"""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():
						lowerCAmelCase__						:						Optional[int]		  =			'pt'
elif is_tf_available():
						lowerCAmelCase__						:						Union[str, Any]		  =			'tf'
else:
						lowerCAmelCase__						:						Tuple		  =			'jax'
class        snake_case (				__UpperCAmelCase   ,					unittest.TestCase       ):




					"""simple docstring"""

					snake_case__       					=				PerceiverTokenizer
					snake_case__       					=				False







					def 	__lowerCAmelCase		(       self     :			str    ):
									super().setUp()
									UpperCAmelCase__    =							PerceiverTokenizer()
									tokenizer.save_pretrained(self.tmpdirname    )







					@cached_property
					def 	__lowerCAmelCase		(       self     :			Union[str, Any]    ):
									return PerceiverTokenizer.from_pretrained('deepmind/language-perceiver'    )







					def 	__lowerCAmelCase		(       self     :			Union[str, Any]					,**lowerCamelCase__     :			Optional[int]    ):
									return self.tokenizer_class.from_pretrained(self.tmpdirname					,**lowerCamelCase__    )







					def 	__lowerCAmelCase		(       self     :			Any					,lowerCamelCase__     :			Union[str, Any]					,lowerCamelCase__     :			Tuple=False					,lowerCamelCase__     :			Optional[Any]=20					,lowerCamelCase__     :			str=5    ):
									# 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.

									UpperCAmelCase__    =							[]
									for i in range(len(lowerCamelCase__    )    ):
													try:
																	UpperCAmelCase__    =							tokenizer.decode([i]					,clean_up_tokenization_spaces=lowerCamelCase__    )
													except UnicodeDecodeError:
																	pass
													toks.append((i, tok)    )

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

									# Ensure consistency
									UpperCAmelCase__    =							tokenizer.decode(lowerCamelCase__					,clean_up_tokenization_spaces=lowerCamelCase__    )
									if " " not in output_txt and len(lowerCamelCase__    ) > 1:
													UpperCAmelCase__    =							(
													    tokenizer.decode([toks_ids[0]]					,clean_up_tokenization_spaces=lowerCamelCase__    )
													    + ' '
													    + tokenizer.decode(toks_ids[1:]					,clean_up_tokenization_spaces=lowerCamelCase__    )
													)
									if with_prefix_space:
													UpperCAmelCase__    =							' ' + output_txt
									UpperCAmelCase__    =							tokenizer.encode(lowerCamelCase__					,add_special_tokens=lowerCamelCase__    )
									return output_txt, output_ids







					def 	__lowerCAmelCase		(       self     :			List[Any]    ):
									UpperCAmelCase__    =							self.perceiver_tokenizer
									UpperCAmelCase__    =							'Unicode €.'
									UpperCAmelCase__    =							tokenizer(lowerCamelCase__    )
									UpperCAmelCase__    =							[4, 91, 116, 111, 105, 117, 106, 107, 38, 232, 136, 178, 52, 5]
									self.assertEqual(encoded['input_ids']					,lowerCamelCase__    )

									# decoding
									UpperCAmelCase__    =							tokenizer.decode(lowerCamelCase__    )
									self.assertEqual(lowerCamelCase__					,'[CLS]Unicode €.[SEP]'    )

									UpperCAmelCase__    =							tokenizer('e è é ê ë'    )
									UpperCAmelCase__    =							[4, 107, 38, 201, 174, 38, 201, 175, 38, 201, 176, 38, 201, 177, 5]
									self.assertEqual(encoded['input_ids']					,lowerCamelCase__    )
									# decoding
									UpperCAmelCase__    =							tokenizer.decode(lowerCamelCase__    )
									self.assertEqual(lowerCamelCase__					,'[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 	__lowerCAmelCase		(       self     :			Union[str, Any]    ):
									UpperCAmelCase__    =							self.perceiver_tokenizer
									UpperCAmelCase__    =							['A long paragraph for summarization.', 'Another paragraph for summarization.']
									# fmt: off
									UpperCAmelCase__    =							[4, 71, 38, 114, 117, 116, 109, 38, 118, 103, 120, 103, 109, 120, 103, 118, 110, 38, 108, 117, 120, 38, 121, 123, 115, 115, 103, 120, 111, 128, 103, 122, 111, 117, 116, 52, 5, 0]
									# fmt: on
									UpperCAmelCase__    =							tokenizer(lowerCamelCase__					,padding=lowerCamelCase__					,return_tensors=lowerCamelCase__    )
									self.assertIsInstance(lowerCamelCase__					,lowerCamelCase__    )

