





'''simple docstring'''




import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing




class      UpperCamelCase__					(					lowercase_			):




					"""simple docstring"""


					def __init__(						self				:			Any      ,						lowerCamelCase_				:			str = "▁"      ,						lowerCamelCase_				:			bool = True      ,						lowerCamelCase_				:			Union[str, AddedToken] = "<unk>"      ,						lowerCamelCase_				:			Union[str, AddedToken] = "</s>"      ,						lowerCamelCase_				:			Union[str, AddedToken] = "<pad>"      ,						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				List[str]		=			{
							    """pad""": {"""id""": 0, """token""": pad_token},
							    """eos""": {"""id""": 1, """token""": eos_token},
							    """unk""": {"""id""": 2, """token""": unk_token},
							}

							SCREAMING_SNAKE_CASE :				Dict		=			[None] * len(self.special_tokens						)
							for token_dict in self.special_tokens.values():
									SCREAMING_SNAKE_CASE :				Optional[Any]		=			token_dict["""token"""]

							SCREAMING_SNAKE_CASE :				List[str]		=			Tokenizer(Unigram()						)

							SCREAMING_SNAKE_CASE :				List[Any]		=			normalizers.Sequence(
							    [
							        normalizers.Nmt(),
							        normalizers.NFKC(),
							        normalizers.Replace(Regex(""" {2,}"""						)      ,						""" """						),
							        normalizers.Lowercase(),
							    ]						)
							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			pre_tokenizers.Sequence(
							    [
							        pre_tokenizers.Metaspace(replacement=lowerCamelCase_      ,						add_prefix_space=lowerCamelCase_						),
							        pre_tokenizers.Digits(individual_digits=lowerCamelCase_						),
							        pre_tokenizers.Punctuation(),
							    ]						)
							SCREAMING_SNAKE_CASE :				List[Any]		=			decoders.Metaspace(replacement=lowerCamelCase_      ,						add_prefix_space=lowerCamelCase_						)

							SCREAMING_SNAKE_CASE :				Optional[int]		=			TemplateProcessing(
							    single=f'''$A {self.special_tokens["eos"]["token"]}'''      ,						special_tokens=[(self.special_tokens["""eos"""]["""token"""], self.special_tokens["""eos"""]["""id"""])]      ,						)

							SCREAMING_SNAKE_CASE :				Dict		=			{
							    """model""": """SentencePieceUnigram""",
							    """replacement""": replacement,
							    """add_prefix_space""": add_prefix_space,
							}

							super().__init__(lowerCamelCase_      ,						lowerCamelCase_						)


					def lowerCamelCase_			(						self				:			List[Any]      ,						lowerCamelCase_				:			Union[str, List[str]]      ,						lowerCamelCase_				:			int = 80_00      ,						lowerCamelCase_				:			bool = True      ,						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			trainers.UnigramTrainer(
							    vocab_size=lowerCamelCase_      ,						special_tokens=self.special_tokens_list      ,						show_progress=lowerCamelCase_      ,						)

							if isinstance(lowerCamelCase_      ,						lowerCamelCase_						):
									SCREAMING_SNAKE_CASE :				List[str]		=			[files]
							self._tokenizer.train(lowerCamelCase_      ,						trainer=lowerCamelCase_						)

							self.add_unk_id()


					def lowerCamelCase_			(						self				:			str      ,						lowerCamelCase_				:			Union[Iterator[str], Iterator[Iterator[str]]]      ,						lowerCamelCase_				:			int = 80_00      ,						lowerCamelCase_				:			bool = True      ,						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				str		=			trainers.UnigramTrainer(
							    vocab_size=lowerCamelCase_      ,						special_tokens=self.special_tokens_list      ,						show_progress=lowerCamelCase_      ,						)

							self._tokenizer.train_from_iterator(lowerCamelCase_      ,						trainer=lowerCamelCase_						)

							self.add_unk_id()



					def lowerCamelCase_			(						self				:			Optional[int]						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Optional[int]		=			json.loads(self._tokenizer.to_str()						)

							SCREAMING_SNAKE_CASE :				Dict		=			self.special_tokens["""unk"""]["""id"""]

