


import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class   A__ (   __A	, unittest.TestCase     ):







    """simple docstring"""

    __magic_name__        =		LongformerTokenizer
    __magic_name__        =		True
    __magic_name__        =		LongformerTokenizerFast
    __magic_name__        =		True
    def 		a_      (	self   ):
         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         snake_case					=    [
             '''l''',
             '''o''',
             '''w''',
             '''e''',
             '''r''',
             '''s''',
             '''t''',
             '''i''',
             '''d''',
             '''n''',
             '''\u0120''',
             '''\u0120l''',
             '''\u0120n''',
             '''\u0120lo''',
             '''\u0120low''',
             '''er''',
             '''\u0120lowest''',
             '''\u0120newer''',
             '''\u0120wider''',
             '''<unk>''',
         ]
         snake_case					=    dict(zip(__lowercase      , range(len(__lowercase   )   )   )   )
         snake_case					=    ['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
         snake_case					=    {'''unk_token''': '''<unk>'''}

         snake_case					=    os.path.join(self.tmpdirname      , VOCAB_FILES_NAMES['''vocab_file''']   )
         snake_case					=    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(__lowercase   ) + '''\n'''   )
         with open(self.merges_file      , '''w'''      , encoding='''utf-8'''   ) as fp:
              fp.write('''\n'''.join(__lowercase   )   )
    def 		a_      (	self      , **__snake_case   ):
         kwargs.update(self.special_tokens_map   )
         return self.tokenizer_class.from_pretrained(self.tmpdirname      , **__lowercase   )
    def 		a_      (	self      , **__snake_case   ):
         kwargs.update(self.special_tokens_map   )
         return self.rust_tokenizer_class.from_pretrained(self.tmpdirname      , **__lowercase   )
    def 		a_      (	self      , __snake_case   ):
         snake_case					=    '''lower newer'''
         snake_case					=    '''lower newer'''
         return input_text, output_text
    def 		a_      (	self   ):
         snake_case					=    self.tokenizer_class(self.vocab_file      , self.merges_file      , **self.special_tokens_map   )
         snake_case					=    '''lower newer'''
         snake_case					=    ['''l''', '''o''', '''w''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
         snake_case					=    tokenizer.tokenize(__lowercase   )  # , add_prefix_space=True)
         self.assertListEqual(__lowercase      , __lowercase   )

         snake_case					=    tokens + [tokenizer.unk_token]
         snake_case					=    [0, 1, 2, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowercase   )      , __lowercase   )
    def 		a_      (	self   ):
         snake_case					=    self.get_tokenizer()

         self.assertListEqual(tokenizer.encode('''Hello world!'''      , add_special_tokens=__lowercase   )      , [0, 3_1_4_1_4, 2_3_2, 3_2_8, 2]   )
         self.assertListEqual(
             tokenizer.encode('''Hello world! cécé herlolip 418'''      , add_special_tokens=__lowercase   )      , [0, 3_1_4_1_4, 2_3_2, 3_2_8, 7_4_0, 1_1_4_0, 1_2_6_9_5, 6_9, 4_6_0_7_8, 1_5_8_8, 2]      , )
    @slow
    def 		a_      (	self   ):
         snake_case					=    self.tokenizer_class.from_pretrained('''allenai/longformer-base-4096'''   )

         snake_case					=    tokenizer.encode('''sequence builders'''      , add_special_tokens=__lowercase   )
         snake_case					=    tokenizer.encode('''multi-sequence build'''      , add_special_tokens=__lowercase   )

         snake_case					=    tokenizer.encode(
             '''sequence builders'''      , add_special_tokens=__lowercase      , add_prefix_space=__lowercase   )
         snake_case					=    tokenizer.encode(
             '''sequence builders'''      , '''multi-sequence build'''      , add_special_tokens=__lowercase      , add_prefix_space=__lowercase   )

         snake_case					=    tokenizer.build_inputs_with_special_tokens(__lowercase   )
         snake_case					=    tokenizer.build_inputs_with_special_tokens(__lowercase      , __lowercase   )

         assert encoded_sentence == encoded_text_from_decode
         assert encoded_pair == encoded_pair_from_decode
    def 		a_      (	self   ):
         snake_case					=    self.get_tokenizer()

         snake_case					=    '''Encode this sequence.'''
         snake_case					=    tokenizer.byte_encoder[''' '''.encode('''utf-8'''   )[0]]

         # Testing encoder arguments
         snake_case					=    tokenizer.encode(__lowercase      , add_special_tokens=__lowercase      , add_prefix_space=__lowercase   )
         snake_case					=    tokenizer.convert_ids_to_tokens(encoded[0]   )[0]
         self.assertNotEqual(__lowercase      , __lowercase   )

         snake_case					=    tokenizer.encode(__lowercase      , add_special_tokens=__lowercase      , add_prefix_space=__lowercase   )
         snake_case					=    tokenizer.convert_ids_to_tokens(encoded[0]   )[0]
         self.assertEqual(__lowercase      , __lowercase   )

         tokenizer.add_special_tokens({'''bos_token''': '''<s>'''}   )
         snake_case					=    tokenizer.encode(__lowercase      , add_special_tokens=__lowercase   )
         snake_case					=    tokenizer.convert_ids_to_tokens(encoded[1]   )[0]
         self.assertNotEqual(__lowercase      , __lowercase   )

