






import json
import os
import re
import unicodedata
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowercase  							= logging.get_logger(__name__)

lowercase  							= {
    "src_vocab_file": "vocab-src.json",
    "tgt_vocab_file": "vocab-tgt.json",
    "merges_file": "merges.txt",
}

lowercase  							= {
    "src_vocab_file": {
        "stas/tiny-wmt19-en-de": "https://huggingface.co/stas/tiny-wmt19-en-de/resolve/main/vocab-src.json"
    },
    "tgt_vocab_file": {
        "stas/tiny-wmt19-en-de": "https://huggingface.co/stas/tiny-wmt19-en-de/resolve/main/vocab-tgt.json"
    },
    "merges_file": {"stas/tiny-wmt19-en-de": "https://huggingface.co/stas/tiny-wmt19-en-de/resolve/main/merges.txt"},
}

lowercase  							= {"stas/tiny-wmt19-en-de": 1024}
lowercase  							= {
    "stas/tiny-wmt19-en-de": {
        "langs": ["en", "de"],
        "model_max_length": 1024,
        "special_tokens_map_file": None,
        "full_tokenizer_file": None,
    }
}





def 						__UpperCAmelCase      (					a_):
							snake_case_           =							set()
							snake_case_           =							word[0]
							for char in word[1:]:
														pairs.add((prev_char, char))
														snake_case_           =							char
							return pairs





def 						__UpperCAmelCase      (					a_):
							snake_case_           =							text.replace('，'							,					',')
							snake_case_           =							re.sub(R'。\s*'							,					'. '							,					_A)
							snake_case_           =							text.replace('、'							,					',')
							snake_case_           =							text.replace('”'							,					'"')
							snake_case_           =							text.replace('“'							,					'"')
							snake_case_           =							text.replace('∶'							,					':')
							snake_case_           =							text.replace('：'							,					':')
							snake_case_           =							text.replace('？'							,					'?')
							snake_case_           =							text.replace('《'							,					'"')
							snake_case_           =							text.replace('》'							,					'"')
							snake_case_           =							text.replace('）'							,					')')
							snake_case_           =							text.replace('！'							,					'!')
							snake_case_           =							text.replace('（'							,					'(')
							snake_case_           =							text.replace('；'							,					';')
							snake_case_           =							text.replace('１'							,					'1')
							snake_case_           =							text.replace('」'							,					'"')
							snake_case_           =							text.replace('「'							,					'"')
							snake_case_           =							text.replace('０'							,					'0')
							snake_case_           =							text.replace('３'							,					'3')
							snake_case_           =							text.replace('２'							,					'2')
							snake_case_           =							text.replace('５'							,					'5')
							snake_case_           =							text.replace('６'							,					'6')
							snake_case_           =							text.replace('９'							,					'9')
							snake_case_           =							text.replace('７'							,					'7')
							snake_case_           =							text.replace('８'							,					'8')
							snake_case_           =							text.replace('４'							,					'4')
							snake_case_           =							re.sub(R'．\s*'							,					'. '							,					_A)
							snake_case_           =							text.replace('～'							,					'~')
							snake_case_           =							text.replace('’'							,					'\'')
							snake_case_           =							text.replace('…'							,					'...')
							snake_case_           =							text.replace('━'							,					'-')
							snake_case_           =							text.replace('〈'							,					'<')
							snake_case_           =							text.replace('〉'							,					'>')
							snake_case_           =							text.replace('【'							,					'[')
							snake_case_           =							text.replace('】'							,					']')
							snake_case_           =							text.replace('％'							,					'%')
							return text





def 						__UpperCAmelCase      (					a_):
							snake_case_           =							[]
							for char in text:
														snake_case_           =							unicodedata.category(_A)
														if cat.startswith('C'):
																					continue
														output.append(_A)
							return "".join(_A)




class 			UpperCamelCase_				(      lowerCamelCase__    ):



