"""simple docstring"""







import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 		UpperCamelCase      (   SCREAMING_SNAKE_CASE_				,     unittest.TestCase						):
				UpperCAmelCase    :				List[Any]   =		LEDTokenizer
				UpperCAmelCase    :				Union[str, Any]   =		LEDTokenizerFast
				UpperCAmelCase    :				int   =		True



				def  _lowercase					(self    :				int)   ->     int:
					super().setUp()
					__snake_case      :							Optional[int]						=			[
					    'l',
					    'o',
					    'w',
					    'e',
					    'r',
					    's',
					    't',
					    'i',
					    'd',
					    'n',
					    '\u0120',
					    '\u0120l',
					    '\u0120n',
					    '\u0120lo',
					    '\u0120low',
					    'er',
					    '\u0120lowest',
					    '\u0120newer',
					    '\u0120wider',
					    '<unk>',
					]
					__snake_case      :							List[Any]						=			dict(zip(snake_case__     ,  range(len(snake_case__))))
					__snake_case      :							Optional[int]						=			['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
					__snake_case      :							str						=			{'unk_token': '<unk>'}

					__snake_case      :							Union[str, Any]						=			os.path.join(self.tmpdirname     ,  VOCAB_FILES_NAMES['vocab_file'])
					__snake_case      :							int						=			os.path.join(self.tmpdirname     ,  VOCAB_FILES_NAMES['merges_file'])
					with open(self.vocab_file     ,  'w'     ,  encoding='utf-8') as fp:
						fp.write(json.dumps(snake_case__) + '\n')
					with open(self.merges_file     ,  'w'     ,  encoding='utf-8') as fp:
						fp.write('\n'.join(snake_case__))



				def  _lowercase					(self    :				List[Any]     ,  **_A    :				Union[str, Any])   ->     Optional[int]:
					kwargs.update(self.special_tokens_map)
					return self.tokenizer_class.from_pretrained(self.tmpdirname     ,  **snake_case__)



				def  _lowercase					(self    :				Union[str, Any]     ,  **_A    :				Optional[int])   ->     Optional[int]:
					kwargs.update(self.special_tokens_map)
					return self.rust_tokenizer_class.from_pretrained(self.tmpdirname     ,  **snake_case__)



				def  _lowercase					(self    :				Any     ,  _A    :				Optional[Any])   ->     int:
					return "lower newer", "lower newer"



				@cached_property
				def  _lowercase					(self    :				Any)   ->     Dict:
					return LEDTokenizer.from_pretrained('allenai/led-base-16384')



				@cached_property
				def  _lowercase					(self    :				Any)   ->     Any:
					return LEDTokenizerFast.from_pretrained('allenai/led-base-16384')



				@require_torch
				def  _lowercase					(self    :				str)   ->     str:
					__snake_case      :							Optional[int]						=			['A long paragraph for summarization.', 'Another paragraph for summarization.']
					__snake_case      :							Optional[Any]						=			[0, 2_50, 2_51, 1_78_18, 13, 3_91_86, 19_38, 4, 2]

					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
						__snake_case      :							Dict						=			tokenizer(snake_case__     ,  max_length=len(snake_case__)     ,  padding=snake_case__     ,  return_tensors='pt')
						self.assertIsInstance(snake_case__     ,  snake_case__)

						self.assertEqual((2, 9)     ,  batch.input_ids.shape)
						self.assertEqual((2, 9)     ,  batch.attention_mask.shape)
						__snake_case      :							str						=			batch.input_ids.tolist()[0]
						self.assertListEqual(snake_case__     ,  snake_case__)



				@require_torch
				def  _lowercase					(self    :				Tuple)   ->     str:
					__snake_case      :							List[str]						=			['A long paragraph for summarization.', 'Another paragraph for summarization.']
					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
						__snake_case      :							Dict						=			tokenizer(snake_case__     ,  padding=snake_case__     ,  return_tensors='pt')
						self.assertIn('input_ids'     ,  snake_case__)
						self.assertIn('attention_mask'     ,  snake_case__)
						self.assertNotIn('labels'     ,  snake_case__)
						self.assertNotIn('decoder_attention_mask'     ,  snake_case__)



