




import os
import unittest

from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin




class 					snake_case__							(_UpperCamelCase					, unittest.TestCase     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							Any											=      TransfoXLTokenizer
				SCREAMING_SNAKE_CASE_ :							List[Any]											=      False
				SCREAMING_SNAKE_CASE_ :							Union[str, Any]											=      False





				def 							__UpperCAmelCase							(   self       :  str							)      ->  Optional[int]:
							super().setUp()

							a					=    [
							    "<unk>",
							    "[CLS]",
							    "[SEP]",
							    "want",
							    "unwanted",
							    "wa",
							    "un",
							    "running",
							    ",",
							    "low",
							    "l",
							]
							a					=    os.path.join(self.tmpdirname      ,   VOCAB_FILES_NAMES["vocab_file"]							)
							with open(self.vocab_file      ,   "w"      ,   encoding="utf-8"							) as vocab_writer:
										vocab_writer.write("".join([x + "\n" for x in vocab_tokens]							)							)





				def 							__UpperCAmelCase							(   self       :  List[str]      ,   **__lowerCamelCase       :  Any							)      ->  Union[str, Any]:
							a					=    True
							return TransfoXLTokenizer.from_pretrained(self.tmpdirname      ,   **__lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  Dict      ,   __lowerCamelCase       :  Tuple							)      ->  List[Any]:
							a					=    "<unk> UNwanted , running"
							a					=    "<unk> unwanted, running"
							return input_text, output_text





				def 							__UpperCAmelCase							(   self       :  Union[str, Any]							)      ->  Optional[int]:
							a					=    TransfoXLTokenizer(vocab_file=self.vocab_file      ,   lower_case=__lowerCamelCase							)

							a					=    tokenizer.tokenize("<unk> UNwanted , running"							)
							self.assertListEqual(__lowerCamelCase      ,   ["<unk>", "unwanted", ",", "running"]							)

							self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase							)      ,   [0, 4, 8, 7]							)





				def 							__UpperCAmelCase							(   self       :  Dict							)      ->  int:
							a					=    TransfoXLTokenizer(lower_case=__lowerCamelCase							)

							self.assertListEqual(
							    tokenizer.tokenize(" \tHeLLo ! how  \n Are yoU ?  "							)      ,   ["hello", "!", "how", "are", "you", "?"]							)





				def 							__UpperCAmelCase							(   self       :  Dict							)      ->  Dict:
							a					=    TransfoXLTokenizer(lower_case=__lowerCamelCase							)

							self.assertListEqual(
							    tokenizer.tokenize(" \tHeLLo ! how  \n Are yoU ?  "							)      ,   ["HeLLo", "!", "how", "Are", "yoU", "?"]							)





				def 							__UpperCAmelCase							(   self       :  Tuple							)      ->  List[str]:
							a					=    TransfoXLTokenizer(lower_case=__lowerCamelCase							)
							a					=    "Hello (bracket) and side-scrolled [and] Henry's $5,000 with 3.34 m. What's up!?"
							a					=    [
							    "Hello",
							    "(",
							    "bracket",
							    ")",
							    "and",
							    "side",
							    "@-@",
							    "scrolled",
							    "[",
							    "and",
							    "]",
							    "Henry",
							    "'s",
							    "$",
							    "5",
							    "@,@",
							    "000",
							    "with",
							    "3",
							    "@.@",
							    "34",
							    "m",
							    ".",
							    "What",
							    "'s",
							    "up",
							    "!",
							    "?",
							]

							self.assertListEqual(tokenizer.tokenize(__lowerCamelCase							)      ,   __lowerCamelCase							)

							self.assertEqual(tokenizer.convert_tokens_to_string(__lowerCamelCase							)      ,   __lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  str							)      ->  Dict:
							a					=    self.get_tokenizer()
							a					=    len(__lowerCamelCase							)

							tokenizer.add_tokens(["new1", "new2"]							)
							tokenizer.move_added_token("new1"      ,   1							)

							# Check that moved token is not copied (duplicate)
							self.assertEqual(len(__lowerCamelCase							)      ,   original_len + 2							)
							# Check that token is moved to specified id
							self.assertEqual(tokenizer.encode("new1"							)      ,   [1]							)
							self.assertEqual(tokenizer.decode([1]							)      ,   "new1"							)












from typing import TYPE_CHECKING

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


__lowerCAmelCase	:       Any     =	{
    'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'],
    'tokenization_roc_bert': ['RoCBertTokenizer'],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		pass

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase	:       Optional[Any]     =	[
		    'ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'RoCBertForCausalLM',
		    'RoCBertForMaskedLM',
		    'RoCBertForMultipleChoice',
		    'RoCBertForPreTraining',
		    'RoCBertForQuestionAnswering',
		    'RoCBertForSequenceClassification',
		    'RoCBertForTokenClassification',
		    'RoCBertLayer',
		    'RoCBertModel',
		    'RoCBertPreTrainedModel',
		    'load_tf_weights_in_roc_bert',
		]

if TYPE_CHECKING:
		from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
		from .tokenization_roc_bert import RoCBertTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				raise OptionalDependencyNotAvailable()

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_roc_bert import (
				    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    RoCBertForCausalLM,
				    RoCBertForMaskedLM,
				    RoCBertForMultipleChoice,
				    RoCBertForPreTraining,
				    RoCBertForQuestionAnswering,
				    RoCBertForSequenceClassification,
				    RoCBertForTokenClassification,
				    RoCBertLayer,
				    RoCBertModel,
				    RoCBertPreTrainedModel,
				    load_tf_weights_in_roc_bert,
				)


else:
		import sys

		__lowerCAmelCase	:       Union[str, Any]     =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