	'''simple docstring'''




	lowerCAmelCase													=			VOCAB_FILES_NAMES
	lowerCAmelCase													=			PRETRAINED_VOCAB_FILES_MAP
	lowerCAmelCase													=			PRETRAINED_INIT_CONFIGURATION
	lowerCAmelCase													=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowerCAmelCase													=			['input_ids', 'attention_mask']




	def __init__(	self	,      a=None	,      a=None	,      a=None	,      a=None	,      a=False	,      a="<unk>"	,      a="<s>"	,      a="</s>"	,      a="<pad>"	,      **a	,      )	->   List[Any]:
								super().__init__(
								    langs=lowercase_	,      src_vocab_file=lowercase_	,      tgt_vocab_file=lowercase_	,      merges_file=lowercase_	,      do_lower_case=lowercase_	,      unk_token=lowercase_	,      bos_token=lowercase_	,      sep_token=lowercase_	,      pad_token=lowercase_	,      **lowercase_	,      )

								try:
															import sacremoses
								except ImportError:
															raise ImportError(
															    'You need to install sacremoses to use XLMTokenizer. '
															    'See https://pypi.org/project/sacremoses/ for installation.' )

								snake_case_           =							sacremoses

								snake_case_           =							src_vocab_file
								snake_case_           =							tgt_vocab_file
								snake_case_           =							merges_file
								snake_case_           =							do_lower_case

								# cache of sm.MosesPunctNormalizer instance
								snake_case_           =							{}
								# cache of sm.MosesTokenizer instance
								snake_case_           =							{}
								snake_case_           =							{}

								if langs and len(lowercase_ ) == 2:
															snake_case_      ,		snake_case_           =							langs
								else:
															raise ValueError(
															    F'''arg `langs` needs to be a list of 2 langs, e.g. [\'en\', \'ru\'], but got {langs}. '''
															    'Usually that means that tokenizer can\'t find a mapping for the given model path '
															    'in PRETRAINED_VOCAB_FILES_MAP, and other maps of this tokenizer.' )

								with open(lowercase_	,      encoding='utf-8' ) as src_vocab_handle:
															snake_case_           =							json.load(lowercase_ )
								with open(lowercase_	,      encoding='utf-8' ) as tgt_vocab_handle:
															snake_case_           =							json.load(lowercase_ )
															snake_case_           =							{v: k for k, v in tgt_vocab.items()}
								with open(lowercase_	,      encoding='utf-8' ) as merges_handle:
															snake_case_           =							merges_handle.read().split('\n' )[:-1]
								snake_case_           =							[tuple(merge.split()[:2] ) for merge in merges]
								snake_case_           =							dict(zip(lowercase_	,      range(len(lowercase_ ) ) ) )
								snake_case_           =							{}




	def 							_UpperCamelCase      (	self )	->   Dict[str, int]:
								return self.get_src_vocab()




	@property
	def 							_UpperCamelCase      (	self )	->   int:
								return self.src_vocab_size




	def 							_UpperCamelCase      (	self	,      a	,      a )	->   Optional[Any]:






								if lang not in self.cache_moses_punct_normalizer:
															snake_case_           =							self.sm.MosesPunctNormalizer(lang=lowercase_ )
															snake_case_           =							punct_normalizer
								return self.cache_moses_punct_normalizer[lang].normalize(lowercase_ )




	def 							_UpperCamelCase      (	self	,      a	,      a )	->   List[str]:






								if lang not in self.cache_moses_tokenizer:
															snake_case_           =							self.sm.MosesTokenizer(lang=lowercase_ )
															snake_case_           =							moses_tokenizer
								return self.cache_moses_tokenizer[lang].tokenize(
								    lowercase_	,      aggressive_dash_splits=lowercase_	,      return_str=lowercase_	,      escape=lowercase_ )




	def 							_UpperCamelCase      (	self	,      a	,      a )	->   Dict:






								if lang not in self.cache_moses_detokenizer:
															snake_case_           =							self.sm.MosesDetokenizer(lang=lowercase_ )
															snake_case_           =							moses_detokenizer
								return self.cache_moses_detokenizer[lang].detokenize(lowercase_ )




	def 							_UpperCamelCase      (	self	,      a	,      a )	->   Union[str, Any]:
								snake_case_           =							replace_unicode_punct(lowercase_ )
								snake_case_           =							self.moses_punct_norm(lowercase_	,      lowercase_ )
								snake_case_           =							remove_non_printing_char(lowercase_ )
								return text




	@property
	def 							_UpperCamelCase      (	self )	->   List[str]:
								return len(self.encoder )




