import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path

import pytest

import transformers
from transformers import (
    BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
    GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
    AutoTokenizer,
    BertConfig,
    BertTokenizer,
    BertTokenizerFast,
    CTRLTokenizer,
    GPTaTokenizer,
    GPTaTokenizerFast,
    PreTrainedTokenizerFast,
    RobertaTokenizer,
    RobertaTokenizerFast,
    is_tokenizers_available,
)
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.auto.tokenization_auto import (
    TOKENIZER_MAPPING,
    get_tokenizer_config,
    tokenizer_class_from_name,
)
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import (
    DUMMY_DIFF_TOKENIZER_IDENTIFIER,
    DUMMY_UNKNOWN_IDENTIFIER,
    SMALL_MODEL_IDENTIFIER,
    RequestCounter,
    require_tokenizers,
    slow,
)


sys.path.append(str(Path(__file__).parent.parent.parent.parent / """utils"""))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
       from test_module.custom_tokenization_fast import CustomTokenizerFast


class       UpperCAmelCase__     (		unittest.TestCase       ):



  """simple docstring"""






  def 						_UpperCAmelCase					(					self:      int )			->			str:




    '''simple docstring'''




    __UpperCAmelCase         =							0






  @slow
  def 						_UpperCAmelCase					(					self:      List[Any] )			->			Optional[Any]:




    '''simple docstring'''




    for model_name in (x for x in BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() if "japanese" not in x):
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase )
      self.assertIsNotNone(__lowerCAmelCase )
      self.assertIsInstance(__lowerCAmelCase					,					(BertTokenizer, BertTokenizerFast) )
      self.assertGreater(len(__lowerCAmelCase )					,					0 )

    for model_name in GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP.keys():
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase )
      self.assertIsNotNone(__lowerCAmelCase )
      self.assertIsInstance(__lowerCAmelCase					,					(GPTaTokenizer, GPTaTokenizerFast) )
      self.assertGreater(len(__lowerCAmelCase )					,					0 )






  def 						_UpperCAmelCase					(					self:      Dict )			->			Optional[Any]:




    '''simple docstring'''




    __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase )
    self.assertIsInstance(__lowerCAmelCase					,					(BertTokenizer, BertTokenizerFast) )
    self.assertEqual(tokenizer.vocab_size					,					12 )






  def 						_UpperCAmelCase					(					self:      int )			->			Tuple:




    '''simple docstring'''




    __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase )
    self.assertIsInstance(__lowerCAmelCase					,					(RobertaTokenizer, RobertaTokenizerFast) )
    self.assertEqual(tokenizer.vocab_size					,					20 )






  def 						_UpperCAmelCase					(					self:      str )			->			Dict:




    '''simple docstring'''




    __UpperCAmelCase         =							AutoConfig.from_pretrained(__lowerCAmelCase )
    self.assertIsInstance(__lowerCAmelCase					,					__lowerCAmelCase )
    # Check that tokenizer_type ≠ model_type
    __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase					,					config=__lowerCAmelCase )
    self.assertIsInstance(__lowerCAmelCase					,					(BertTokenizer, BertTokenizerFast) )
    self.assertEqual(tokenizer.vocab_size					,					12 )






  def 						_UpperCAmelCase					(					self:      Tuple )			->			Any:




    '''simple docstring'''




    with tempfile.TemporaryDirectory() as tmp_dir:
      shutil.copy("./tests/fixtures/vocab.txt"					,					os.path.join(__lowerCAmelCase					,					"vocab.txt" ) )

      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase					,					tokenizer_type="bert"					,					use_fast=__lowerCAmelCase )
      self.assertIsInstance(__lowerCAmelCase					,					__lowerCAmelCase )

    with tempfile.TemporaryDirectory() as tmp_dir:
      shutil.copy("./tests/fixtures/vocab.json"					,					os.path.join(__lowerCAmelCase					,					"vocab.json" ) )
      shutil.copy("./tests/fixtures/merges.txt"					,					os.path.join(__lowerCAmelCase					,					"merges.txt" ) )

      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase					,					tokenizer_type="gpt2"					,					use_fast=__lowerCAmelCase )
      self.assertIsInstance(__lowerCAmelCase					,					__lowerCAmelCase )






  @require_tokenizers
  def 						_UpperCAmelCase					(					self:      Any )			->			Dict:




