




class       A      :
     """simple docstring"""

     def __init__(     self	: Tuple						,	A__	: int      )					->							Dict:
           lowerCamelCase__   	=					data
           lowerCamelCase__   	=					42
           lowerCamelCase__   	=					42

def       lowerCAmelCase_      (	lowerCamelCase:							List[Any]    )       ->      Optional[int]:


      '''simple docstring'''




      lowerCamelCase__   	=					0
      lowerCamelCase__   	=					x

def       lowerCAmelCase_      (	lowerCamelCase:							Optional[int]  ,					lowerCamelCase:							List[str]    )       ->      Tuple:


      '''simple docstring'''




      lowerCamelCase__   	=					find_set(_UpperCAmelCase    ), find_set(_UpperCAmelCase    )
      if x == y:
            return

      elif x.rank > y.rank:
            lowerCamelCase__   	=					x
      else:
            lowerCamelCase__   	=					y
            if x.rank == y.rank:
                  y.rank += 1

def       lowerCAmelCase_      (	lowerCamelCase:							Optional[int]    )       ->      Union[str, Any]:


      '''simple docstring'''




      if x != x.parent:
            lowerCamelCase__   	=					find_set(x.parent    )
      return x.parent

def       lowerCAmelCase_      (	lowerCamelCase:							Any    )       ->      Dict:


      '''simple docstring'''




      lowerCamelCase__   	=					({0, 1, 2}, {3, 4, 5})
      for s in sets:
            if node.data in s:
                  return s
      lowerCamelCase__   	=					f"""{node.data} is not in {sets}"""
      raise ValueError(_UpperCAmelCase    )

def       lowerCAmelCase_      (	)       ->      Optional[int]:


      '''simple docstring'''




      lowerCamelCase__   	=					[Node(_UpperCAmelCase    ) for i in range(6    )]
      for v in vertex:
            make_set(_UpperCAmelCase    )

      union_set(vertex[0]  ,					vertex[1]    )
      union_set(vertex[1]  ,					vertex[2]    )
      union_set(vertex[3]  ,					vertex[4]    )
      union_set(vertex[3]  ,					vertex[5]    )

      for nodea in vertex:
            for nodea in vertex:
                  if find_python_set(_UpperCAmelCase    ).isdisjoint(find_python_set(_UpperCAmelCase    )    ):
                        assert find_set(_UpperCAmelCase    ) != find_set(_UpperCAmelCase    )
                  else:
                        assert find_set(_UpperCAmelCase    ) == find_set(_UpperCAmelCase    )


if __name__ == "__main__":
      test_disjoint_set()






'''simple docstring'''

from typing import TYPE_CHECKING

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


lowerCAmelCase__      :   Any      	=			{
    "configuration_open_llama": ["OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "OpenLlamaConfig"],
}

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

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

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase__      :   int      	=			[
			    "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

			lowerCAmelCase__      :   Dict      	=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