	@property
	def 							_UpperCamelCase      (	self )	->   List[str]:
								return len(self.decoder )




	def 							_UpperCamelCase      (	self )	->   Any:
								return dict(self.encoder	,      **self.added_tokens_encoder )




	def 							_UpperCamelCase      (	self )	->   Optional[int]:
								return dict(self.decoder	,      **self.added_tokens_decoder )




	def 							_UpperCamelCase      (	self	,      a )	->   Optional[int]:
								snake_case_           =							tuple(token[:-1] ) + (token[-1] + '</w>',)
								if token in self.cache:
															return self.cache[token]
								snake_case_           =							get_pairs(lowercase_ )

								if not pairs:
															return token + "</w>"

								while True:
															snake_case_           =							min(lowercase_	,      key=lambda a : self.bpe_ranks.get(lowercase_	,      float('inf' ) ) )
															if bigram not in self.bpe_ranks:
																						break
															snake_case_      ,		snake_case_           =							bigram
															snake_case_           =							[]
															snake_case_           =							0
															while i < len(lowercase_ ):
																						try:
																													snake_case_           =							word.index(lowercase_	,      lowercase_ )
																						except ValueError:
																													new_word.extend(word[i:] )
																													break
																						else:
																													new_word.extend(word[i:j] )
																													snake_case_           =							j

																						if word[i] == first and i < len(lowercase_ ) - 1 and word[i + 1] == second:
																													new_word.append(first + second )
																													i += 2
																						else:
																													new_word.append(word[i] )
																													i += 1
															snake_case_           =							tuple(lowercase_ )
															snake_case_           =							new_word
															if len(lowercase_ ) == 1:
																						break
															else:
																						snake_case_           =							get_pairs(lowercase_ )
								snake_case_           =							' '.join(lowercase_ )
								if word == "\n  </w>":
															snake_case_           =							'\n</w>'
								snake_case_           =							word
								return word




	def 							_UpperCamelCase      (	self	,      a	,      a="en"	,      a=False )	->   Dict:
								snake_case_           =							self.src_lang

								if self.do_lower_case:
															snake_case_           =							text.lower()

								if bypass_tokenizer:
															snake_case_           =							text.split()
								else:
															snake_case_           =							self.moses_pipeline(lowercase_	,      lang=lowercase_ )
															snake_case_           =							self.moses_tokenize(lowercase_	,      lang=lowercase_ )

								snake_case_           =							[]
								for token in text:
															if token:
																						split_tokens.extend(list(self.bpe(lowercase_ ).split(' ' ) ) )

								return split_tokens




	def 							_UpperCamelCase      (	self	,      a )	->   int:
								return self.encoder.get(lowercase_	,      self.encoder.get(self.unk_token ) )




	def 							_UpperCamelCase      (	self	,      a )	->   List[str]:
								return self.decoder.get(lowercase_	,      self.unk_token )




	def 							_UpperCamelCase      (	self	,      a )	->   Union[str, Any]:
								snake_case_           =							[t.replace(' '	,      '' ).replace('</w>'	,      ' ' ) for t in tokens]
								snake_case_           =							''.join(lowercase_ ).split()
								# detokenize
								snake_case_           =							self.moses_detokenize(lowercase_	,      self.tgt_lang )
								return text




	def 							_UpperCamelCase      (	self	,      a	,      a = None )	->   List[int]:
								snake_case_           =							[self.sep_token_id]

								# no bos used in fairseq
								if token_ids_a is None:
															return token_ids_a + sep
								return token_ids_a + sep + token_ids_a + sep




	def 							_UpperCamelCase      (	self	,      a	,      a = None	,      a = False )	->   List[int]:






								if already_has_special_tokens:
															return super().get_special_tokens_mask(
															    token_ids_a=lowercase_	,      token_ids_a=lowercase_	,      already_has_special_tokens=lowercase_ )
								# no bos used in fairseq
								if token_ids_a is not None:
															return ([0] * len(lowercase_ )) + [1] + ([0] * len(lowercase_ )) + [1]
								return ([0] * len(lowercase_ )) + [1]




	def 							_UpperCamelCase      (	self	,      a	,      a = None )	->   List[int]:
								snake_case_           =							[self.sep_token_id]

