PerceiverTokenizer()
             tokenizer.save_pretrained(self.tmpdirname							)


      @cached_property
      def 		_UpperCAmelCase       (   self							)       ->					int:
             return PerceiverTokenizer.from_pretrained('deepmind/language-perceiver'							)


      def 		_UpperCAmelCase       (   self		,			**a							)       ->					Any:
             return self.tokenizer_class.from_pretrained(self.tmpdirname		,			**UpperCamelCase__							)


      def 		_UpperCAmelCase       (   self		,			a		,			a=False		,			a=2_0		,			a=5							)       ->					Dict:
             # XXX The default common tokenizer tests assume that every ID is decodable on its own.
             # This assumption is invalid for Perceiver because single bytes might not be
             # valid utf-8 (byte 128 for instance).
             # Here we're overriding the smallest possible method to provide
             # a clean sequence without making the same assumption.

             lowercase__			:		List[str]       =	[]
             for i in range(len(UpperCamelCase__							)							):
                    try:
                           lowercase__			:		str       =	tokenizer.decode([i]		,			clean_up_tokenization_spaces=UpperCamelCase__							)
                    except UnicodeDecodeError:
                           pass
                    toks.append((i, tok)							)

             lowercase__			:		Any       =	list(filter(lambda a							: re.match(R'^[ a-zA-Z]+$'		,			t[1]							)		,			UpperCamelCase__							)							)
             lowercase__			:		str       =	list(filter(lambda a							: [t[0]] == tokenizer.encode(t[1]		,			add_special_tokens=UpperCamelCase__							)		,			UpperCamelCase__							)							)
             if max_length is not None and len(UpperCamelCase__							) > max_length:
                    lowercase__			:		str       =	toks[:max_length]
             if min_length is not None and len(UpperCamelCase__							) < min_length and len(UpperCamelCase__							) > 0:
                    while len(UpperCamelCase__							) < min_length:
                           lowercase__			:		Any       =	toks + toks
        # toks_str = [t[1] for t in toks]
             lowercase__			:		Optional[Any]       =	[t[0] for t in toks]

             # Ensure consistency
             lowercase__			:		List[Any]       =	tokenizer.decode(UpperCamelCase__		,			clean_up_tokenization_spaces=UpperCamelCase__							)
             if " " not in output_txt and len(UpperCamelCase__							) > 1:
                    lowercase__			:		Optional[int]       =	(
                        tokenizer.decode([toks_ids[0]]		,			clean_up_tokenization_spaces=UpperCamelCase__							)
                        + """ """
                        + tokenizer.decode(toks_ids[1:]		,			clean_up_tokenization_spaces=UpperCamelCase__							)
                    )
             if with_prefix_space:
                    lowercase__			:		List[Any]       =	""" """ + output_txt
             lowercase__			:		str       =	tokenizer.encode(UpperCamelCase__		,			add_special_tokens=UpperCamelCase__							)
             return output_txt, output_ids


      def 		_UpperCAmelCase       (   self							)       ->					Dict:
             lowercase__			:		Union[str, Any]       =	self.perceiver_tokenizer
             lowercase__			:		List[str]       =	"""Unicode €."""
             lowercase__			:		Any       =	tokenizer(UpperCamelCase__							)
             lowercase__			:		str       =	[4, 9_1, 1_1_6, 1_1_1, 1_0_5, 1_1_7, 1_0_6, 1_0_7, 3_8, 2_3_2, 1_3_6, 1_7_8, 5_2, 5]
             self.assertEqual(encoded['input_ids']		,			UpperCamelCase__							)

