from .stack import Stack
def 				__lowercase	(						lowerCamelCase__					)				->bool:

  '''simple docstring'''




  a__     		=     Stack()
  a__     		=     {"(": ")", "[": "]", "{": "}"}
  for bracket in parentheses:
    if bracket in bracket_pairs:
      stack.push(lowerCamelCase__					)
    elif bracket in (")", "]", "}"):
      if stack.is_empty() or bracket_pairs[stack.pop()] != bracket:
        return False
  return stack.is_empty()


if __name__ == "__main__":
     from doctest import testmod

     testmod()

     _SCREAMING_SNAKE_CASE   						=    ["""((()))""", """((())""", """(()))"""]
     print("""Balanced parentheses demonstration:\n""")
     for example in examples:
          _SCREAMING_SNAKE_CASE   						=    """""" if balanced_parentheses(example) else """not """
          print(F"""{example} is {not_str}balanced""")


from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE   						=    {
    """configuration_open_llama""": ["""OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """OpenLlamaConfig"""],
}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE   						=    ["""LlamaTokenizer"""]

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE   						=    ["""LlamaTokenizerFast"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE   						=    [
         """OpenLlamaForCausalLM""",
         """OpenLlamaModel""",
         """OpenLlamaPreTrainedModel""",
         """OpenLlamaForSequenceClassification""",
     ]


if TYPE_CHECKING:
     from .configuration_open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from transformers import LlamaTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from transformers import LlamaTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_open_llama import (
              OpenLlamaForCausalLM,
              OpenLlamaForSequenceClassification,
              OpenLlamaModel,
              OpenLlamaPreTrainedModel,
          )


else:
     import sys

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

