

'''simple docstring'''

# Lint as: python3
import itertools
import os
import re


lowercase__			    =			re.compile(r"([A-Z]+)([A-Z][a-z])")
lowercase__			    =			re.compile(r"([a-z\d])([A-Z])")

lowercase__			    =			re.compile(r"(?<!_)_(?!_)")
lowercase__			    =			re.compile(r"(_{2,})")

lowercase__			    =			r"^\w+(\.\w+)*$"

lowercase__			    =			r"<>:/\|?*"




def       UpperCamelCase(     UpperCAmelCase_	):
 UpperCAmelCase       :	Any											= _uppercase_uppercase_re.sub(R'\1_\2'  ,       UpperCAmelCase_	)
 UpperCAmelCase       :	Optional[int]											= _lowercase_uppercase_re.sub(R'\1_\2'  ,       UpperCAmelCase_	)
 return name.lower()




def       UpperCamelCase(     UpperCAmelCase_	):
 UpperCAmelCase       :	List[Any]											= _single_underscore_re.split(UpperCAmelCase_	)
 UpperCAmelCase       :	Dict											= [_multiple_underscores_re.split(UpperCAmelCase_	) for n in name]
 return "".join(n.capitalize() for n in itertools.chain.from_iterable(UpperCAmelCase_	) if n != ''	)




def       UpperCamelCase(     UpperCAmelCase_	):
 if os.path.basename(UpperCAmelCase_	) != name:
  raise ValueError(F"""Should be a dataset name, not a path: {name}"""	)
 return camelcase_to_snakecase(UpperCAmelCase_	)




def       UpperCamelCase(     UpperCAmelCase_  ,       UpperCAmelCase_	):
 if os.path.basename(UpperCAmelCase_	) != name:
  raise ValueError(F"""Should be a dataset name, not a path: {name}"""	)
 if not re.match(_split_re  ,       UpperCAmelCase_	):
  raise ValueError(F"""Split name should match '{_split_re}'' but got '{split}'."""	)
 return F"""{filename_prefix_for_name(UpperCAmelCase_	)}-{split}"""




def       UpperCamelCase(     UpperCAmelCase_  ,       UpperCAmelCase_  ,       UpperCAmelCase_  ,       UpperCAmelCase_=None	):
 UpperCAmelCase       :	Union[str, Any]											= filename_prefix_for_split(UpperCAmelCase_  ,       UpperCAmelCase_	)
 if filetype_suffix:
  prefix += F""".{filetype_suffix}"""
 UpperCAmelCase       :	int											= os.path.join(UpperCAmelCase_  ,       UpperCAmelCase_	)
 return F"""{filepath}*"""




def       UpperCamelCase(     UpperCAmelCase_  ,       UpperCAmelCase_  ,       UpperCAmelCase_  ,       UpperCAmelCase_=None  ,       UpperCAmelCase_=None	):
 UpperCAmelCase       :	int											= filename_prefix_for_split(UpperCAmelCase_  ,       UpperCAmelCase_	)
 UpperCAmelCase       :	str											= os.path.join(UpperCAmelCase_  ,       UpperCAmelCase_	)

 if shard_lengths:
  UpperCAmelCase       :	Optional[Any]											= len(UpperCAmelCase_	)
  UpperCAmelCase       :	List[str]											= [F"""{prefix}-{shard_id:05d}-of-{num_shards:05d}""" for shard_id in range(UpperCAmelCase_	)]
  if filetype_suffix:
   UpperCAmelCase       :	str											= [filename + F""".{filetype_suffix}""" for filename in filenames]
  return filenames
 else:
  UpperCAmelCase       :	Optional[Any]											= prefix
  if filetype_suffix:
   filename += F""".{filetype_suffix}"""
  return [filename]










from typing import TYPE_CHECKING

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


_UpperCAmelCase		:  List[str]	=   {
    "configuration_blenderbot": [
        "BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlenderbotConfig",
        "BlenderbotOnnxConfig",
    ],
    "tokenization_blenderbot": ["BlenderbotTokenizer"],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  Optional[int]	=   ["BlenderbotTokenizerFast"]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  int	=   [
         "BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "BlenderbotForCausalLM",
         "BlenderbotForConditionalGeneration",
         "BlenderbotModel",
         "BlenderbotPreTrainedModel",
     ]


try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  Any	=   [
         "TFBlenderbotForConditionalGeneration",
         "TFBlenderbotModel",
         "TFBlenderbotPreTrainedModel",
     ]


try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  Optional[int]	=   [
         "FlaxBlenderbotForConditionalGeneration",
         "FlaxBlenderbotModel",
         "FlaxBlenderbotPreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_blenderbot import (
         BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
         BlenderbotConfig,
         BlenderbotOnnxConfig,
     )
     from .tokenization_blenderbot import BlenderbotTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_blenderbot import (
              BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
              BlenderbotForCausalLM,
              BlenderbotForConditionalGeneration,
              BlenderbotModel,
              BlenderbotPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_blenderbot import (
              TFBlenderbotForConditionalGeneration,
              TFBlenderbotModel,
              TFBlenderbotPreTrainedModel,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_blenderbot import (
              FlaxBlenderbotForConditionalGeneration,
              FlaxBlenderbotModel,
              FlaxBlenderbotPreTrainedModel,
          )

else:
     import sys

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



