

import json
import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin




class      UpperCamelCase (     SCREAMING_SNAKE_CASE	,			unittest.TestCase   ):
    __UpperCamelCase         =CTRLTokenizer
    __UpperCamelCase         =False
    __UpperCamelCase         =False

    def UpperCamelCase			(			self :      int    ):

     """simple docstring"""






     super().setUp()

     # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
     SCREAMING_SNAKE_CASE								=			['adapt', 're@@', 'a@@', 'apt', 'c@@', 't', '<unk>']
     SCREAMING_SNAKE_CASE								=			dict(zip(snake_case__							,    range(len(snake_case__    )    )    )    )
     SCREAMING_SNAKE_CASE								=			['#version: 0.2', 'a p', 'ap t</w>', 'r e', 'a d', 'ad apt</w>', '']
     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(snake_case__    ) + '\n'    )
     with open(self.merges_file							,    'w'							,    encoding='utf-8'    ) as fp:
      fp.write('\n'.join(snake_case__    )    )

    def UpperCamelCase			(			self :      List[str]							,    **snake_case__ :      Any    ):

     """simple docstring"""






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

    def UpperCamelCase			(			self :      Optional[int]							,    snake_case__ :      Tuple    ):

     """simple docstring"""






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




    def UpperCamelCase			(			self :      Dict    ):

     """simple docstring"""






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

     SCREAMING_SNAKE_CASE								=			tokens + [tokenizer.unk_token]

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




from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
      if not (is_transformers_available() and is_torch_available()):
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      from ...utils.dummy_torch_and_transformers_objects import (
          ImageTextPipelineOutput,
          UniDiffuserPipeline,
      )
else:
      from .modeling_text_decoder import UniDiffuserTextDecoder
      from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
      from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline

