
"""simple docstring"""



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			(					SCREAMING_SNAKE_CASE__						,		unittest.TestCase      ):
      UpperCamelCase							:   str           =     LongformerTokenizer
      UpperCamelCase							:   Any           =     True
      UpperCamelCase							:   int           =     LongformerTokenizerFast
      UpperCamelCase							:   int           =     True



      def  __snake_case							(   self      ):
          super().setUp()

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

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



      def  __snake_case							(   self     ,	**UpperCamelCase_      ):
          kwargs.update(self.special_tokens_map      )
          return self.tokenizer_class.from_pretrained(self.tmpdirname     ,	**A_      )



      def  __snake_case							(   self     ,	**UpperCamelCase_      ):
          kwargs.update(self.special_tokens_map      )
          return self.rust_tokenizer_class.from_pretrained(self.tmpdirname     ,	**A_      )



      def  __snake_case							(   self     ,	UpperCamelCase_      ):
          UpperCAmelCase__	:      Union[str, Any]     							=					'''lower newer'''
          UpperCAmelCase__	:      Union[str, Any]     							=					'''lower newer'''
          return input_text, output_text



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Tuple     							=					self.tokenizer_class(self.vocab_file     ,	self.merges_file     ,	**self.special_tokens_map      )
          UpperCAmelCase__	:      List[Any]     							=					'''lower newer'''
          UpperCAmelCase__	:      Tuple     							=					['''l''', '''o''', '''w''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
          UpperCAmelCase__	:      Union[str, Any]     							=					tokenizer.tokenize(A_      )  # , add_prefix_space=True)
          self.assertListEqual(A_     ,	A_      )

          UpperCAmelCase__	:      int     							=					tokens + [tokenizer.unk_token]
          UpperCAmelCase__	:      str     							=					[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(A_      )     ,	A_      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Optional[int]     							=					self.get_tokenizer()

          self.assertListEqual(tokenizer.encode('Hello world!'     ,	add_special_tokens=A_      )     ,	[0, 31_414, 232, 328, 2]      )
          self.assertListEqual(
              tokenizer.encode('Hello world! cécé herlolip 418'     ,	add_special_tokens=A_      )     ,	[0, 31_414, 232, 328, 740, 1_140, 12_695, 69, 46_078, 1_588, 2]     ,	)



      @slow
      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Dict     							=					self.tokenizer_class.from_pretrained('allenai/longformer-base-4096'      )

          UpperCAmelCase__	:      List[Any]     							=					tokenizer.encode('sequence builders'     ,	add_special_tokens=A_      )
          UpperCAmelCase__	:      Optional[Any]     							=					tokenizer.encode('multi-sequence build'     ,	add_special_tokens=A_      )

          UpperCAmelCase__	:      Any     							=					tokenizer.encode(
              'sequence builders'     ,	add_special_tokens=A_     ,	add_prefix_space=A_      )
          UpperCAmelCase__	:      List[Any]     							=					tokenizer.encode(
              'sequence builders'     ,	'multi-sequence build'     ,	add_special_tokens=A_     ,	add_prefix_space=A_      )

          UpperCAmelCase__	:      Optional[int]     							=					tokenizer.build_inputs_with_special_tokens(A_      )
          UpperCAmelCase__	:      str     							=					tokenizer.build_inputs_with_special_tokens(A_     ,	A_      )

          assert encoded_sentence == encoded_text_from_decode
          assert encoded_pair == encoded_pair_from_decode



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Tuple     							=					self.get_tokenizer()

          UpperCAmelCase__	:      str     							=					'''Encode this sequence.'''
          UpperCAmelCase__	:      List[str]     							=					tokenizer.byte_encoder[''' '''.encode('utf-8'      )[0]]

          # Testing encoder arguments
          UpperCAmelCase__	:      Tuple     							=					tokenizer.encode(A_     ,	add_special_tokens=A_     ,	add_prefix_space=A_      )
          UpperCAmelCase__	:      Any     							=					tokenizer.convert_ids_to_tokens(encoded[0]      )[0]
          self.assertNotEqual(A_     ,	A_      )

