import json
import os
import unittest

from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin
class     a_			(						__A	,					unittest.TestCase						):






 '''simple docstring'''






 UpperCAmelCase_     			= CTRLTokenizer
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False




 def 		__snake_case						(      self :  Tuple):







        '''simple docstring'''



        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        lowerCAmelCase__					     = ['adapt', 're@@', 'a@@', 'apt', 'c@@', 't', '<unk>']
        lowerCAmelCase__					     = dict(zip(__lowercase      ,   range(len(__lowercase))))
        lowerCAmelCase__					     = ['#version: 0.2', 'a p', 'ap t</w>', 'r e', 'a d', 'ad apt</w>', '']
        lowerCAmelCase__					     = {'unk_token': '<unk>'}

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




 def 		__snake_case						(      self :  List[str]      ,   **lowercase__ :  int):







        '''simple docstring'''



        kwargs.update(self.special_tokens_map)
        return CTRLTokenizer.from_pretrained(self.tmpdirname      ,   **__lowercase)




 def 		__snake_case						(      self :  str      ,   lowercase__ :  str):







        '''simple docstring'''



        lowerCAmelCase__					     = 'adapt react readapt apt'
        lowerCAmelCase__					     = 'adapt react readapt apt'
        return input_text, output_text




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







        '''simple docstring'''



        lowerCAmelCase__					     = CTRLTokenizer(self.vocab_file      ,   self.merges_file      ,   **self.special_tokens_map)
        lowerCAmelCase__					     = 'adapt react readapt apt'
        lowerCAmelCase__					     = 'adapt re@@ a@@ c@@ t re@@ adapt apt'.split()
        lowerCAmelCase__					     = tokenizer.tokenize(__lowercase)
        self.assertListEqual(__lowercase      ,   __lowercase)

        lowerCAmelCase__					     = tokens + [tokenizer.unk_token]

        lowerCAmelCase__					     = [0, 1, 2, 4, 5, 1, 0, 3, 6]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowercase)      ,   __lowercase)

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


if is_sentencepiece_available():
    from ..ta.tokenization_ta import TaTokenizer
else:
    from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCAmelCase__     						=			TaTokenizer

if is_tokenizers_available():
    from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
    from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCAmelCase__     						=			TaTokenizerFast

lowerCAmelCase__     						=			{'configuration_mt5': ['MT5Config', 'MT5OnnxConfig']}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			[
        'MT5EncoderModel',
        'MT5ForConditionalGeneration',
        'MT5ForQuestionAnswering',
        'MT5Model',
        'MT5PreTrainedModel',
        'MT5Stack',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			['TFMT5EncoderModel', 'TFMT5ForConditionalGeneration', 'TFMT5Model']

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			['FlaxMT5EncoderModel', 'FlaxMT5ForConditionalGeneration', 'FlaxMT5Model']


if TYPE_CHECKING:
    from .configuration_mta import MTaConfig, MTaOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mta import (
            MTaEncoderModel,
            MTaForConditionalGeneration,
            MTaForQuestionAnswering,
            MTaModel,
            MTaPreTrainedModel,
            MTaStack,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
    import sys

    lowerCAmelCase__     						=			_LazyModule(
        __name__,
        globals()['__file__'],
        _import_structure,
        extra_objects={'MT5Tokenizer': MTaTokenizer, 'MT5TokenizerFast': MTaTokenizerFast},
        module_spec=__spec__,
    )