    '''simple docstring'''




    with tempfile.TemporaryDirectory() as tmp_dir:
      shutil.copy("./tests/fixtures/vocab.txt"					,					os.path.join(__lowerCAmelCase					,					"vocab.txt" ) )

      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase					,					tokenizer_type="bert" )
      self.assertIsInstance(__lowerCAmelCase					,					__lowerCAmelCase )

    with tempfile.TemporaryDirectory() as tmp_dir:
      shutil.copy("./tests/fixtures/vocab.json"					,					os.path.join(__lowerCAmelCase					,					"vocab.json" ) )
      shutil.copy("./tests/fixtures/merges.txt"					,					os.path.join(__lowerCAmelCase					,					"merges.txt" ) )

      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase					,					tokenizer_type="gpt2" )
      self.assertIsInstance(__lowerCAmelCase					,					__lowerCAmelCase )






  def 						_UpperCAmelCase					(					self:      int )			->			str:




    '''simple docstring'''




    with pytest.raises(__lowerCAmelCase ):
      AutoTokenizer.from_pretrained("./"					,					tokenizer_type="xxx" )






  @require_tokenizers
  def 						_UpperCAmelCase					(					self:      List[str] )			->			List[Any]:




    '''simple docstring'''




    for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
      __UpperCAmelCase         =							tokenizer_class.from_pretrained("wietsedv/bert-base-dutch-cased" )
      self.assertIsInstance(__lowerCAmelCase					,					(BertTokenizer, BertTokenizerFast) )

      if isinstance(__lowerCAmelCase					,					__lowerCAmelCase ):
        self.assertEqual(tokenizer.basic_tokenizer.do_lower_case					,					__lowerCAmelCase )
      else:
        self.assertEqual(tokenizer.do_lower_case					,					__lowerCAmelCase )

      self.assertEqual(tokenizer.model_max_length					,					512 )






  @require_tokenizers
  def 						_UpperCAmelCase					(					self:      str )			->			Tuple:




    '''simple docstring'''




    for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
      with self.assertRaisesRegex(
          __lowerCAmelCase					,					"julien-c/herlolip-not-exists is not a local folder and is not a valid model identifier"					,					):
        __UpperCAmelCase         =							tokenizer_class.from_pretrained("julien-c/herlolip-not-exists" )






  def 						_UpperCAmelCase					(					self:      Tuple )			->			Dict:




    '''simple docstring'''




    __UpperCAmelCase         =							TOKENIZER_MAPPING.values()
    __UpperCAmelCase         =							[]

    for slow_tok, fast_tok in tokenizers:
      if slow_tok is not None:
        tokenizer_names.append(slow_tok.__name__ )

      if fast_tok is not None:
        tokenizer_names.append(fast_tok.__name__ )

    for tokenizer_name in tokenizer_names:
      # must find the right class
      tokenizer_class_from_name(__lowerCAmelCase )






  @require_tokenizers
  def 						_UpperCAmelCase					(					self:      Union[str, Any] )			->			List[Any]:




    '''simple docstring'''




    self.assertIsInstance(AutoTokenizer.from_pretrained("bert-base-cased"					,					use_fast=__lowerCAmelCase )					,					__lowerCAmelCase )
    self.assertIsInstance(AutoTokenizer.from_pretrained("bert-base-cased" )					,					__lowerCAmelCase )






  @require_tokenizers
  def 						_UpperCAmelCase					(					self:      str )			->			Optional[Any]:




    '''simple docstring'''




    __UpperCAmelCase         =							AutoTokenizer.from_pretrained("distilbert-base-uncased"					,					do_lower_case=__lowerCAmelCase )
    __UpperCAmelCase         =							"Hello, world. How are you?"
    __UpperCAmelCase         =							tokenizer.tokenize(__lowerCAmelCase )
    self.assertEqual("[UNK]"					,					tokens[0] )

    __UpperCAmelCase         =							AutoTokenizer.from_pretrained("microsoft/mpnet-base"					,					do_lower_case=__lowerCAmelCase )
    __UpperCAmelCase         =							tokenizer.tokenize(__lowerCAmelCase )
    self.assertEqual("[UNK]"					,					tokens[0] )






  @require_tokenizers
  def 						_UpperCAmelCase					(					self:      Optional[int] )			->			Tuple:




    '''simple docstring'''