          UpperCAmelCase__	:      Dict     							=					tokenizer.encode(A_     ,	add_special_tokens=A_     ,	add_prefix_space=A_      )
          UpperCAmelCase__	:      List[str]     							=					tokenizer.convert_ids_to_tokens(encoded[0]      )[0]
          self.assertEqual(A_     ,	A_      )

          tokenizer.add_special_tokens({'bos_token': '<s>'}      )
          UpperCAmelCase__	:      Optional[Any]     							=					tokenizer.encode(A_     ,	add_special_tokens=A_      )
          UpperCAmelCase__	:      Union[str, Any]     							=					tokenizer.convert_ids_to_tokens(encoded[1]      )[0]
          self.assertNotEqual(A_     ,	A_      )

          # Testing spaces after special tokens
          UpperCAmelCase__	:      Optional[Any]     							=					'''<mask>'''
          tokenizer.add_special_tokens(
              {'mask_token': AddedToken(A_     ,	lstrip=A_     ,	rstrip=A_      )}      )  # mask token has a left space
          UpperCAmelCase__	:      Union[str, Any]     							=					tokenizer.convert_tokens_to_ids(A_      )

          UpperCAmelCase__	:      str     							=					'''Encode <mask> sequence'''
          UpperCAmelCase__	:      Any     							=					'''Encode <mask>sequence'''

          UpperCAmelCase__	:      Optional[Any]     							=					tokenizer.encode(A_      )
          UpperCAmelCase__	:      List[str]     							=					encoded.index(A_      )
          UpperCAmelCase__	:      str     							=					tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]      )[0]
          self.assertEqual(A_     ,	A_      )

          UpperCAmelCase__	:      Tuple     							=					tokenizer.encode(A_      )
          UpperCAmelCase__	:      str     							=					encoded.index(A_      )
          UpperCAmelCase__	:      int     							=					tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]      )[0]
          self.assertNotEqual(A_     ,	A_      )



      def  __snake_case							(   self      ):
          pass



      def  __snake_case							(   self      ):




          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
                  UpperCAmelCase__	:      str     							=					self.rust_tokenizer_class.from_pretrained(A_     ,	**A_      )
                  UpperCAmelCase__	:      List[str]     							=					self.tokenizer_class.from_pretrained(A_     ,	**A_      )
                  UpperCAmelCase__	:      Dict     							=					'''A, <mask> AllenNLP sentence.'''
                  UpperCAmelCase__	:      Union[str, Any]     							=					tokenizer_r.encode_plus(A_     ,	add_special_tokens=A_     ,	return_token_type_ids=A_      )
                  UpperCAmelCase__	:      Optional[Any]     							=					tokenizer_p.encode_plus(A_     ,	add_special_tokens=A_     ,	return_token_type_ids=A_      )

                  # 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']      )     ,	)

                  UpperCAmelCase__	:      Optional[int]     							=					tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']      )
                  UpperCAmelCase__	:      Optional[int]     							=					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, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]      )
                  self.assertSequenceEqual(tokens_r['input_ids']     ,	[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]      )

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



      def  __snake_case							(   self      ):




          for trim_offsets, add_prefix_space in itertools.product([True, False]     ,	repeat=2      ):
              UpperCAmelCase__	:      Dict     							=					self.rust_tokenizer_class.from_pretrained(
                  self.tmpdirname     ,	use_fast=A_     ,	add_prefix_space=A_     ,	trim_offsets=A_      )

              UpperCAmelCase__	:      str     							=					json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()      )
              UpperCAmelCase__	:      List[Any]     							=					json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()      )

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

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



      def  __snake_case							(   self      ):




          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
                  UpperCAmelCase__	:      Tuple     							=					'''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
                  UpperCAmelCase__	:      Dict     							=					F'''{text_of_1_token} {text_of_1_token}'''

                  UpperCAmelCase__	:      Optional[int]     							=					self.rust_tokenizer_class.from_pretrained(
                      A_     ,	use_fast=A_     ,	add_prefix_space=A_     ,	trim_offsets=A_      )
                  UpperCAmelCase__	:      Union[str, Any]     							=					tokenizer_r(A_     ,	return_offsets_mapping=A_     ,	add_special_tokens=A_      )
                  self.assertEqual(encoding.offset_mapping[0]     ,	(0, len(A_      ))      )
                  self.assertEqual(
                      encoding.offset_mapping[1]     ,	(len(A_      ) + 1, len(A_      ) + 1 + len(A_      ))     ,	)

