




"""simple docstring"""
import os
from shutil import copyfile
from typing import Optional, Tuple

from ...file_utils import is_sentencepiece_available
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if is_sentencepiece_available():
    from .tokenization_deberta_va import DebertaVaTokenizer
else:
    _SCREAMING_SNAKE_CASE						 =     None

_SCREAMING_SNAKE_CASE						 =     logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE						 =     {'vocab_file': 'spm.model', 'tokenizer_file': 'tokenizer.json'}

_SCREAMING_SNAKE_CASE						 =     {
    'vocab_file': {
        'microsoft/deberta-v2-xlarge': 'https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model',
        'microsoft/deberta-v2-xxlarge': 'https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model',
        'microsoft/deberta-v2-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model'
        ),
        'microsoft/deberta-v2-xxlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model'
        ),
    }
}

_SCREAMING_SNAKE_CASE						 =     {
    'microsoft/deberta-v2-xlarge': 5_1_2,
    'microsoft/deberta-v2-xxlarge': 5_1_2,
    'microsoft/deberta-v2-xlarge-mnli': 5_1_2,
    'microsoft/deberta-v2-xxlarge-mnli': 5_1_2,
}

_SCREAMING_SNAKE_CASE						 =     {
    'microsoft/deberta-v2-xlarge': {'do_lower_case': False},
    'microsoft/deberta-v2-xxlarge': {'do_lower_case': False},
    'microsoft/deberta-v2-xlarge-mnli': {'do_lower_case': False},
    'microsoft/deberta-v2-xxlarge-mnli': {'do_lower_case': False},
}







class  _SCREAMING_SNAKE_CASE       (     SCREAMING_SNAKE_CASE__				):



 '''simple docstring'''





 __UpperCAmelCase		   =							VOCAB_FILES_NAMES
 __UpperCAmelCase		   =							PRETRAINED_VOCAB_FILES_MAP
 __UpperCAmelCase		   =							PRETRAINED_INIT_CONFIGURATION
 __UpperCAmelCase		   =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __UpperCAmelCase		   =							DebertaVaTokenizer






 def __init__(self					,     lowerCAmelCase__=None					,     lowerCAmelCase__=None					,     lowerCAmelCase__=False					,     lowerCAmelCase__=False					,     lowerCAmelCase__="[CLS]"					,     lowerCAmelCase__="[SEP]"					,     lowerCAmelCase__="[UNK]"					,     lowerCAmelCase__="[SEP]"					,     lowerCAmelCase__="[PAD]"					,     lowerCAmelCase__="[CLS]"					,     lowerCAmelCase__="[MASK]"					,     **lowerCAmelCase__					,     ):

  '''simple docstring'''







  super().__init__(
      snake_case__					,     tokenizer_file=snake_case__					,     do_lower_case=snake_case__					,     bos_token=snake_case__					,     eos_token=snake_case__					,     unk_token=snake_case__					,     sep_token=snake_case__					,     pad_token=snake_case__					,     cls_token=snake_case__					,     mask_token=snake_case__					,     split_by_punct=snake_case__					,     **snake_case__					,     )

  _UpperCamelCase      :	Any					      =  do_lower_case
  _UpperCamelCase      :	str					      =  split_by_punct
  _UpperCamelCase      :	Dict					      =  vocab_file
  _UpperCamelCase      :	List[Any]					      =  False if not self.vocab_file else True






 def lowercase_      (self					,     lowerCAmelCase__					,     lowerCAmelCase__=None   ):

  '''simple docstring'''







  if token_ids_a is None:
   return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
  _UpperCamelCase      :	Tuple					      =  [self.cls_token_id]
  _UpperCamelCase      :	Optional[int]					      =  [self.sep_token_id]
  return cls + token_ids_a + sep + token_ids_a + sep






 def lowercase_      (self					,     lowerCAmelCase__					,     lowerCAmelCase__=None					,     lowerCAmelCase__=False   ):

  '''simple docstring'''







  if already_has_special_tokens:
   return super().get_special_tokens_mask(
       token_ids_a=snake_case__					,     token_ids_a=snake_case__					,     already_has_special_tokens=snake_case__   )

  if token_ids_a is not None:
   return [1] + ([0] * len(snake_case__   )) + [1] + ([0] * len(snake_case__   )) + [1]
  return [1] + ([0] * len(snake_case__   )) + [1]






 def lowercase_      (self					,     lowerCAmelCase__					,     lowerCAmelCase__=None   ):