             # decoding
             lowercase__			:		Tuple       =	tokenizer.decode(UpperCamelCase__							)
             self.assertEqual(UpperCamelCase__		,			'[CLS]Unicode €.[SEP]'							)

             lowercase__			:		Dict       =	tokenizer('e è é ê ë'							)
             lowercase__			:		str       =	[4, 1_0_7, 3_8, 2_0_1, 1_7_4, 3_8, 2_0_1, 1_7_5, 3_8, 2_0_1, 1_7_6, 3_8, 2_0_1, 1_7_7, 5]
             self.assertEqual(encoded['input_ids']		,			UpperCamelCase__							)
             # decoding
             lowercase__			:		List[str]       =	tokenizer.decode(UpperCamelCase__							)
             self.assertEqual(UpperCamelCase__		,			'[CLS]e è é ê ë[SEP]'							)

             # encode/decode, but with `encode` instead of `__call__`
             self.assertEqual(tokenizer.decode(tokenizer.encode('e è é ê ë'							)							)		,			'[CLS]e è é ê ë[SEP]'							)


      def 		_UpperCAmelCase       (   self							)       ->					str:
             lowercase__			:		Optional[Any]       =	self.perceiver_tokenizer
             lowercase__			:		List[Any]       =	["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
             # fmt: off
             lowercase__			:		Optional[Any]       =	[4, 7_1, 3_8, 1_1_4, 1_1_7, 1_1_6, 1_0_9, 3_8, 1_1_8, 1_0_3, 1_2_0, 1_0_3, 1_0_9, 1_2_0, 1_0_3, 1_1_8, 1_1_0, 3_8, 1_0_8, 1_1_7, 1_2_0, 3_8, 1_2_1, 1_2_3, 1_1_5, 1_1_5, 1_0_3, 1_2_0, 1_1_1, 1_2_8, 1_0_3, 1_2_2, 1_1_1, 1_1_7, 1_1_6, 5_2, 5, 0]
             # fmt: on
             lowercase__			:		Optional[Any]       =	tokenizer(UpperCamelCase__		,			padding=UpperCamelCase__		,			return_tensors=UpperCamelCase__							)
             self.assertIsInstance(UpperCamelCase__		,			UpperCamelCase__							)

             if FRAMEWORK != "jax":
                    lowercase__			:		Union[str, Any]       =	list(batch.input_ids.numpy()[0]							)
             else:
                    lowercase__			:		Dict       =	list(batch.input_ids.tolist()[0]							)

             self.assertListEqual(UpperCamelCase__		,			UpperCamelCase__							)

             self.assertEqual((2, 3_8)		,			batch.input_ids.shape							)
             self.assertEqual((2, 3_8)		,			batch.attention_mask.shape							)


      def 		_UpperCAmelCase       (   self							)       ->					Optional[Any]:
             lowercase__			:		Optional[Any]       =	self.perceiver_tokenizer
             lowercase__			:		int       =	["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
             lowercase__			:		Optional[int]       =	tokenizer(UpperCamelCase__		,			padding=UpperCamelCase__		,			return_tensors=UpperCamelCase__							)
             # check if input_ids are returned and no decoder_input_ids
             self.assertIn('input_ids'		,			UpperCamelCase__							)
             self.assertIn('attention_mask'		,			UpperCamelCase__							)
             self.assertNotIn('decoder_input_ids'		,			UpperCamelCase__							)
             self.assertNotIn('decoder_attention_mask'		,			UpperCamelCase__							)


      def 		_UpperCAmelCase       (   self							)       ->					Union[str, Any]:
             lowercase__			:		List[str]       =	self.perceiver_tokenizer
             lowercase__			:		Dict       =	[
                 """Summary of the text.""",
                 """Another summary.""",
             ]
             lowercase__			:		Any       =	tokenizer(
                 text_target=UpperCamelCase__		,			max_length=3_2		,			padding='max_length'		,			truncation=UpperCamelCase__		,			return_tensors=UpperCamelCase__							)
             self.assertEqual(3_2		,			targets['input_ids'].shape[1]							)


      def 		_UpperCAmelCase       (   self							)       ->					Tuple:
             # safety check on max_len default value so we are sure the test works
             lowercase__			:		List[str]       =	self.get_tokenizers()
             for tokenizer in tokenizers:
                    with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
                           self.assertNotEqual(tokenizer.model_max_length		,			4_2							)