								# no bos used in fairseq
								if token_ids_a is None:
															return len(token_ids_a + sep ) * [0]
								return len(token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1]




	def 							_UpperCamelCase      (	self	,      a	,      a = None )	->   Tuple[str]:






								if not os.path.isdir(lowercase_ ):
															logger.error(F'''Vocabulary path ({save_directory}) should be a directory''' )
															return

								snake_case_           =							os.path.join(
								    lowercase_	,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['src_vocab_file'] )
								snake_case_           =							os.path.join(
								    lowercase_	,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['tgt_vocab_file'] )
								snake_case_           =							os.path.join(
								    lowercase_	,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file'] )

								with open(lowercase_	,      'w'	,      encoding='utf-8' ) as f:
															f.write(json.dumps(self.encoder	,      indent=2	,      sort_keys=lowercase_	,      ensure_ascii=lowercase_ ) + '\n' )

								with open(lowercase_	,      'w'	,      encoding='utf-8' ) as f:
															snake_case_           =							{v: k for k, v in self.decoder.items()}
															f.write(json.dumps(lowercase_	,      indent=2	,      sort_keys=lowercase_	,      ensure_ascii=lowercase_ ) + '\n' )

								snake_case_           =							0
								with open(lowercase_	,      'w'	,      encoding='utf-8' ) as writer:
															for bpe_tokens, token_index in sorted(self.bpe_ranks.items()	,      key=lambda a : kv[1] ):
																						if index != token_index:
																													logger.warning(
																													    F'''Saving vocabulary to {merges_file}: BPE merge indices are not consecutive.'''
																													    ' Please check that the tokenizer is not corrupted!' )
																													snake_case_           =							token_index
																						writer.write(' '.join(lowercase_ ) + '\n' )
																						index += 1

								return src_vocab_file, tgt_vocab_file, merges_file




	def __getstate__(	self )	->   int:
								snake_case_           =							self.__dict__.copy()
								snake_case_           =							None
								return state






	def __setstate__(	self	,      a )	->   str:
								snake_case_           =							d

								try:
															import sacremoses
								except ImportError:
															raise ImportError(
															    'You need to install sacremoses to use XLMTokenizer. '
															    'See https://pypi.org/project/sacremoses/ for installation.' )

								snake_case_           =							sacremoses













from collections.abc import Callable
from math import log
from os import name, system
from random import gauss, seed
from typing import TypeVar





def 						__UpperCAmelCase      (					a_							,					a_							,					a_):
							seed(1)
							return [gauss(a_							,					a_) for _ in range(a_)]





def 						__UpperCAmelCase      (					a_							,					a_):
							return [k for k in range(a_) for _ in range(instance_count[k])]





def 						__UpperCAmelCase      (					a_							,					a_):
							return sum(a_) / instance_count





def 						__UpperCAmelCase      (					a_							,					a_):
							return instance_count / total_count





def 						__UpperCAmelCase      (					a_							,					a_							,					a_):
							snake_case_           =							[]  # An empty list to store all squared differences
							# iterate over number of elements in items
							for i in range(len(a_)):
														# for loop iterates over number of elements in inner layer of items
														for j in range(len(items[i])):
																					# appending squared differences to 'squared_diff' list
																					squared_diff.append((items[i][j] - means[i]) ** 2)

    # one divided by (the number of all instances - number of classes) multiplied by
    # sum of all squared differences
							snake_case_           =							len(a_)  # Number of classes in dataset
							return 1 / (total_count - n_classes) * sum(a_)





def 						__UpperCAmelCase      (					a_							,					a_							,					a_							,					a_):
							snake_case_           =							[]
							# for loop iterates over number of elements in list
							for i in range(len(a_)):
														# for loop iterates over number of inner items of each element
														for j in range(len(x_items[i])):
																					snake_case_           =							[]  # to store all discriminant values of each item as a list
																					# for loop iterates over number of classes we have in our dataset
																					for k in range(len(a_)):
																												# appending values of discriminants for each class to 'temp' list
																												temp.append(
																												    x_items[i][j] * (means[k] / variance)
																												    - (means[k] ** 2 / (2 * variance))
																												    + log(probabilities[k]))
																					# appending discriminant values of each item to 'results' list
																					results.append(a_)

							return [result.index(max(a_)) for result in results]





def 						__UpperCAmelCase      (					a_							,					a_):
							snake_case_           =							sum(1 for i, j in zip(a_							,					a_) if i == j)
							# percentage of accuracy equals to number of correct predictions divided by number
							# of all data and multiplied by 100
							return (correct / len(a_)) * 1_00


lowercase  							= TypeVar("num")





def 						__UpperCAmelCase      (					a_							,					a_							,					a_							,					a_ = lambda a_: True							,					a_ = None							,					):
							while True:
														try:
																					snake_case_           =							input_type(input(a_).strip() or default)
																					if condition(a_):
																												return user_input
																					else:
																												print(f'''{user_input}: {err_msg}''')
																												continue
														except ValueError:
																					print(
																					    f'''{user_input}: Incorrect input type, expected {input_type.__name__!r}''')





def 						__UpperCAmelCase      (					):
							while True:
														print(' Linear Discriminant Analysis '.center(50							,					'*'))
														print('*' * 50							,					'\n')
														print('First of all we should specify the number of classes that')
														print('we want to generate as training dataset')
														# Trying to get number of classes
														snake_case_           =							valid_input(
														    input_type=a_							,					condition=lambda a_: x > 0							,					input_msg='Enter the number of classes (Data Groupings): '							,					err_msg='Number of classes should be positive!'							,					)

														print('-' * 1_00)