				@require_torch
				def  _lowercase					(self    :				Optional[int])   ->     str:
					__snake_case      :							str						=			[
					    'Summary of the text.',
					    'Another summary.',
					]
					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
						__snake_case      :							int						=			tokenizer(text_target=snake_case__     ,  max_length=32     ,  padding='max_length'     ,  return_tensors='pt')
						self.assertEqual(32     ,  targets['input_ids'].shape[1])



				@require_torch
				def  _lowercase					(self    :				int)   ->     int:

					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
						__snake_case      :							List[Any]						=			tokenizer(
						    ['I am a small frog' * 10_24, 'I am a small frog']     ,  padding=snake_case__     ,  truncation=snake_case__     ,  return_tensors='pt')
						self.assertIsInstance(snake_case__     ,  snake_case__)
						self.assertEqual(batch.input_ids.shape     ,  (2, 51_22))



				@require_torch
				def  _lowercase					(self    :				Tuple)   ->     Optional[Any]:
					__snake_case      :							str						=			['A long paragraph for summarization.']
					__snake_case      :							str						=			[
					    'Summary of the text.',
					]
					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
						__snake_case      :							int						=			tokenizer(snake_case__     ,  return_tensors='pt')
						__snake_case      :							List[Any]						=			tokenizer(text_target=snake_case__     ,  return_tensors='pt')
						__snake_case      :							str						=			inputs['input_ids']
						__snake_case      :							int						=			targets['input_ids']
						self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item())
						self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item())
						self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item())
						self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item())



				@require_torch
				def  _lowercase					(self    :				Tuple)   ->     Any:

					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
						__snake_case      :							int						=			['Summary of the text.', 'Another summary.']
						__snake_case      :							Dict						=			[[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

						__snake_case      :							List[Any]						=			tokenizer(snake_case__     ,  padding=snake_case__)
						__snake_case      :							Tuple						=			[[0] * len(snake_case__) for x in encoded_output['input_ids']]
						__snake_case      :							Optional[Any]						=			tokenizer.pad(snake_case__)
						self.assertSequenceEqual(outputs['global_attention_mask']     ,  snake_case__)



				def  _lowercase					(self    :				Dict)   ->     str:
					pass






				def  _lowercase					(self    :				List[str])   ->     List[Any]:

					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
							__snake_case      :							Optional[int]						=			self.rust_tokenizer_class.from_pretrained(snake_case__     ,  **snake_case__)
							__snake_case      :							Tuple						=			self.tokenizer_class.from_pretrained(snake_case__     ,  **snake_case__)
							__snake_case      :							List[str]						=			'A, <mask> AllenNLP sentence.'
							__snake_case      :							Union[str, Any]						=			tokenizer_r.encode_plus(snake_case__     ,  add_special_tokens=snake_case__     ,  return_token_type_ids=snake_case__)
							__snake_case      :							Dict						=			tokenizer_p.encode_plus(snake_case__     ,  add_special_tokens=snake_case__     ,  return_token_type_ids=snake_case__)
							self.assertEqual(sum(tokens_r['token_type_ids'])     ,  sum(tokens_p['token_type_ids']))
							self.assertEqual(
							    sum(tokens_r['attention_mask']) / len(tokens_r['attention_mask'])     ,  sum(tokens_p['attention_mask']) / len(tokens_p['attention_mask'])     ,  )

							__snake_case      :							List[str]						=			tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids'])
							__snake_case      :							str						=			tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids'])
							self.assertSequenceEqual(tokens_p['input_ids']     ,  [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2])
							self.assertSequenceEqual(tokens_r['input_ids']     ,  [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2])

							self.assertSequenceEqual(
							    snake_case__     ,  ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>'])
							self.assertSequenceEqual(
							    snake_case__     ,  ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>'])






"""simple docstring"""







import itertools
import string
from collections.abc import Generator, Iterable
def   __UpperCAmelCase    (   UpperCAmelCase_   :    Iterable[str]      ,							UpperCAmelCase_   :    int  )							->      Generator[tuple[str, ...], None, None]:

	'''simple docstring'''