        # Now let's start the test
             lowercase__			:		Any       =	self.get_tokenizers()
             for tokenizer in tokenizers:
                    with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
                           # Isolate this from the other tests because we save additional tokens/etc
                           lowercase__			:		Optional[int]       =	tempfile.mkdtemp()

                           lowercase__			:		int       =	""" He is very happy, UNwant\u00E9d,running"""
                           lowercase__			:		Any       =	tokenizer.encode(UpperCamelCase__		,			add_special_tokens=UpperCamelCase__							)
                           tokenizer.save_pretrained(UpperCamelCase__							)

                           lowercase__			:		Union[str, Any]       =	tokenizer.__class__.from_pretrained(UpperCamelCase__							)
                           lowercase__			:		Optional[int]       =	after_tokenizer.encode(UpperCamelCase__		,			add_special_tokens=UpperCamelCase__							)
                           self.assertListEqual(UpperCamelCase__		,			UpperCamelCase__							)

                           shutil.rmtree(UpperCamelCase__							)

             lowercase__			:		Dict       =	self.get_tokenizers(model_max_length=4_2							)
             for tokenizer in tokenizers:
                    with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
                           # Isolate this from the other tests because we save additional tokens/etc
                           lowercase__			:		Optional[int]       =	tempfile.mkdtemp()

                           lowercase__			:		str       =	""" He is very happy, UNwant\u00E9d,running"""
                           tokenizer.add_tokens(['bim', 'bambam']							)
                           lowercase__			:		Any       =	tokenizer.additional_special_tokens
                           additional_special_tokens.append('new_additional_special_token'							)
                           tokenizer.add_special_tokens({'additional_special_tokens': additional_special_tokens}							)
                           lowercase__			:		int       =	tokenizer.encode(UpperCamelCase__		,			add_special_tokens=UpperCamelCase__							)
                           tokenizer.save_pretrained(UpperCamelCase__							)

                           lowercase__			:		Optional[Any]       =	tokenizer.__class__.from_pretrained(UpperCamelCase__							)
                           lowercase__			:		int       =	after_tokenizer.encode(UpperCamelCase__		,			add_special_tokens=UpperCamelCase__							)
                           self.assertListEqual(UpperCamelCase__		,			UpperCamelCase__							)
                           self.assertIn('new_additional_special_token'		,			after_tokenizer.additional_special_tokens							)
                           self.assertEqual(after_tokenizer.model_max_length		,			4_2							)

                           lowercase__			:		Optional[int]       =	tokenizer.__class__.from_pretrained(UpperCamelCase__		,			model_max_length=4_3							)
                           self.assertEqual(tokenizer.model_max_length		,			4_3							)

                           shutil.rmtree(UpperCamelCase__							)


      def 		_UpperCAmelCase       (   self							)       ->					Any:
             lowercase__			:		Tuple       =	[]
             if self.test_slow_tokenizer:
                    tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())							)

             if self.test_rust_tokenizer:
                    tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())							)

             for tokenizer_class, tokenizer_utils in tokenizer_list:
                    with tempfile.TemporaryDirectory() as tmp_dir:
                           tokenizer_utils.save_pretrained(UpperCamelCase__							)

                           with open(os.path.join(UpperCamelCase__		,			'special_tokens_map.json'							)		,			encoding='utf-8'							) as json_file:
                                  lowercase__			:		Optional[Any]       =	json.load(UpperCamelCase__							)

                           with open(os.path.join(UpperCamelCase__		,			'tokenizer_config.json'							)		,			encoding='utf-8'							) as json_file:
                                  lowercase__			:		Dict       =	json.load(UpperCamelCase__							)

                           lowercase__			:		int       =	[f"""<extra_id_{i}>""" for i in range(1_2_5							)]

                           lowercase__			:		str       =	added_tokens_extra_ids + [
                               """an_additional_special_token"""
                           ]
                           lowercase__			:		Any       =	added_tokens_extra_ids + [
                               """an_additional_special_token"""
                           ]