         # Testing spaces after special tokens
         snake_case					=    '''<mask>'''
         tokenizer.add_special_tokens(
             {'''mask_token''': AddedToken(__lowercase      , lstrip=__lowercase      , rstrip=__lowercase   )}   )  # mask token has a left space
         snake_case					=    tokenizer.convert_tokens_to_ids(__lowercase   )

         snake_case					=    '''Encode <mask> sequence'''
         snake_case					=    '''Encode <mask>sequence'''

         snake_case					=    tokenizer.encode(__lowercase   )
         snake_case					=    encoded.index(__lowercase   )
         snake_case					=    tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]   )[0]
         self.assertEqual(__lowercase      , __lowercase   )

         snake_case					=    tokenizer.encode(__lowercase   )
         snake_case					=    encoded.index(__lowercase   )
         snake_case					=    tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]   )[0]
         self.assertNotEqual(__lowercase      , __lowercase   )
    def 		a_      (	self   ):
         pass
    def 		a_      (	self   ):
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''   ):
                   snake_case					=    self.rust_tokenizer_class.from_pretrained(__lowercase      , **__lowercase   )
                   snake_case					=    self.tokenizer_class.from_pretrained(__lowercase      , **__lowercase   )
                   snake_case					=    '''A, <mask> AllenNLP sentence.'''
                   snake_case					=    tokenizer_r.encode_plus(__lowercase      , add_special_tokens=__lowercase      , return_token_type_ids=__lowercase   )
                   snake_case					=    tokenizer_p.encode_plus(__lowercase      , add_special_tokens=__lowercase      , return_token_type_ids=__lowercase   )

                   # token_type_ids should put 0 everywhere
                   self.assertEqual(sum(tokens_r['''token_type_ids''']   )      , sum(tokens_p['''token_type_ids''']   )   )

                   # attention_mask should put 1 everywhere, so sum over length should be 1
                   self.assertEqual(
                       sum(tokens_r['''attention_mask''']   ) / len(tokens_r['''attention_mask''']   )      , sum(tokens_p['''attention_mask''']   ) / len(tokens_p['''attention_mask''']   )      , )

                   snake_case					=    tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']   )
                   snake_case					=    tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids''']   )

                   # Rust correctly handles the space before the mask while python doesnt
                   self.assertSequenceEqual(tokens_p['''input_ids''']      , [0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]   )
                   self.assertSequenceEqual(tokens_r['''input_ids''']      , [0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]   )

                   self.assertSequenceEqual(
                       __lowercase      , ['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']   )
                   self.assertSequenceEqual(
                       __lowercase      , ['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']   )
    def 		a_      (	self   ):
         for trim_offsets, add_prefix_space in itertools.product([True, False]      , repeat=2   ):
              snake_case					=    self.rust_tokenizer_class.from_pretrained(
                  self.tmpdirname      , use_fast=__lowercase      , add_prefix_space=__lowercase      , trim_offsets=__lowercase   )

              snake_case					=    json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()   )
              snake_case					=    json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()   )

              self.assertEqual(pre_tokenizer_state['''add_prefix_space''']      , __lowercase   )

              self.assertEqual(post_processor_state['''add_prefix_space''']      , __lowercase   )
              self.assertEqual(post_processor_state['''trim_offsets''']      , __lowercase   )




    def 		a_      (	self   ):
         # Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
         # `trim_offsets`
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''   ):
                   snake_case					=    '''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
                   snake_case					=    F'''{text_of_1_token} {text_of_1_token}'''

                   snake_case					=    self.rust_tokenizer_class.from_pretrained(
                       __lowercase      , use_fast=__lowercase      , add_prefix_space=__lowercase      , trim_offsets=__lowercase   )
                   snake_case					=    tokenizer_r(__lowercase      , return_offsets_mapping=__lowercase      , add_special_tokens=__lowercase   )
                   self.assertEqual(encoding.offset_mapping[0]      , (0, len(__lowercase   ))   )
                   self.assertEqual(
                       encoding.offset_mapping[1]      , (len(__lowercase   ) + 1, len(__lowercase   ) + 1 + len(__lowercase   ))      , )

                   snake_case					=    self.rust_tokenizer_class.from_pretrained(
                       __lowercase      , use_fast=__lowercase      , add_prefix_space=__lowercase      , trim_offsets=__lowercase   )
                   snake_case					=    tokenizer_r(__lowercase      , return_offsets_mapping=__lowercase      , add_special_tokens=__lowercase   )
                   self.assertEqual(encoding.offset_mapping[0]      , (0, len(__lowercase   ))   )
                   self.assertEqual(
                       encoding.offset_mapping[1]      , (len(__lowercase   ) + 1, len(__lowercase   ) + 1 + len(__lowercase   ))      , )

