

from typing import TYPE_CHECKING

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


lowerCAmelCase_       	=	{
    '''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LlamaConfig'''],
}

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

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

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_       	=	[
					    '''LlamaForCausalLM''',
					    '''LlamaModel''',
					    '''LlamaPreTrainedModel''',
					    '''LlamaForSequenceClassification''',
					]


if TYPE_CHECKING:
					from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

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

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

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
					import sys

					lowerCAmelCase_       	=	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


from collections import deque

from .hash_table import HashTable





class 	snake_case_   (		__A					):







			'''simple docstring'''

			def __init__(     self :				int							,   *_UpperCamelCase :				int							,   **_UpperCamelCase :				Tuple							)      ->Tuple:
									super().__init__(*_UpperCamelCase							,   **_UpperCamelCase							)







			def 				snake_case__(     self :				Dict							,   _UpperCamelCase :				List[str]							,   _UpperCamelCase :				Dict							)      ->Tuple:
									snake_case_   =	deque([]							) if self.values[key] is None else self.values[key]
									self.values[key].appendleft(_UpperCamelCase							)
									snake_case_   =	self.values[key]







			def 				snake_case__(     self :				List[Any]							)      ->str:
									return (
									    sum(self.charge_factor - len(_UpperCamelCase							) for slot in self.values							)
									    / self.size_table
									    * self.charge_factor
									)







			def 				snake_case__(     self :				Dict							,   _UpperCamelCase :				Union[str, Any]							,   _UpperCamelCase :				Optional[int]=None							)      ->str:
									if not (
									    len(self.values[key]							) == self.charge_factor and self.values.count(_UpperCamelCase							) == 0
									):
															return key
									return super()._collision_resolution(_UpperCamelCase							,   _UpperCamelCase							)