    __UpperCAmelCase         =							AutoTokenizer.from_pretrained("robot-test/dummy-tokenizer-fast-with-model-config" )
    self.assertEqual(type(__lowerCAmelCase )					,					__lowerCAmelCase )
    self.assertEqual(tokenizer.model_max_length					,					512 )
    self.assertEqual(tokenizer.vocab_size					,					30_000 )
    self.assertEqual(tokenizer.unk_token					,					"[UNK]" )
    self.assertEqual(tokenizer.padding_side					,					"right" )
    self.assertEqual(tokenizer.truncation_side					,					"right" )






  def 						_UpperCAmelCase					(					self:      Dict )			->			Tuple:




    '''simple docstring'''




    __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase )
    self.assertIsInstance(__lowerCAmelCase					,					(BertTokenizer, BertTokenizerFast) )
    with tempfile.TemporaryDirectory() as tmp_dir:
      tokenizer.save_pretrained(__lowerCAmelCase )
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase )

    self.assertIsInstance(__lowerCAmelCase					,					tokenizer.__class__ )
    self.assertEqual(tokenizera.vocab_size					,					12 )






  def 						_UpperCAmelCase					(					self:      Optional[Any] )			->			Optional[Any]:




    '''simple docstring'''




    __UpperCAmelCase         =							AutoTokenizer.from_pretrained("ctrl" )
    # There is no fast CTRL so this always gives us a slow tokenizer.
    self.assertIsInstance(__lowerCAmelCase					,					__lowerCAmelCase )






  def 						_UpperCAmelCase					(					self:      Optional[Any] )			->			str:




    '''simple docstring'''




    __UpperCAmelCase         =							get_tokenizer_config("bert-base-cased" )
    __UpperCAmelCase         =							config.pop("_commit_hash"					,					__lowerCAmelCase )
    # If we ever update bert-base-cased tokenizer config, this dict here will need to be updated.
    self.assertEqual(__lowerCAmelCase					,					{"do_lower_case": False} )

    # This model does not have a tokenizer_config so we get back an empty dict.
    __UpperCAmelCase         =							get_tokenizer_config(__lowerCAmelCase )
    self.assertDictEqual(__lowerCAmelCase					,					{} )

    # A tokenizer saved with `save_pretrained` always creates a tokenizer config.
    __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase )
    with tempfile.TemporaryDirectory() as tmp_dir:
      tokenizer.save_pretrained(__lowerCAmelCase )
      __UpperCAmelCase         =							get_tokenizer_config(__lowerCAmelCase )

    # Check the class of the tokenizer was properly saved (note that it always saves the slow class).
    self.assertEqual(config["tokenizer_class"]					,					"BertTokenizer" )






  def 						_UpperCAmelCase					(					self:      List[str] )			->			List[str]:




    '''simple docstring'''




    try:
      AutoConfig.register("custom"					,					__lowerCAmelCase )

      AutoTokenizer.register(__lowerCAmelCase					,					slow_tokenizer_class=__lowerCAmelCase )
      # Trying to register something existing in the Transformers library will raise an error
      with self.assertRaises(__lowerCAmelCase ):
        AutoTokenizer.register(__lowerCAmelCase					,					slow_tokenizer_class=__lowerCAmelCase )

      __UpperCAmelCase         =							CustomTokenizer.from_pretrained(__lowerCAmelCase )
      with tempfile.TemporaryDirectory() as tmp_dir:
        tokenizer.save_pretrained(__lowerCAmelCase )

        __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase )
        self.assertIsInstance(__lowerCAmelCase					,					__lowerCAmelCase )

    finally:
      if "custom" in CONFIG_MAPPING._extra_content:
        del CONFIG_MAPPING._extra_content["custom"]
      if CustomConfig in TOKENIZER_MAPPING._extra_content:
        del TOKENIZER_MAPPING._extra_content[CustomConfig]






  @require_tokenizers
  def 						_UpperCAmelCase					(					self:      List[str] )			->			Union[str, Any]:




    '''simple docstring'''




    try:
      AutoConfig.register("custom"					,					__lowerCAmelCase )

      # Can register in two steps
      AutoTokenizer.register(__lowerCAmelCase					,					slow_tokenizer_class=__lowerCAmelCase )
      self.assertEqual(TOKENIZER_MAPPING[CustomConfig]					,					(CustomTokenizer, None) )
      AutoTokenizer.register(__lowerCAmelCase					,					fast_tokenizer_class=__lowerCAmelCase )
      self.assertEqual(TOKENIZER_MAPPING[CustomConfig]					,					(CustomTokenizer, CustomTokenizerFast) )

      del TOKENIZER_MAPPING._extra_content[CustomConfig]
      # Can register in one step
      AutoTokenizer.register(
          __lowerCAmelCase					,					slow_tokenizer_class=__lowerCAmelCase					,					fast_tokenizer_class=__lowerCAmelCase )
      self.assertEqual(TOKENIZER_MAPPING[CustomConfig]					,					(CustomTokenizer, CustomTokenizerFast) )

      # Trying to register something existing in the Transformers library will raise an error
      with self.assertRaises(__lowerCAmelCase ):
        AutoTokenizer.register(__lowerCAmelCase					,					fast_tokenizer_class=__lowerCAmelCase )

      # We pass through a bert tokenizer fast cause there is no converter slow to fast for our new toknizer
      # and that model does not have a tokenizer.json
      with tempfile.TemporaryDirectory() as tmp_dir:
        __UpperCAmelCase         =							BertTokenizerFast.from_pretrained(__lowerCAmelCase )
        bert_tokenizer.save_pretrained(__lowerCAmelCase )
        __UpperCAmelCase         =							CustomTokenizerFast.from_pretrained(__lowerCAmelCase )

      with tempfile.TemporaryDirectory() as tmp_dir:
        tokenizer.save_pretrained(__lowerCAmelCase )

        __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase )
        self.assertIsInstance(__lowerCAmelCase					,					__lowerCAmelCase )

        __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase					,					use_fast=__lowerCAmelCase )
        self.assertIsInstance(__lowerCAmelCase					,					__lowerCAmelCase )

    finally:
      if "custom" in CONFIG_MAPPING._extra_content:
        del CONFIG_MAPPING._extra_content["custom"]
      if CustomConfig in TOKENIZER_MAPPING._extra_content:
        del TOKENIZER_MAPPING._extra_content[CustomConfig]






  def 						_UpperCAmelCase					(					self:      int )			->			List[Any]:




    '''simple docstring'''




    with self.assertRaises(__lowerCAmelCase ):
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer" )
    # If remote code is disabled, we can't load this config.
    with self.assertRaises(__lowerCAmelCase ):
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(
          "hf-internal-testing/test_dynamic_tokenizer"					,					trust_remote_code=__lowerCAmelCase )

    __UpperCAmelCase         =							AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer"					,					trust_remote_code=__lowerCAmelCase )
    self.assertTrue(tokenizer.special_attribute_present )
    # Test tokenizer can be reloaded.
    with tempfile.TemporaryDirectory() as tmp_dir:
      tokenizer.save_pretrained(__lowerCAmelCase )
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase					,					trust_remote_code=__lowerCAmelCase )
    self.assertTrue(reloaded_tokenizer.special_attribute_present )

    if is_tokenizers_available():
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizerFast" )
      self.assertEqual(reloaded_tokenizer.__class__.__name__					,					"NewTokenizerFast" )

      # Test we can also load the slow version
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(
          "hf-internal-testing/test_dynamic_tokenizer"					,					trust_remote_code=__lowerCAmelCase					,					use_fast=__lowerCAmelCase )
      self.assertTrue(tokenizer.special_attribute_present )
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizer" )
      # Test tokenizer can be reloaded.
      with tempfile.TemporaryDirectory() as tmp_dir:
        tokenizer.save_pretrained(__lowerCAmelCase )
        __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase					,					trust_remote_code=__lowerCAmelCase					,					use_fast=__lowerCAmelCase )
      self.assertEqual(reloaded_tokenizer.__class__.__name__					,					"NewTokenizer" )
      self.assertTrue(reloaded_tokenizer.special_attribute_present )
    else:
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizer" )
      self.assertEqual(reloaded_tokenizer.__class__.__name__					,					"NewTokenizer" )






  @require_tokenizers
  def 						_UpperCAmelCase					(					self:      Any )			->			str:




    '''simple docstring'''




    class       UpperCAmelCase__     (		_a       ):



      """simple docstring"""






      lowerCAmelCase__		:						List[str]     		=			False






    class       UpperCAmelCase__     (		_a       ):