  '''simple docstring'''







  _UpperCamelCase      :	Optional[int]					      =  [self.sep_token_id]
  _UpperCamelCase      :	int					      =  [self.cls_token_id]
  if token_ids_a is None:
   return len(cls + token_ids_a + sep   ) * [0]
  return len(cls + token_ids_a + sep   ) * [0] + len(token_ids_a + sep   ) * [1]






 def lowercase_      (self					,     lowerCAmelCase__					,     lowerCAmelCase__ = None   ):

  '''simple docstring'''







  if not self.can_save_slow_tokenizer:
   raise ValueError(
       "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
       "tokenizer."   )

  if not os.path.isdir(snake_case__   ):
   logger.error(F"Vocabulary path ({save_directory}) should be a directory"   )
   return
  _UpperCamelCase      :	Optional[Any]					      =  os.path.join(
      snake_case__					,     (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]   )

  if os.path.abspath(self.vocab_file   ) != os.path.abspath(snake_case__   ):
   copyfile(self.vocab_file					,     snake_case__   )

  return (out_vocab_file,)







'''simple docstring'''




import importlib.metadata
import sys

from transformers.testing_utils import TestCasePlus
from transformers.utils.versions import require_version, require_version_core


_lowerCAmelCase	:		Optional[int]		  =						importlib.metadata.version('numpy')
_lowerCAmelCase	:		List[Any]		  =						'.'.join([str(x) for x in sys.version_info[:3]])



class 			lowerCAmelCase					(					a				):



	def 					lowercase  (       self     ):
		# lt + different version strings
		require_version_core('numpy<1000.4.5'     )
		require_version_core('numpy<1000.4'     )
		require_version_core('numpy<1000'     )

		# le
		require_version_core('numpy<=1000.4.5'     )
		require_version_core(f"numpy<={numpy_ver}"     )

		# eq
		require_version_core(f"numpy=={numpy_ver}"     )

		# ne
		require_version_core('numpy!=1000.4.5'     )

		# ge
		require_version_core('numpy>=1.0'     )
		require_version_core('numpy>=1.0.0'     )
		require_version_core(f"numpy>={numpy_ver}"     )

		# gt
		require_version_core('numpy>1.0.0'     )

		# mix
		require_version_core('numpy>1.0.0,<1000'     )

		# requirement w/o version
		require_version_core('numpy'     )

		# unmet requirements due to version conflict
		for req in ["numpy==1.0.0", "numpy>=1000.0.0", f"numpy<{numpy_ver}"]:
			try:
				require_version_core(snake_case__     )
			except ImportError as e:
				self.assertIn(f"{req} is required"			,       str(snake_case__     )     )
				self.assertIn('but found'			,       str(snake_case__     )     )

        # unmet requirements due to missing module
		for req in ["numpipypie>1", "numpipypie2"]:
			try:
				require_version_core(snake_case__     )
			except importlib.metadata.PackageNotFoundError as e:
				self.assertIn(f"The '{req}' distribution was not found and is required by this application"			,       str(snake_case__     )     )
				self.assertIn('Try: pip install transformers -U'			,       str(snake_case__     )     )

        # bogus requirements formats:
        # 1. whole thing
		for req in ["numpy??1.0.0", "numpy1.0.0"]:
			try:
				require_version_core(snake_case__     )
			except ValueError as e:
				self.assertIn('requirement needs to be in the pip package format'			,       str(snake_case__     )     )
        # 2. only operators
		for req in ["numpy=1.0.0", "numpy == 1.00", "numpy<>1.0.0", "numpy><1.00", "numpy>>1.0.0"]:
			try:
				require_version_core(snake_case__     )
			except ValueError as e:
				self.assertIn('need one of '			,       str(snake_case__     )     )



	def 					lowercase  (       self     ):
		# matching requirement
		require_version('python>=3.6.0'     )

		# not matching requirements
		for req in ["python>9.9.9", "python<3.0.0"]:
			try:
				require_version_core(snake_case__     )
			except ImportError as e:
				self.assertIn(f"{req} is required"			,       str(snake_case__     )     )
				self.assertIn(f"but found python=={python_ver}"			,       str(snake_case__     )     )