                  UpperCAmelCase__	:      Dict     							=					self.rust_tokenizer_class.from_pretrained(
                      A_     ,	use_fast=A_     ,	add_prefix_space=A_     ,	trim_offsets=A_      )
                  UpperCAmelCase__	:      str     							=					tokenizer_r(A_     ,	return_offsets_mapping=A_     ,	add_special_tokens=A_      )
                  self.assertEqual(encoding.offset_mapping[0]     ,	(0, len(A_      ))      )
                  self.assertEqual(
                      encoding.offset_mapping[1]     ,	(len(A_      ) + 1, len(A_      ) + 1 + len(A_      ))     ,	)

                  UpperCAmelCase__	:      Tuple     							=					self.rust_tokenizer_class.from_pretrained(
                      A_     ,	use_fast=A_     ,	add_prefix_space=A_     ,	trim_offsets=A_      )
                  UpperCAmelCase__	:      Optional[Any]     							=					tokenizer_r(A_     ,	return_offsets_mapping=A_     ,	add_special_tokens=A_      )
                  self.assertEqual(encoding.offset_mapping[0]     ,	(0, len(A_      ))      )
                  self.assertEqual(
                      encoding.offset_mapping[1]     ,	(len(A_      ), len(A_      ) + 1 + len(A_      ))     ,	)

                  UpperCAmelCase__	:      Tuple     							=					self.rust_tokenizer_class.from_pretrained(
                      A_     ,	use_fast=A_     ,	add_prefix_space=A_     ,	trim_offsets=A_      )
                  UpperCAmelCase__	:      Optional[int]     							=					tokenizer_r(A_     ,	return_offsets_mapping=A_     ,	add_special_tokens=A_      )
                  self.assertEqual(encoding.offset_mapping[0]     ,	(0, len(A_      ))      )
                  self.assertEqual(
                      encoding.offset_mapping[1]     ,	(len(A_      ), len(A_      ) + 1 + len(A_      ))     ,	)

                  UpperCAmelCase__	:      str     							=					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)),
                  # )

                  UpperCAmelCase__	:      Optional[int]     							=					self.rust_tokenizer_class.from_pretrained(
                      A_     ,	use_fast=A_     ,	add_prefix_space=A_     ,	trim_offsets=A_      )
                  UpperCAmelCase__	:      Optional[Any]     							=					tokenizer_r(A_     ,	return_offsets_mapping=A_     ,	add_special_tokens=A_      )
                  self.assertEqual(encoding.offset_mapping[0]     ,	(1, 1 + len(A_      ))      )
                  self.assertEqual(
                      encoding.offset_mapping[1]     ,	(1 + len(A_      ) + 1, 1 + len(A_      ) + 1 + len(A_      ))     ,	)

                  UpperCAmelCase__	:      str     							=					self.rust_tokenizer_class.from_pretrained(
                      A_     ,	use_fast=A_     ,	add_prefix_space=A_     ,	trim_offsets=A_      )
                  UpperCAmelCase__	:      Any     							=					tokenizer_r(A_     ,	return_offsets_mapping=A_     ,	add_special_tokens=A_      )
                  self.assertEqual(encoding.offset_mapping[0]     ,	(0, 1 + len(A_      ))      )
                  self.assertEqual(
                      encoding.offset_mapping[1]     ,	(1 + len(A_      ), 1 + len(A_      ) + 1 + len(A_      ))     ,	)

                  UpperCAmelCase__	:      Optional[Any]     							=					self.rust_tokenizer_class.from_pretrained(
                      A_     ,	use_fast=A_     ,	add_prefix_space=A_     ,	trim_offsets=A_      )
                  UpperCAmelCase__	:      Union[str, Any]     							=					tokenizer_r(A_     ,	return_offsets_mapping=A_     ,	add_special_tokens=A_      )
                  self.assertEqual(encoding.offset_mapping[0]     ,	(0, 1 + len(A_      ))      )
                  self.assertEqual(
                      encoding.offset_mapping[1]     ,	(1 + len(A_      ), 1 + len(A_      ) + 1 + len(A_      ))     ,	)



"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


A__ :       List[str]				= {
    'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
    'tokenization_biogpt': ['BioGptTokenizer'],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  A__ :       Dict				= [
      'BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'BioGptForCausalLM',
      'BioGptForTokenClassification',
      'BioGptForSequenceClassification',
      'BioGptModel',
      'BioGptPreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
  from .tokenization_biogpt import BioGptTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_biogpt import (
        BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        BioGptForCausalLM,
        BioGptForSequenceClassification,
        BioGptForTokenClassification,
        BioGptModel,
        BioGptPreTrainedModel,
    )


else:
  import sys

  A__ :       int				= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
