




"""simple docstring"""

import json
import os
from typing import Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__A       						=	logging.get_logger(__name__)

__A       						=	{"vocab_file": "vocab.json"}

__A       						=	{
    "vocab_file": {
        "mgp-str": "https://huggingface.co/alibaba-damo/mgp-str-base/blob/main/vocab.json",
    }
}

__A       						=	{"mgp-str": 27}
class 	lowerCamelCase__			(     lowerCamelCase_	):
			a__       :					Dict	    =   VOCAB_FILES_NAMES
			a__       :					Optional[int]	    =   PRETRAINED_VOCAB_FILES_MAP
			a__       :					List[Any]	    =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES


			def __init__(   self ,       SCREAMING_SNAKE_CASE ,       SCREAMING_SNAKE_CASE="[GO]" ,       SCREAMING_SNAKE_CASE="[GO]" ,       SCREAMING_SNAKE_CASE="[s]" ,       SCREAMING_SNAKE_CASE="[GO]" ,       **SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					super().__init__(
					    unk_token=_SCREAMING_SNAKE_CASE ,       bos_token=_SCREAMING_SNAKE_CASE ,       eos_token=_SCREAMING_SNAKE_CASE ,       pad_token=_SCREAMING_SNAKE_CASE ,       **_SCREAMING_SNAKE_CASE ,       )

					with open(_SCREAMING_SNAKE_CASE ,       encoding="utf-8"							) as vocab_handle:
							snake_case						:  str    	= json.load(_SCREAMING_SNAKE_CASE							)
					snake_case						:  Union[str, Any]    	= {v: k for k, v in self.vocab.items()}


			@property
			def 							lowerCamelCase_ (   self							):



					"""simple docstring"""







					return len(self.vocab							)


			def 							lowerCamelCase_ (   self							):



					"""simple docstring"""







					return dict(self.vocab ,       **self.added_tokens_encoder							)


			def 							lowerCamelCase_ (   self ,       SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					snake_case						:  str    	= []
					for s in text:
							char_tokens.extend(_SCREAMING_SNAKE_CASE							)
					return char_tokens


			def 							lowerCamelCase_ (   self ,       SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					return self.vocab.get(_SCREAMING_SNAKE_CASE ,       self.vocab.get(self.unk_token							)							)


			def 							lowerCamelCase_ (   self ,       SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					return self.decoder.get(_SCREAMING_SNAKE_CASE							)



			def 							lowerCamelCase_ (   self ,       SCREAMING_SNAKE_CASE ,       SCREAMING_SNAKE_CASE = None							):



					"""simple docstring"""







					if not os.path.isdir(_SCREAMING_SNAKE_CASE							):
							logger.error("Vocabulary path ({}) should be a directory".format(_SCREAMING_SNAKE_CASE							)							)
							return
					snake_case						:  Union[str, Any]    	= os.path.join(
					    _SCREAMING_SNAKE_CASE ,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)

					with open(_SCREAMING_SNAKE_CASE ,       "w" ,       encoding="utf-8"							) as f:
							f.write(json.dumps(self.vocab ,       indent=2 ,       sort_keys=_SCREAMING_SNAKE_CASE ,       ensure_ascii=_SCREAMING_SNAKE_CASE							) + "\n"							)

					return (vocab_file,)





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


UpperCamelCase								=	{
    """configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MobileViTConfig""", """MobileViTOnnxConfig"""],
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase								=	["""MobileViTFeatureExtractor"""]
     UpperCamelCase								=	["""MobileViTImageProcessor"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase								=	[
         """MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """MobileViTForImageClassification""",
         """MobileViTForSemanticSegmentation""",
         """MobileViTModel""",
         """MobileViTPreTrainedModel""",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase								=	[
         """TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """TFMobileViTForImageClassification""",
         """TFMobileViTForSemanticSegmentation""",
         """TFMobileViTModel""",
         """TFMobileViTPreTrainedModel""",
     ]

if TYPE_CHECKING:
     from .configuration_mobilevit import MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTConfig, MobileViTOnnxConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_mobilevit import MobileViTFeatureExtractor
          from .image_processing_mobilevit import MobileViTImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_mobilevit import (
              MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
              MobileViTForImageClassification,
              MobileViTForSemanticSegmentation,
              MobileViTModel,
              MobileViTPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_mobilevit import (
              TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFMobileViTForImageClassification,
              TFMobileViTForSemanticSegmentation,
              TFMobileViTModel,
              TFMobileViTPreTrainedModel,
          )


else:
     import sys

     UpperCamelCase								=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




