




'''simple docstring'''



import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 		lowercase_   (			A					,  unittest.TestCase       ):


   """simple docstring"""

   lowerCamelCase_      =						None
   lowerCamelCase_      =						BloomTokenizerFast
   lowerCamelCase_      =						BloomTokenizerFast
   lowerCamelCase_      =						True
   lowerCamelCase_      =						False
   lowerCamelCase_      =						'''tokenizer_file'''
   lowerCamelCase_      =						{'''bos_token''': '''<s>''', '''eos_token''': '''</s>''', '''unk_token''': '''<unk>''', '''pad_token''': '''<pad>'''}



   def 							lowerCAmelCase_      (   self :     Union[str, Any]   ):

      """simple docstring"""
      super().setUp()
      _SCREAMING_SNAKE_CASE	=				BloomTokenizerFast.from_pretrained("bigscience/tokenizer"   )
      tokenizer.save_pretrained(self.tmpdirname   )



   def 							lowerCAmelCase_      (   self :     str  ,				**__lowerCamelCase :     Tuple   ):

      """simple docstring"""
      kwargs.update(self.special_tokens_map   )
      return BloomTokenizerFast.from_pretrained(self.tmpdirname  ,				**__lowerCamelCase   )



   def 							lowerCAmelCase_      (   self :     Optional[Any]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				self.get_rust_tokenizer()

      _SCREAMING_SNAKE_CASE	=				["The quick brown fox</s>", "jumps over the lazy dog</s>"]
      _SCREAMING_SNAKE_CASE	=				[[2_1_7_5, 2_3_7_1_4, 7_3_1_7_3, 1_4_4_2_5_2, 2], [7_7, 1_3_2_6_1_9, 3_4_7_8, 3_6_8, 1_0_9_5_8_6, 3_5_4_3_3, 2]]

      _SCREAMING_SNAKE_CASE	=				tokenizer.batch_encode_plus(__lowerCamelCase   )["input_ids"]
      self.assertListEqual(__lowerCamelCase  ,				__lowerCamelCase   )

      _SCREAMING_SNAKE_CASE	=				tokenizer.batch_decode(__lowerCamelCase   )
      self.assertListEqual(__lowerCamelCase  ,				__lowerCamelCase   )



   def 							lowerCAmelCase_      (   self :     Optional[Any]  ,				__lowerCamelCase :     int=6   ):

      """simple docstring"""
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""   ):
            _SCREAMING_SNAKE_CASE	=				self.rust_tokenizer_class.from_pretrained(__lowerCamelCase  ,				**__lowerCamelCase   )
            # tokenizer_r.pad_token = None # Hotfixing padding = None
            # Simple input
            _SCREAMING_SNAKE_CASE	=				"This is a simple input"
            _SCREAMING_SNAKE_CASE	=				["This is a simple input 1", "This is a simple input 2"]
            _SCREAMING_SNAKE_CASE	=				("This is a simple input", "This is a pair")
            _SCREAMING_SNAKE_CASE	=				[
                ("This is a simple input 1", "This is a simple input 2"),
                ("This is a simple pair 1", "This is a simple pair 2"),
            ]

            # Simple input tests
            try:
               tokenizer_r.encode(__lowerCamelCase  ,				max_length=__lowerCamelCase   )
               tokenizer_r.encode_plus(__lowerCamelCase  ,				max_length=__lowerCamelCase   )

               tokenizer_r.batch_encode_plus(__lowerCamelCase  ,				max_length=__lowerCamelCase   )
               tokenizer_r.encode(__lowerCamelCase  ,				max_length=__lowerCamelCase   )
               tokenizer_r.batch_encode_plus(__lowerCamelCase  ,				max_length=__lowerCamelCase   )
            except ValueError:
               self.fail("Bloom Tokenizer should be able to deal with padding"   )

            _SCREAMING_SNAKE_CASE	=				None  # Hotfixing padding = None
            self.assertRaises(__lowerCamelCase  ,				tokenizer_r.encode  ,				__lowerCamelCase  ,				max_length=__lowerCamelCase  ,				padding="max_length"   )

            # Simple input
            self.assertRaises(__lowerCamelCase  ,				tokenizer_r.encode_plus  ,				__lowerCamelCase  ,				max_length=__lowerCamelCase  ,				padding="max_length"   )

            # Simple input
            self.assertRaises(
                __lowerCamelCase  ,				tokenizer_r.batch_encode_plus  ,				__lowerCamelCase  ,				max_length=__lowerCamelCase  ,				padding="max_length"  ,				)

            # Pair input
            self.assertRaises(__lowerCamelCase  ,				tokenizer_r.encode  ,				__lowerCamelCase  ,				max_length=__lowerCamelCase  ,				padding="max_length"   )

            # Pair input
            self.assertRaises(__lowerCamelCase  ,				tokenizer_r.encode_plus  ,				__lowerCamelCase  ,				max_length=__lowerCamelCase  ,				padding="max_length"   )

            # Pair input
            self.assertRaises(
                __lowerCamelCase  ,				tokenizer_r.batch_encode_plus  ,				__lowerCamelCase  ,				max_length=__lowerCamelCase  ,				padding="max_length"  ,				)



   def 							lowerCAmelCase_      (   self :     List[Any]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				self.get_rust_tokenizer()
      _SCREAMING_SNAKE_CASE	=				load_dataset("xnli"  ,				"all_languages"  ,				split="test"  ,				streaming=__lowerCamelCase   )

      _SCREAMING_SNAKE_CASE	=				next(iter(__lowerCamelCase   )   )["premise"]  # pick up one data
      _SCREAMING_SNAKE_CASE	=				list(sample_data.values()   )

      _SCREAMING_SNAKE_CASE	=				list(map(tokenizer.encode  ,				__lowerCamelCase   )   )
      _SCREAMING_SNAKE_CASE	=				[tokenizer.decode(__lowerCamelCase  ,				clean_up_tokenization_spaces=__lowerCamelCase   ) for x in output_tokens]
      self.assertListEqual(__lowerCamelCase  ,				__lowerCamelCase   )



   def 							lowerCAmelCase_      (   self :     str   ):

      """simple docstring"""
      self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map   )  ,				1   )
      self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()   )[0]   )  ,				1   )







'''simple docstring'''



from typing import TYPE_CHECKING

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


lowerCamelCase_			=						{
    'configuration_ctrl': ['CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CTRLConfig'],
    'tokenization_ctrl': ['CTRLTokenizer'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase_			=						[
     'CTRL_PRETRAINED_MODEL_ARCHIVE_LIST',
     'CTRLForSequenceClassification',
     'CTRLLMHeadModel',
     'CTRLModel',
     'CTRLPreTrainedModel',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase_			=						[
     'TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFCTRLForSequenceClassification',
     'TFCTRLLMHeadModel',
     'TFCTRLModel',
     'TFCTRLPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig
 from .tokenization_ctrl import CTRLTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_ctrl import (
      CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
      CTRLForSequenceClassification,
      CTRLLMHeadModel,
      CTRLModel,
      CTRLPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_ctrl import (
      TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFCTRLForSequenceClassification,
      TFCTRLLMHeadModel,
      TFCTRLModel,
      TFCTRLPreTrainedModel,
  )

else:
 import sys

 lowerCamelCase_			=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