														# Trying to get the value of standard deviation
														snake_case_           =							valid_input(
														    input_type=a_							,					condition=lambda a_: x >= 0							,					input_msg=(
														        'Enter the value of standard deviation'
														        '(Default value is 1.0 for all classes): '
														    )							,					err_msg='Standard deviation should not be negative!'							,					default='1.0'							,					)

														print('-' * 1_00)

														# Trying to get number of instances in classes and theirs means to generate
														# dataset
														snake_case_           =							[]  # An empty list to store instance counts of classes in dataset
														for i in range(a_):
																					snake_case_           =							valid_input(
																					    input_type=a_							,					condition=lambda a_: x > 0							,					input_msg=(f'''Enter The number of instances for class_{i+1}: ''')							,					err_msg='Number of instances should be positive!'							,					)
																					counts.append(a_)
														print('-' * 1_00)

														# An empty list to store values of user-entered means of classes
														snake_case_           =							[]
														for a in range(a_):
																					snake_case_           =							valid_input(
																					    input_type=a_							,					input_msg=(f'''Enter the value of mean for class_{a+1}: ''')							,					err_msg='This is an invalid value.'							,					)
																					user_means.append(a_)
														print('-' * 1_00)

														print('Standard deviation: '							,					a_)
														# print out the number of instances in classes in separated line
														for i, count in enumerate(a_							,					1):
																					print(f'''Number of instances in class_{i} is: {count}''')
														print('-' * 1_00)

														# print out mean values of classes separated line
														for i, user_mean in enumerate(a_							,					1):
																					print(f'''Mean of class_{i} is: {user_mean}''')
														print('-' * 1_00)

														# Generating training dataset drawn from gaussian distribution
														snake_case_           =							[
														    gaussian_distribution(user_means[j]							,					a_							,					counts[j])
														    for j in range(a_)
														]
														print('Generated Normal Distribution: \n'							,					a_)
														print('-' * 1_00)

														# Generating Ys to detecting corresponding classes
														snake_case_           =							y_generator(a_							,					a_)
														print('Generated Corresponding Ys: \n'							,					a_)
														print('-' * 1_00)

														# Calculating the value of actual mean for each class
														snake_case_           =							[calculate_mean(counts[k]							,					x[k]) for k in range(a_)]
														# for loop iterates over number of elements in 'actual_means' list and print
														# out them in separated line
														for i, actual_mean in enumerate(a_							,					1):
																					print(f'''Actual(Real) mean of class_{i} is: {actual_mean}''')
														print('-' * 1_00)

														# Calculating the value of probabilities for each class
														snake_case_           =							[
														    calculate_probabilities(counts[i]							,					sum(a_)) for i in range(a_)
														]

														# for loop iterates over number of elements in 'probabilities' list and print
														# out them in separated line
														for i, probability in enumerate(a_							,					1):
																					print(f'''Probability of class_{i} is: {probability}''')
														print('-' * 1_00)

														# Calculating the values of variance for each class
														snake_case_           =							calculate_variance(a_							,					a_							,					sum(a_))
														print('Variance: '							,					a_)
														print('-' * 1_00)

														# Predicting Y values
														# storing predicted Y values in 'pre_indexes' variable
														snake_case_           =							predict_y_values(a_							,					a_							,					a_							,					a_)
														print('-' * 1_00)

														# Calculating Accuracy of the model
														print(f'''Accuracy: {accuracy(a_							,					a_)}''')
														print('-' * 1_00)
														print(' DONE '.center(1_00							,					'+'))

														if input('Press any key to restart or \'q\' for quit: ').strip().lower() == "q":
																					print('\n' + 'GoodBye!'.center(1_00							,					'-') + '\n')
																					break
														system('cls' if name == 'nt' else 'clear')  # noqa: S605


if __name__ == "__main__":
	main()





