
'''simple docstring'''






import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin

class 			UpperCAmelCase__    (							A    ,						unittest.TestCase			):
    lowerCAmelCase_					     =		BlenderbotSmallTokenizer
    lowerCAmelCase_					     =		False



    def 	lowerCamelCase_	(						self   :							int  ):
          super().setUp()

          _lowerCamelCase					: Tuple		    = ["__start__", "adapt", "act", "ap@@", "te", "__end__", "__unk__"]
          _lowerCamelCase					: int		    = dict(zip(__A,range(len(__A  )  )  )  )

          _lowerCamelCase					: Any		    = ["#version: 0.2", "a p", "t e</w>", "ap t</w>", "a d", "ad apt</w>", "a c", "ac t</w>", ""]
          _lowerCamelCase					: List[str]		    = {"unk_token": "__unk__", "bos_token": "__start__", "eos_token": "__end__"}

          _lowerCamelCase					: List[Any]		    = os.path.join(self.tmpdirname,VOCAB_FILES_NAMES["vocab_file"]  )
          _lowerCamelCase					: List[Any]		    = 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(__A  ) + "\n"  )
          with open(self.merges_file,"w",encoding="utf-8"  ) as fp:
                fp.write("\n".join(__A  )  )



    def 	lowerCamelCase_	(						self   :							Tuple,**__A   :							Tuple  ):
          kwargs.update(self.special_tokens_map  )
          return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname,**__A  )



    def 	lowerCamelCase_	(						self   :							List[Any],__A   :							List[str]  ):
          _lowerCamelCase					: Optional[Any]		    = "adapt act apte"
          _lowerCamelCase					: Optional[Any]		    = "adapt act apte"
          return input_text, output_text



    def 	lowerCamelCase_	(						self   :							List[Any]  ):
          _lowerCamelCase					: int		    = BlenderbotSmallTokenizer(self.vocab_file,self.merges_file,**self.special_tokens_map  )
          _lowerCamelCase					: Optional[Any]		    = "adapt act apte"
          _lowerCamelCase					: Union[str, Any]		    = ["adapt", "act", "ap@@", "te"]
          _lowerCamelCase					: Tuple		    = tokenizer.tokenize(__A  )
          self.assertListEqual(__A,__A  )

          _lowerCamelCase					: List[str]		    = [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

          _lowerCamelCase					: Union[str, Any]		    = [0, 1, 2, 3, 4, 5]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(__A  ),__A  )



    def 	lowerCamelCase_	(						self   :							List[str]  ):
          _lowerCamelCase					: Optional[Any]		    = BlenderbotSmallTokenizer.from_pretrained("facebook/blenderbot-90M"  )
          assert tok("sam"  ).input_ids == [1_3_8_4]
          _lowerCamelCase					: Optional[int]		    = "I am a small frog."
          _lowerCamelCase					: Optional[int]		    = tok([src_text],padding=__A,truncation=__A  )["input_ids"]
          _lowerCamelCase					: List[str]		    = tok.batch_decode(__A,skip_special_tokens=__A,clean_up_tokenization_spaces=__A  )[0]
          assert src_text != decoded  # I wish it did!
          assert decoded == "i am a small frog ."



    def 	lowerCamelCase_	(						self   :							Any  ):
          _lowerCamelCase					: List[Any]		    = BlenderbotSmallTokenizer.from_pretrained("facebook/blenderbot-90M"  )
          _lowerCamelCase					: Dict		    = "I am a small frog ."
          _lowerCamelCase					: int		    = "."
          _lowerCamelCase					: Tuple		    = tok(__A  )["input_ids"]
          _lowerCamelCase					: int		    = tok(__A  )["input_ids"]

          assert encoded[-1] == encoded_dot[0]
"""simple docstring"""






from typing import TYPE_CHECKING

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


__lowerCAmelCase       :			Optional[int]   	={
    """configuration_chinese_clip""": [
        """CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ChineseCLIPConfig""",
        """ChineseCLIPOnnxConfig""",
        """ChineseCLIPTextConfig""",
        """ChineseCLIPVisionConfig""",
    ],
    """processing_chinese_clip""": ["""ChineseCLIPProcessor"""],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCAmelCase       :			List[Any]   	=["""ChineseCLIPFeatureExtractor"""]
       __lowerCAmelCase       :			List[Any]   	=["""ChineseCLIPImageProcessor"""]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCAmelCase       :			Tuple   	=[
           """CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """ChineseCLIPModel""",
           """ChineseCLIPPreTrainedModel""",
           """ChineseCLIPTextModel""",
           """ChineseCLIPVisionModel""",
       ]

if TYPE_CHECKING:
       from .configuration_chinese_clip import (
           CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
           ChineseCLIPConfig,
           ChineseCLIPOnnxConfig,
           ChineseCLIPTextConfig,
           ChineseCLIPVisionConfig,
       )
       from .processing_chinese_clip import ChineseCLIPProcessor

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_chinese_clip import (
                  CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ChineseCLIPModel,
                  ChineseCLIPPreTrainedModel,
                  ChineseCLIPTextModel,
                  ChineseCLIPVisionModel,
              )

else:
       import sys

       __lowerCAmelCase       :			Optional[Any]   	=_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