      """simple docstring"""






      lowerCAmelCase__		:						Dict     		=			NewTokenizer
      lowerCAmelCase__		:						List[Any]     		=			False

    try:
      AutoConfig.register("custom"					,					__lowerCAmelCase )
      AutoTokenizer.register(__lowerCAmelCase					,					slow_tokenizer_class=__lowerCAmelCase )
      AutoTokenizer.register(__lowerCAmelCase					,					fast_tokenizer_class=__lowerCAmelCase )
      # If remote code is not set, the default is to use local
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer" )
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizerFast" )
      self.assertFalse(tokenizer.special_attribute_present )
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer"					,					use_fast=__lowerCAmelCase )
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizer" )
      self.assertFalse(tokenizer.special_attribute_present )

      # If remote code is disabled, we load the local one.
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(
          "hf-internal-testing/test_dynamic_tokenizer"					,					trust_remote_code=__lowerCAmelCase )
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizerFast" )
      self.assertFalse(tokenizer.special_attribute_present )
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(
          "hf-internal-testing/test_dynamic_tokenizer"					,					trust_remote_code=__lowerCAmelCase					,					use_fast=__lowerCAmelCase )
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizer" )
      self.assertFalse(tokenizer.special_attribute_present )

      # If remote is enabled, we load from the Hub
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(
          "hf-internal-testing/test_dynamic_tokenizer"					,					trust_remote_code=__lowerCAmelCase )
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizerFast" )
      self.assertTrue(tokenizer.special_attribute_present )
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(
          "hf-internal-testing/test_dynamic_tokenizer"					,					trust_remote_code=__lowerCAmelCase					,					use_fast=__lowerCAmelCase )
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizer" )
      self.assertTrue(tokenizer.special_attribute_present )

    finally:
      if "custom" in CONFIG_MAPPING._extra_content:
        del CONFIG_MAPPING._extra_content["custom"]
      if CustomConfig in TOKENIZER_MAPPING._extra_content:
        del TOKENIZER_MAPPING._extra_content[CustomConfig]






  def 						_UpperCAmelCase					(					self:      List[str] )			->			Dict:




    '''simple docstring'''




    __UpperCAmelCase         =							AutoTokenizer.from_pretrained(
        "hf-internal-testing/test_dynamic_tokenizer_legacy"					,					trust_remote_code=__lowerCAmelCase )
    self.assertTrue(tokenizer.special_attribute_present )
    if is_tokenizers_available():
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizerFast" )

      # Test we can also load the slow version
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(
          "hf-internal-testing/test_dynamic_tokenizer_legacy"					,					trust_remote_code=__lowerCAmelCase					,					use_fast=__lowerCAmelCase )
      self.assertTrue(tokenizer.special_attribute_present )
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizer" )
    else:
      self.assertEqual(tokenizer.__class__.__name__					,					"NewTokenizer" )






  def 						_UpperCAmelCase					(					self:      List[Any] )			->			Any:




    '''simple docstring'''




    with self.assertRaisesRegex(
        __lowerCAmelCase					,					"bert-base is not a local folder and is not a valid model identifier" ):
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained("bert-base" )






  def 						_UpperCAmelCase					(					self:      List[str] )			->			List[str]:




    '''simple docstring'''




    with self.assertRaisesRegex(
        __lowerCAmelCase					,					r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)" ):
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained(__lowerCAmelCase					,					revision="aaaaaa" )






  def 						_UpperCAmelCase					(					self:      Optional[Any] )			->			Tuple:




    '''simple docstring'''




    __UpperCAmelCase         =							AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert" )
    with RequestCounter() as counter:
      __UpperCAmelCase         =							AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert" )
      self.assertEqual(counter.get_request_count					,					0 )
      self.assertEqual(counter.head_request_count					,					1 )
      self.assertEqual(counter.other_request_count					,					0 )










import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
					from .tokenization_big_bird import BigBirdTokenizer
else:
					UpperCamelCase__           =			None

UpperCamelCase__           =			logging.get_logger(__name__)
UpperCamelCase__           =			{"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

UpperCamelCase__           =			{
    "vocab_file": {
        "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model",
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"
        ),
    },
    "tokenizer_file": {
        "google/bigbird-roberta-base": (
            "https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json"
        ),
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json"
        ),
    },
}