							SCREAMING_SNAKE_CASE :				List[Any]		=			Tokenizer.from_str(json.dumps(lowerCamelCase_						)						)










'''simple docstring'''




import os
import sys
import unittest


__UpperCAmelCase            =       os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
__UpperCAmelCase            =       os.path.join(git_repo_path, """src""", """transformers""")

__UpperCAmelCase            =       """
{0} = None
"""

__UpperCAmelCase            =       """
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
"""


__UpperCAmelCase            =       """
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
"""




class      UpperCamelCase__					(					unittest.TestCase			):




					"""simple docstring"""


					def lowerCamelCase_			(						self				:			List[str]						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Dict		=			find_backend("""    _import_structure[\"models.albert\"].append(\"AlbertTokenizerFast\")"""						)
							self.assertIsNone(lowerCamelCase_						)

							SCREAMING_SNAKE_CASE :				str		=			find_backend("""    if not is_tokenizers_available():"""						)
							self.assertEqual(lowerCamelCase_      ,						"""tokenizers"""						)

							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			find_backend("""    if not is_tensorflow_text_available():"""						)
							self.assertEqual(lowerCamelCase_      ,						"""tensorflow_text"""						)

							SCREAMING_SNAKE_CASE :				List[str]		=			find_backend("""    if not (is_sentencepiece_available() and is_tokenizers_available()):"""						)
							self.assertEqual(lowerCamelCase_      ,						"""sentencepiece_and_tokenizers"""						)

							SCREAMING_SNAKE_CASE :				Tuple		=			find_backend(
							    """    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"""						)
							self.assertEqual(lowerCamelCase_      ,						"""sentencepiece_and_tensorflow_text"""						)

							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			find_backend(
							    """    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):"""						)
							self.assertEqual(lowerCamelCase_      ,						"""sentencepiece_and_tokenizers_and_vision"""						)


					def lowerCamelCase_			(						self				:			Any						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Optional[Any]		=			read_init()
							# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
							self.assertIn("""torch"""      ,						lowerCamelCase_						)
							self.assertIn("""tensorflow_text"""      ,						lowerCamelCase_						)
							self.assertIn("""sentencepiece_and_tokenizers"""      ,						lowerCamelCase_						)

							# Likewise, we can't assert on the exact content of a key
							self.assertIn("""BertModel"""      ,						objects["""torch"""]						)
							self.assertIn("""TFBertModel"""      ,						objects["""tf"""]						)
							self.assertIn("""FlaxBertModel"""      ,						objects["""flax"""]						)
							self.assertIn("""BertModel"""      ,						objects["""torch"""]						)
							self.assertIn("""TFBertTokenizer"""      ,						objects["""tensorflow_text"""]						)
							self.assertIn("""convert_slow_tokenizer"""      ,						objects["""sentencepiece_and_tokenizers"""]						)


					def lowerCamelCase_			(						self				:			int						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				str		=			create_dummy_object("""CONSTANT"""      ,						"""'torch'"""						)
							self.assertEqual(lowerCamelCase_      ,						"""\nCONSTANT = None\n"""						)

							SCREAMING_SNAKE_CASE :				List[Any]		=			create_dummy_object("""function"""      ,						"""'torch'"""						)
							self.assertEqual(
							    lowerCamelCase_      ,						"""\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"""						)

							SCREAMING_SNAKE_CASE :				str		=			"""
class FakeClass(metaclass=DummyObject):
    _backends = 'torch'

    def __init__(self, *args, **kwargs):
        requires_backends(self, 'torch')
"""
							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			create_dummy_object("""FakeClass"""      ,						"""'torch'"""						)
							self.assertEqual(lowerCamelCase_      ,						lowerCamelCase_						)



					def lowerCamelCase_			(						self				:			int						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			"""# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends


CONSTANT = None


def function(*args, **kwargs):
    requires_backends(function, [\"torch\"])


class FakeClass(metaclass=DummyObject):
    _backends = [\"torch\"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, [\"torch\"])
"""
							SCREAMING_SNAKE_CASE :				List[Any]		=			create_dummy_files({"""torch""": ["""CONSTANT""", """function""", """FakeClass"""]}						)
							self.assertEqual(dummy_files["""torch"""]      ,						lowerCamelCase_						)