                           with open(os.path.join(UpperCamelCase__		,			'special_tokens_map.json'							)		,			'w'		,			encoding='utf-8'							) as outfile:
                                  json.dump(UpperCamelCase__		,			UpperCamelCase__							)
                           with open(os.path.join(UpperCamelCase__		,			'tokenizer_config.json'							)		,			'w'		,			encoding='utf-8'							) as outfile:
                                  json.dump(UpperCamelCase__		,			UpperCamelCase__							)

                           # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
                           # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
                           # "special_tokens_map.json" files
                           lowercase__			:		Union[str, Any]       =	tokenizer_class.from_pretrained(
                               UpperCamelCase__		,			)
                           self.assertIn(
                               'an_additional_special_token'		,			tokenizer_without_change_in_init.additional_special_tokens							)
                           self.assertEqual(
                               ['an_additional_special_token']		,			tokenizer_without_change_in_init.convert_ids_to_tokens(
                                   tokenizer_without_change_in_init.convert_tokens_to_ids(['an_additional_special_token']							)							)		,			)

                           # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                           lowercase__			:		int       =	added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'		,			lstrip=UpperCamelCase__							)]
                           lowercase__			:		Any       =	tokenizer_class.from_pretrained(
                               UpperCamelCase__		,			additional_special_tokens=UpperCamelCase__		,			)

                           self.assertIn('a_new_additional_special_token'		,			tokenizer.additional_special_tokens							)
                           self.assertEqual(
                               ['a_new_additional_special_token']		,			tokenizer.convert_ids_to_tokens(
                                   tokenizer.convert_tokens_to_ids(['a_new_additional_special_token']							)							)		,			)


      def 		_UpperCAmelCase       (   self							)       ->					List[str]:
             lowercase__			:		Union[str, Any]       =	self.perceiver_tokenizer
             self.assertEqual(tokenizer.decode([1_7_8]							)		,			'�'							)


      def 		_UpperCAmelCase       (   self							)       ->					Dict:
             pass


      def 		_UpperCAmelCase       (   self							)       ->					int:
             pass


      def 		_UpperCAmelCase       (   self							)       ->					Union[str, Any]:
             pass


      def 		_UpperCAmelCase       (   self							)       ->					Dict:
             pass


      def 		_UpperCAmelCase       (   self							)       ->					Any:
             # The default common tokenizer tests uses invalid tokens for Perceiver that can only accept one-character
             # strings and special added tokens as tokens
             lowercase__			:		List[Any]       =	self.get_tokenizers(fast=UpperCamelCase__		,			do_lower_case=UpperCamelCase__							)
             for tokenizer in tokenizers:
                    with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
                           lowercase__			:		List[str]       =	["""[CLS]""", """t""", """h""", """i""", """s""", """ """, """i""", """s""", """ """, """a""", """ """, """t""", """e""", """s""", """t""", """[SEP]"""]
                           lowercase__			:		Tuple       =	tokenizer.convert_tokens_to_string(UpperCamelCase__							)

                           self.assertIsInstance(UpperCamelCase__		,			UpperCamelCase__							)









'''simple docstring'''







from __future__ import annotations

import requests

_A	:			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  SCREAMING_SNAKE_CASE_       (UpperCamelCase				,			UpperCamelCase = 1				,			UpperCamelCase = "new"				,			UpperCamelCase = None      )      ->       dict:
							lowerCamelCase__					:	Any         =       wanted_data or []
							if invalid_search_terms := ", ".join(sorted(set(UpperCamelCase      ) - valid_terms      )      ):
														lowerCamelCase__					:	str         =       f'''Invalid search term: {invalid_search_terms}'''
														raise ValueError(UpperCamelCase      )
							lowerCamelCase__					:	str         =       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

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

							lowerCamelCase__					:	Dict         =       {}
							for id_ in range(UpperCamelCase      ):
														lowerCamelCase__					:	Union[str, Any]         =       {
														    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''']))

