




'''simple docstring'''



import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







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


   """simple docstring"""

   lowerCamelCase_      =						RobertaTokenizer
   lowerCamelCase_      =						RobertaTokenizerFast
   lowerCamelCase_      =						True
   lowerCamelCase_      =						{'''cls_token''': '''<s>'''}



   def 							lowerCAmelCase_      (   self :     str   ):

      """simple docstring"""
      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      _SCREAMING_SNAKE_CASE	=				[
          "l",
          "o",
          "w",
          "e",
          "r",
          "s",
          "t",
          "i",
          "d",
          "n",
          "\u0120",
          "\u0120l",
          "\u0120n",
          "\u0120lo",
          "\u0120low",
          "er",
          "\u0120lowest",
          "\u0120newer",
          "\u0120wider",
          "<unk>",
      ]
      _SCREAMING_SNAKE_CASE	=				dict(zip(__lowerCamelCase  ,				range(len(__lowerCamelCase   )   )   )   )
      _SCREAMING_SNAKE_CASE	=				["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
      _SCREAMING_SNAKE_CASE	=				{"unk_token": "<unk>"}

      _SCREAMING_SNAKE_CASE	=				os.path.join(self.tmpdirname  ,				VOCAB_FILES_NAMES["vocab_file"]   )
      _SCREAMING_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(__lowerCamelCase   ) + "\n"   )
      with open(self.merges_file  ,				"w"  ,				encoding="utf-8"   ) as fp:
         fp.write("\n".join(__lowerCamelCase   )   )



   def 							lowerCAmelCase_      (   self :     List[Any]  ,				**__lowerCamelCase :     Optional[int]   ):

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



   def 							lowerCAmelCase_      (   self :     Optional[Any]  ,				**__lowerCamelCase :     Tuple   ):

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



   def 							lowerCAmelCase_      (   self :     int  ,				__lowerCamelCase :     str   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				"lower newer"
      _SCREAMING_SNAKE_CASE	=				"lower newer"
      return input_text, output_text



   def 							lowerCAmelCase_      (   self :     Optional[int]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				self.tokenizer_class(self.vocab_file  ,				self.merges_file  ,				**self.special_tokens_map   )
      _SCREAMING_SNAKE_CASE	=				"lower newer"
      _SCREAMING_SNAKE_CASE	=				["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
      _SCREAMING_SNAKE_CASE	=				tokenizer.tokenize(__lowerCamelCase   )  # , add_prefix_space=True)
      self.assertListEqual(__lowerCamelCase  ,				__lowerCamelCase   )

      _SCREAMING_SNAKE_CASE	=				tokens + [tokenizer.unk_token]
      _SCREAMING_SNAKE_CASE	=				[0, 1, 2, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase   )  ,				__lowerCamelCase   )



   def 							lowerCAmelCase_      (   self :     Optional[int]   ):

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

      self.assertListEqual(tokenizer.encode("Hello world!"  ,				add_special_tokens=__lowerCamelCase   )  ,				[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=__lowerCamelCase   )  ,				[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 							lowerCAmelCase_      (   self :     Optional[Any]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				self.tokenizer_class.from_pretrained("roberta-base"   )

      _SCREAMING_SNAKE_CASE	=				tokenizer.encode("sequence builders"  ,				add_special_tokens=__lowerCamelCase   )
      _SCREAMING_SNAKE_CASE	=				tokenizer.encode("multi-sequence build"  ,				add_special_tokens=__lowerCamelCase   )

      _SCREAMING_SNAKE_CASE	=				tokenizer.encode(
          "sequence builders"  ,				add_special_tokens=__lowerCamelCase  ,				add_prefix_space=__lowerCamelCase   )
      _SCREAMING_SNAKE_CASE	=				tokenizer.encode(
          "sequence builders"  ,				"multi-sequence build"  ,				add_special_tokens=__lowerCamelCase  ,				add_prefix_space=__lowerCamelCase   )