UpperCamelCase__           =			{
    "google/bigbird-roberta-base": 4_096,
    "google/bigbird-roberta-large": 4_096,
    "google/bigbird-base-trivia-itc": 4_096,
}


UpperCamelCase__           =			"▁"

class 							__SCREAMING_SNAKE_CASE       (  _a							):
							snake_case  :   Optional[Any]      =							VOCAB_FILES_NAMES
							snake_case  :   List[str]      =							PRETRAINED_VOCAB_FILES_MAP
							snake_case  :   List[str]      =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							snake_case  :   int      =							BigBirdTokenizer
							snake_case  :   List[Any]      =							["""input_ids""", """attention_mask"""]
							snake_case  :   List[int]      =							[]






							def __init__(    self	,			__lowerCAmelCase=None	,			__lowerCAmelCase=None	,			__lowerCAmelCase="<unk>"	,			__lowerCAmelCase="<s>"	,			__lowerCAmelCase="</s>"	,			__lowerCAmelCase="<pad>"	,			__lowerCAmelCase="[SEP]"	,			__lowerCAmelCase="[MASK]"	,			__lowerCAmelCase="[CLS]"	,			**__lowerCAmelCase	,			):
														UpperCamelCase__					  =      AddedToken(__lowerCAmelCase	,			lstrip=__lowerCAmelCase	,			rstrip=__lowerCAmelCase	) if isinstance(__lowerCAmelCase	,			__lowerCAmelCase	) else bos_token
														UpperCamelCase__					  =      AddedToken(__lowerCAmelCase	,			lstrip=__lowerCAmelCase	,			rstrip=__lowerCAmelCase	) if isinstance(__lowerCAmelCase	,			__lowerCAmelCase	) else eos_token
														UpperCamelCase__					  =      AddedToken(__lowerCAmelCase	,			lstrip=__lowerCAmelCase	,			rstrip=__lowerCAmelCase	) if isinstance(__lowerCAmelCase	,			__lowerCAmelCase	) else unk_token
														UpperCamelCase__					  =      AddedToken(__lowerCAmelCase	,			lstrip=__lowerCAmelCase	,			rstrip=__lowerCAmelCase	) if isinstance(__lowerCAmelCase	,			__lowerCAmelCase	) else pad_token
														UpperCamelCase__					  =      AddedToken(__lowerCAmelCase	,			lstrip=__lowerCAmelCase	,			rstrip=__lowerCAmelCase	) if isinstance(__lowerCAmelCase	,			__lowerCAmelCase	) else cls_token
														UpperCamelCase__					  =      AddedToken(__lowerCAmelCase	,			lstrip=__lowerCAmelCase	,			rstrip=__lowerCAmelCase	) if isinstance(__lowerCAmelCase	,			__lowerCAmelCase	) else sep_token

														# Mask token behave like a normal word, i.e. include the space before it
														UpperCamelCase__					  =      AddedToken(__lowerCAmelCase	,			lstrip=__lowerCAmelCase	,			rstrip=__lowerCAmelCase	) if isinstance(__lowerCAmelCase	,			__lowerCAmelCase	) else mask_token

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

														UpperCamelCase__					  =      vocab_file
														UpperCamelCase__					  =      False if not self.vocab_file else True






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase = None	):
														UpperCamelCase__					  =      [self.sep_token_id]
														UpperCamelCase__					  =      [self.cls_token_id]
														if token_ids_a is None:
																					return cls + token_ids_a + sep
														return cls + token_ids_a + sep + token_ids_a + sep






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase = None	,			__lowerCAmelCase = False	):

														if already_has_special_tokens:
																					if token_ids_a is not None:
																												raise ValueError(
																												    """You should not supply a second sequence if the provided sequence of """
																												    """ids is already formatted with special tokens for the model."""	)
																					return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

														if token_ids_a is None:
																					return [1] + ([0] * len(__lowerCAmelCase	)) + [1]
														return [1] + ([0] * len(__lowerCAmelCase	)) + [1] + ([0] * len(__lowerCAmelCase	)) + [1]






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase = None	):
														UpperCamelCase__					  =      [self.sep_token_id]
														UpperCamelCase__					  =      [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 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase = None	):
														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(__lowerCAmelCase	):
																					logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""	)
																					return
														UpperCamelCase__					  =      os.path.join(
														    __lowerCAmelCase	,			(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]	)

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

														return (out_vocab_file,)




