


"""simple docstring"""
from typing import TYPE_CHECKING

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


UpperCAmelCase				=						{
    """configuration_bloom""": ["""BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BloomConfig""", """BloomOnnxConfig"""],
}
try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase				=						["""BloomTokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase				=						[
     """BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """BloomForCausalLM""",
     """BloomModel""",
     """BloomPreTrainedModel""",
     """BloomForSequenceClassification""",
     """BloomForTokenClassification""",
     """BloomForQuestionAnswering""",
 ]

if TYPE_CHECKING:
 from .configuration_bloom import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP, BloomConfig, BloomOnnxConfig

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_bloom_fast import BloomTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_bloom import (
      BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST,
      BloomForCausalLM,
      BloomForQuestionAnswering,
      BloomForSequenceClassification,
      BloomForTokenClassification,
      BloomModel,
      BloomPreTrainedModel,
  )

else:
 import sys

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





"""simple docstring"""
def 				_snake_case      (   __snake_case							:      list[list[int]]						, __snake_case							:      int						, __snake_case							:      int						, __snake_case							:      list[int]   ):




   """simple docstring"""







   if graph[path[curr_ind - 1]][next_ver] == 0:
      return False

   # 2. Validate that next vertex is not already in path
   return not any(vertex == next_ver for vertex in path   )

def 				_snake_case      (   __snake_case							:      list[list[int]]						, __snake_case							:      list[int]						, __snake_case							:      int   ):




   """simple docstring"""







   if curr_ind == len(__snake_case   ):
      # return whether path exists between current and starting vertices
      return graph[path[curr_ind - 1]][path[0]] == 1

   # Recursive Step
   for next_ver in range(0						, len(__snake_case   )   ):
      if valid_connection(__snake_case						, __snake_case						, __snake_case						, __snake_case   ):
         # Insert current vertex  into path as next transition
         _lowerCamelCase	:					List[str]   =		next_ver
         # Validate created path
         if util_hamilton_cycle(__snake_case						, __snake_case						, curr_ind + 1   ):
            return True
         # Backtrack
         _lowerCamelCase	:					Tuple   =		-1
   return False





def 				_snake_case      (   __snake_case							:      list[list[int]]						, __snake_case							:      int = 0   ):




   """simple docstring"""







   _lowerCamelCase	:					Any   =		[-1] * (len(__snake_case   ) + 1)
   # initialize start and end of path with starting index
   _lowerCamelCase	:					Optional[int]   =		start_index
   # evaluate and if we find answer return path either return empty array
   return path if util_hamilton_cycle(__snake_case						, __snake_case						, 1   ) else []