                   snake_case					=    self.rust_tokenizer_class.from_pretrained(
                       __lowercase      , use_fast=__lowercase      , add_prefix_space=__lowercase      , trim_offsets=__lowercase   )
                   snake_case					=    tokenizer_r(__lowercase      , return_offsets_mapping=__lowercase      , add_special_tokens=__lowercase   )
                   self.assertEqual(encoding.offset_mapping[0]      , (0, len(__lowercase   ))   )
                   self.assertEqual(
                       encoding.offset_mapping[1]      , (len(__lowercase   ), len(__lowercase   ) + 1 + len(__lowercase   ))      , )

                   snake_case					=    self.rust_tokenizer_class.from_pretrained(
                       __lowercase      , use_fast=__lowercase      , add_prefix_space=__lowercase      , trim_offsets=__lowercase   )
                   snake_case					=    tokenizer_r(__lowercase      , return_offsets_mapping=__lowercase      , add_special_tokens=__lowercase   )
                   self.assertEqual(encoding.offset_mapping[0]      , (0, len(__lowercase   ))   )
                   self.assertEqual(
                       encoding.offset_mapping[1]      , (len(__lowercase   ), len(__lowercase   ) + 1 + len(__lowercase   ))      , )

                   snake_case					=    F''' {text}'''

                   # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
                   #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
                   # )
                   # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
                   # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
                   # self.assertEqual(
                   #     encoding.offset_mapping[1],
                   #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
                   # )

                   snake_case					=    self.rust_tokenizer_class.from_pretrained(
                       __lowercase      , use_fast=__lowercase      , add_prefix_space=__lowercase      , trim_offsets=__lowercase   )
                   snake_case					=    tokenizer_r(__lowercase      , return_offsets_mapping=__lowercase      , add_special_tokens=__lowercase   )
                   self.assertEqual(encoding.offset_mapping[0]      , (1, 1 + len(__lowercase   ))   )
                   self.assertEqual(
                       encoding.offset_mapping[1]      , (1 + len(__lowercase   ) + 1, 1 + len(__lowercase   ) + 1 + len(__lowercase   ))      , )

                   snake_case					=    self.rust_tokenizer_class.from_pretrained(
                       __lowercase      , use_fast=__lowercase      , add_prefix_space=__lowercase      , trim_offsets=__lowercase   )
                   snake_case					=    tokenizer_r(__lowercase      , return_offsets_mapping=__lowercase      , add_special_tokens=__lowercase   )
                   self.assertEqual(encoding.offset_mapping[0]      , (0, 1 + len(__lowercase   ))   )
                   self.assertEqual(
                       encoding.offset_mapping[1]      , (1 + len(__lowercase   ), 1 + len(__lowercase   ) + 1 + len(__lowercase   ))      , )

                   snake_case					=    self.rust_tokenizer_class.from_pretrained(
                       __lowercase      , use_fast=__lowercase      , add_prefix_space=__lowercase      , trim_offsets=__lowercase   )
                   snake_case					=    tokenizer_r(__lowercase      , return_offsets_mapping=__lowercase      , add_special_tokens=__lowercase   )
                   self.assertEqual(encoding.offset_mapping[0]      , (0, 1 + len(__lowercase   ))   )
                   self.assertEqual(
                       encoding.offset_mapping[1]      , (1 + len(__lowercase   ), 1 + len(__lowercase   ) + 1 + len(__lowercase   ))      , )








import math

class   A__ :







    """simple docstring"""

    def 		a_      (	self      , __snake_case      , __snake_case   ):
         snake_case					=    0.0
         snake_case					=    0.0
         for i in range(len(__snake_case   )   ):
              da += math.pow((sample[i] - weights[0][i])      , 2   )
              da += math.pow((sample[i] - weights[1][i])      , 2   )
              return 0 if da > da else 1
         return 0




    def 		a_      (	self      , __snake_case      , __snake_case      , __snake_case      , __snake_case   ):
         for i in range(len(__snake_case   )   ):
              weights[j][i] += alpha * (sample[i] - weights[j][i])
         return weights






def       UpperCAmelCase__						():



     """simple docstring"""






     snake_case					=    [[1, 1, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0], [0, 0, 1, 1]]

     # weight initialization ( n, C )
     snake_case					=    [[0.2, 0.6, 0.5, 0.9], [0.8, 0.4, 0.7, 0.3]]

     # training
     snake_case					=    SelfOrganizingMap()
     snake_case					=    3
     snake_case					=    0.5

     for _ in range(UpperCamelCase_    ):
          for j in range(len(UpperCamelCase_    )    ):
               # training sample
               snake_case					=    training_samples[j]

               # Compute the winning vector
               snake_case					=    self_organizing_map.get_winner(UpperCamelCase_							,UpperCamelCase_    )

               # Update the winning vector
               snake_case					=    self_organizing_map.update(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_    )

    # classify test sample
     snake_case					=    [0, 0, 0, 1]
     snake_case					=    self_organizing_map.get_winner(UpperCamelCase_							,UpperCamelCase_    )

     # results
     print(F'''Clusters that the test sample belongs to : {winner}'''    )
     print(F'''Weights that have been trained : {weights}'''    )


# running the main() function
if __name__ == "__main__":
 main()