									if FRAMEWORK != "jax":
													UpperCAmelCase__    =							list(batch.input_ids.numpy()[0]    )
									else:
													UpperCAmelCase__    =							list(batch.input_ids.tolist()[0]    )

									self.assertListEqual(lowerCamelCase__					,lowerCamelCase__    )

									self.assertEqual((2, 38)					,batch.input_ids.shape    )
									self.assertEqual((2, 38)					,batch.attention_mask.shape    )







					def 	__lowerCAmelCase		(       self     :			Any    ):
									UpperCAmelCase__    =							self.perceiver_tokenizer
									UpperCAmelCase__    =							['A long paragraph for summarization.', 'Another paragraph for summarization.']
									UpperCAmelCase__    =							tokenizer(lowerCamelCase__					,padding=lowerCamelCase__					,return_tensors=lowerCamelCase__    )
									# check if input_ids are returned and no decoder_input_ids
									self.assertIn('input_ids'					,lowerCamelCase__    )
									self.assertIn('attention_mask'					,lowerCamelCase__    )
									self.assertNotIn('decoder_input_ids'					,lowerCamelCase__    )
									self.assertNotIn('decoder_attention_mask'					,lowerCamelCase__    )







					def 	__lowerCAmelCase		(       self     :			Optional[int]    ):
									UpperCAmelCase__    =							self.perceiver_tokenizer
									UpperCAmelCase__    =							[
									    'Summary of the text.',
									    'Another summary.',
									]
									UpperCAmelCase__    =							tokenizer(
									    text_target=lowerCamelCase__					,max_length=32					,padding='max_length'					,truncation=lowerCamelCase__					,return_tensors=lowerCamelCase__    )
									self.assertEqual(32					,targets['input_ids'].shape[1]    )







					def 	__lowerCAmelCase		(       self     :			List[Any]    ):
									# safety check on max_len default value so we are sure the test works
									UpperCAmelCase__    =							self.get_tokenizers()
									for tokenizer in tokenizers:
													with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
																	self.assertNotEqual(tokenizer.model_max_length					,42    )

        # Now let's start the test
									UpperCAmelCase__    =							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
																	UpperCAmelCase__    =							tempfile.mkdtemp()

																	UpperCAmelCase__    =							' He is very happy, UNwant\u00E9d,running'
																	UpperCAmelCase__    =							tokenizer.encode(lowerCamelCase__					,add_special_tokens=lowerCamelCase__    )
																	tokenizer.save_pretrained(lowerCamelCase__    )

																	UpperCAmelCase__    =							tokenizer.__class__.from_pretrained(lowerCamelCase__    )
																	UpperCAmelCase__    =							after_tokenizer.encode(lowerCamelCase__					,add_special_tokens=lowerCamelCase__    )
																	self.assertListEqual(lowerCamelCase__					,lowerCamelCase__    )

																	shutil.rmtree(lowerCamelCase__    )

									UpperCAmelCase__    =							self.get_tokenizers(model_max_length=42    )
									for tokenizer in tokenizers:
													with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
																	# Isolate this from the other tests because we save additional tokens/etc
																	UpperCAmelCase__    =							tempfile.mkdtemp()

																	UpperCAmelCase__    =							' He is very happy, UNwant\u00E9d,running'
																	tokenizer.add_tokens(['bim', 'bambam']    )
																	UpperCAmelCase__    =							tokenizer.additional_special_tokens
																	additional_special_tokens.append('new_additional_special_token'    )
																	tokenizer.add_special_tokens({'additional_special_tokens': additional_special_tokens}    )
																	UpperCAmelCase__    =							tokenizer.encode(lowerCamelCase__					,add_special_tokens=lowerCamelCase__    )
																	tokenizer.save_pretrained(lowerCamelCase__    )

																	UpperCAmelCase__    =							tokenizer.__class__.from_pretrained(lowerCamelCase__    )
																	UpperCAmelCase__    =							after_tokenizer.encode(lowerCamelCase__					,add_special_tokens=lowerCamelCase__    )
																	self.assertListEqual(lowerCamelCase__					,lowerCamelCase__    )
																	self.assertIn('new_additional_special_token'					,after_tokenizer.additional_special_tokens    )
																	self.assertEqual(after_tokenizer.model_max_length					,42    )