      _SCREAMING_SNAKE_CASE	=				tokenizer.build_inputs_with_special_tokens(__lowerCamelCase   )
      _SCREAMING_SNAKE_CASE	=				tokenizer.build_inputs_with_special_tokens(__lowerCamelCase  ,				__lowerCamelCase   )

      assert encoded_sentence == encoded_text_from_decode
      assert encoded_pair == encoded_pair_from_decode



   def 							lowerCAmelCase_      (   self :     Tuple   ):

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

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

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

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

      tokenizer.add_special_tokens({"bos_token": "<s>"}   )
      _SCREAMING_SNAKE_CASE	=				tokenizer.encode(__lowerCamelCase  ,				add_special_tokens=__lowerCamelCase   )
      _SCREAMING_SNAKE_CASE	=				tokenizer.convert_ids_to_tokens(encoded[1]   )[0]
      self.assertNotEqual(__lowerCamelCase  ,				__lowerCamelCase   )

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

      _SCREAMING_SNAKE_CASE	=				"Encode <mask> sequence"
      _SCREAMING_SNAKE_CASE	=				"Encode <mask>sequence"

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

      _SCREAMING_SNAKE_CASE	=				tokenizer.encode(__lowerCamelCase   )
      _SCREAMING_SNAKE_CASE	=				encoded.index(__lowerCamelCase   )
      _SCREAMING_SNAKE_CASE	=				tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]   )[0]
      self.assertNotEqual(__lowerCamelCase  ,				__lowerCamelCase   )



   def 							lowerCAmelCase_      (   self :     List[str]   ):

      """simple docstring"""
      pass



   def 							lowerCAmelCase_      (   self :     str   ):

      """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   )
            _SCREAMING_SNAKE_CASE	=				self.tokenizer_class.from_pretrained(__lowerCamelCase  ,				**__lowerCamelCase   )
            _SCREAMING_SNAKE_CASE	=				"A, <mask> AllenNLP sentence."
            _SCREAMING_SNAKE_CASE	=				tokenizer_r.encode_plus(__lowerCamelCase  ,				add_special_tokens=__lowerCamelCase  ,				return_token_type_ids=__lowerCamelCase   )
            _SCREAMING_SNAKE_CASE	=				tokenizer_p.encode_plus(__lowerCamelCase  ,				add_special_tokens=__lowerCamelCase  ,				return_token_type_ids=__lowerCamelCase   )

            # 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"]   )  ,				)

            _SCREAMING_SNAKE_CASE	=				tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]   )
            _SCREAMING_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(
                __lowerCamelCase  ,				["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]   )
            self.assertSequenceEqual(
                __lowerCamelCase  ,				["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]   )



   def 							lowerCAmelCase_      (   self :     str   ):

      """simple docstring"""
      for trim_offsets, add_prefix_space in itertools.product([True, False]  ,				repeat=2   ):
         _SCREAMING_SNAKE_CASE	=				self.rust_tokenizer_class.from_pretrained(
             self.tmpdirname  ,				use_fast=__lowerCamelCase  ,				add_prefix_space=__lowerCamelCase  ,				trim_offsets=__lowerCamelCase   )

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

         self.assertEqual(pre_tokenizer_state["add_prefix_space"]  ,				__lowerCamelCase   )

         self.assertEqual(post_processor_state["add_prefix_space"]  ,				__lowerCamelCase   )
         self.assertEqual(post_processor_state["trim_offsets"]  ,				__lowerCamelCase   )



   def 							lowerCAmelCase_      (   self :     Optional[int]   ):

      """simple docstring"""
      # 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})"""   ):
            _SCREAMING_SNAKE_CASE	=				"hello"  # `hello` is a token in the vocabulary of `pretrained_name`
            _SCREAMING_SNAKE_CASE	=				F"""{text_of_1_token} {text_of_1_token}"""

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

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

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

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

            _SCREAMING_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)),
            # )

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

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

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







'''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__)