	__snake_case      :							Optional[int]						=			iter(UpperCAmelCase_  )
	while True:
		__snake_case      :							Optional[int]						=			tuple(itertools.islice(UpperCAmelCase_      ,							UpperCAmelCase_  )  )
		if not chunk:
			return
		yield chunk
def   __UpperCAmelCase    (   UpperCAmelCase_   :    str  )							->      str:

	'''simple docstring'''





	__snake_case      :							Any						=			''.join([c.upper() for c in dirty if c in string.ascii_letters]  )
	__snake_case      :							Union[str, Any]						=			''

	if len(UpperCAmelCase_  ) < 2:
		return dirty

	for i in range(len(UpperCAmelCase_  ) - 1  ):
		clean += dirty[i]

		if dirty[i] == dirty[i + 1]:
			clean += "X"

	clean += dirty[-1]

	if len(UpperCAmelCase_  ) & 1:
		clean += "X"

	return clean
def   __UpperCAmelCase    (   UpperCAmelCase_   :    str  )							->      list[str]:

	'''simple docstring'''





	__snake_case      :							List[str]						=			'ABCDEFGHIKLMNOPQRSTUVWXYZ'
	# we're using a list instead of a '2d' array because it makes the math
	# for setting up the table and doing the actual encoding/decoding simpler
	__snake_case      :							Optional[int]						=			[]

	# copy key chars into the table if they are in `alphabet` ignoring duplicates
	for char in key.upper():
		if char not in table and char in alphabet:
			table.append(UpperCAmelCase_  )

    # fill the rest of the table in with the remaining alphabet chars
	for char in alphabet:
		if char not in table:
			table.append(UpperCAmelCase_  )

	return table
def   __UpperCAmelCase    (   UpperCAmelCase_   :    str      ,							UpperCAmelCase_   :    str  )							->      str:

	'''simple docstring'''





	__snake_case      :							str						=			generate_table(UpperCAmelCase_  )
	__snake_case      :							Union[str, Any]						=			prepare_input(UpperCAmelCase_  )
	__snake_case      :							Tuple						=			''

	# https://en.wikipedia.org/wiki/Playfair_cipher#Description
	for chara, chara in chunker(UpperCAmelCase_      ,							2  ):
		__snake_case		,    __snake_case      :							Any						=			divmod(table.index(UpperCAmelCase_  )      ,							5  )
		__snake_case		,    __snake_case      :							Tuple						=			divmod(table.index(UpperCAmelCase_  )      ,							5  )

		if rowa == rowa:
			ciphertext += table[rowa * 5 + (cola + 1) % 5]
			ciphertext += table[rowa * 5 + (cola + 1) % 5]
		elif cola == cola:
			ciphertext += table[((rowa + 1) % 5) * 5 + cola]
			ciphertext += table[((rowa + 1) % 5) * 5 + cola]
		else:  # rectangle
			ciphertext += table[rowa * 5 + cola]
			ciphertext += table[rowa * 5 + cola]

	return ciphertext

def   __UpperCAmelCase    (   UpperCAmelCase_   :    str      ,							UpperCAmelCase_   :    str  )							->      str:

	'''simple docstring'''





	__snake_case      :							Optional[int]						=			generate_table(UpperCAmelCase_  )
	__snake_case      :							Any						=			''

	# https://en.wikipedia.org/wiki/Playfair_cipher#Description
	for chara, chara in chunker(UpperCAmelCase_      ,							2  ):
		__snake_case		,    __snake_case      :							Union[str, Any]						=			divmod(table.index(UpperCAmelCase_  )      ,							5  )
		__snake_case		,    __snake_case      :							Tuple						=			divmod(table.index(UpperCAmelCase_  )      ,							5  )

		if rowa == rowa:
			plaintext += table[rowa * 5 + (cola - 1) % 5]
			plaintext += table[rowa * 5 + (cola - 1) % 5]
		elif cola == cola:
			plaintext += table[((rowa - 1) % 5) * 5 + cola]
			plaintext += table[((rowa - 1) % 5) * 5 + cola]
		else:  # rectangle
			plaintext += table[rowa * 5 + cola]
			plaintext += table[rowa * 5 + cola]

	return plaintext