																	UpperCAmelCase__    =							tokenizer.__class__.from_pretrained(lowerCamelCase__					,model_max_length=43    )
																	self.assertEqual(tokenizer.model_max_length					,43    )

																	shutil.rmtree(lowerCamelCase__    )







					def 	__lowerCAmelCase		(       self     :			List[Any]    ):
									UpperCAmelCase__    =							[]
									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(lowerCamelCase__    )

																	with open(os.path.join(lowerCamelCase__					,'special_tokens_map.json'    )					,encoding='utf-8'    ) as json_file:
																					UpperCAmelCase__    =							json.load(lowerCamelCase__    )

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

																	UpperCAmelCase__    =							[f'''<extra_id_{i}>''' for i in range(125    )]

																	UpperCAmelCase__    =							added_tokens_extra_ids + [
																	    'an_additional_special_token'
																	]
																	UpperCAmelCase__    =							added_tokens_extra_ids + [
																	    'an_additional_special_token'
																	]

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

																	# 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
																	UpperCAmelCase__    =							tokenizer_class.from_pretrained(
																	    lowerCamelCase__					,)
																	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
																	UpperCAmelCase__    =							added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'					,lstrip=lowerCamelCase__    )]
																	UpperCAmelCase__    =							tokenizer_class.from_pretrained(
																	    lowerCamelCase__					,additional_special_tokens=lowerCamelCase__					,)

																	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 	__lowerCAmelCase		(       self     :			Optional[int]    ):
									UpperCAmelCase__    =							self.perceiver_tokenizer
									self.assertEqual(tokenizer.decode([178]    )					,'�'    )







					def 	__lowerCAmelCase		(       self     :			List[str]    ):
									pass







					def 	__lowerCAmelCase		(       self     :			Optional[int]    ):
									pass







					def 	__lowerCAmelCase		(       self     :			Optional[int]    ):
									pass







					def 	__lowerCAmelCase		(       self     :			Tuple    ):
									pass







					def 	__lowerCAmelCase		(       self     :			int    ):
									# The default common tokenizer tests uses invalid tokens for Perceiver that can only accept one-character
									# strings and special added tokens as tokens
									UpperCAmelCase__    =							self.get_tokenizers(fast=lowerCamelCase__					,do_lower_case=lowerCamelCase__    )
									for tokenizer in tokenizers:
													with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
																	UpperCAmelCase__    =							['[CLS]', 't', 'h', 'i', 's', ' ', 'i', 's', ' ', 'a', ' ', 't', 'e', 's', 't', '[SEP]']
																	UpperCAmelCase__    =							tokenizer.convert_tokens_to_string(lowerCamelCase__    )

																	self.assertIsInstance(lowerCamelCase__					,lowerCamelCase__    )




"""simple docstring"""






from __future__ import annotations

from math import ceil, floor, sqrt



def 						a_		(      lowerCamelCase = 2_0_0_0_0_0_0 ):
				UpperCAmelCase__    =							[0]
				UpperCAmelCase__    =							42

				for idx in range(1      ,    ceil(sqrt(target * 2 ) * 1.1 ) ):
								triangle_numbers.append(triangle_numbers[-1] + idx )

				# we want this to be as close as possible to target
				UpperCAmelCase__    =							0
				# the area corresponding to the grid that gives the product closest to target
				UpperCAmelCase__    =							0
				# an estimate of b, using the quadratic formula
				UpperCAmelCase__    =							42
				# the largest integer less than b_estimate
				UpperCAmelCase__    =							42
				# the largest integer less than b_estimate
				UpperCAmelCase__    =							42
				# the triangle number corresponding to b_floor
				UpperCAmelCase__    =							42
				# the triangle number corresponding to b_ceil
				UpperCAmelCase__    =							42

				for idx_a, triangle_a in enumerate(triangle_numbers[1:]      ,    1 ):
								UpperCAmelCase__    =							(-1 + sqrt(1 + 8 * target / triangle_a )) / 2
								UpperCAmelCase__    =							floor(lowerCamelCase )
								UpperCAmelCase__    =							ceil(lowerCamelCase )
								UpperCAmelCase__    =							triangle_numbers[b_floor]
								UpperCAmelCase__    =							triangle_numbers[b_ceil]

								if abs(target - triangle_b_first_guess * triangle_a ) < abs(
								    target - best_product ):
												UpperCAmelCase__    =							triangle_b_first_guess * triangle_a
												UpperCAmelCase__    =							idx_a * b_floor

								if abs(target - triangle_b_second_guess * triangle_a ) < abs(
								    target - best_product ):
												UpperCAmelCase__    =							triangle_b_second_guess * triangle_a
												UpperCAmelCase__    =							idx_a * b_ceil

				return area


if __name__ == "__main__":
						print(F"""{solution() = }""")



