from typing import TYPE_CHECKING

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


_lowerCamelCase					:   Optional[int]							=		{'''configuration_opt''': ['''OPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''OPTConfig''']}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowerCamelCase					:   int							=		[
					    '''OPT_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''OPTForCausalLM''',
					    '''OPTModel''',
					    '''OPTPreTrainedModel''',
					    '''OPTForSequenceClassification''',
					    '''OPTForQuestionAnswering''',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowerCamelCase					:   Union[str, Any]							=		['''TFOPTForCausalLM''', '''TFOPTModel''', '''TFOPTPreTrainedModel''']

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowerCamelCase					:   int							=		[
					    '''FlaxOPTForCausalLM''',
					    '''FlaxOPTModel''',
					    '''FlaxOPTPreTrainedModel''',
					]


if TYPE_CHECKING:
					from .configuration_opt import OPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OPTConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_opt import (
										    OPT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    OPTForCausalLM,
										    OPTForQuestionAnswering,
										    OPTForSequenceClassification,
										    OPTModel,
										    OPTPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel

else:
					import sys

					_lowerCamelCase					:   int							=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





from __future__ import annotations

from collections.abc import Iterator
from typing import Generic, TypeVar

_lowerCamelCase					:   Optional[Any]							=		TypeVar('''T''')


class 						lowercase    (     Generic[T]     ):




							def __init__(						self   :					Any	,							_UpperCamelCase   :					T      )					->				Any:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       data
												SCREAMING_SNAKE_CASE    			=       None





							def __str__(						self   :					Union[str, Any]      )					->				str:



												'''simple docstring'''

												return F"{self.data}"



class 						lowercase    (     Generic[T]     ):




							def __init__(						self   :					Optional[int]      )					->				None:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       None




							def __iter__(						self   :					str      )					->				Iterator[T]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.top
												while node:
																	yield node.data
																	SCREAMING_SNAKE_CASE    			=       node.next




							def __str__(						self   :					int      )					->				str:



												'''simple docstring'''

												return "->".join([str(_UpperCamelCase      ) for item in self]      )




							def __len__(						self   :					Tuple      )					->				int:



												'''simple docstring'''

												return len(tuple(iter(self      )      )      )




							def 	__snake_case(						self   :					Union[str, Any]      )					->				bool:



												'''simple docstring'''

												return self.top is None




							def 	__snake_case(						self   :					str	,							_UpperCamelCase   :					T      )					->				None:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       Node(_UpperCamelCase      )
												if not self.is_empty():
																	SCREAMING_SNAKE_CASE    			=       self.top
												SCREAMING_SNAKE_CASE    			=       node




							def 	__snake_case(						self   :					Union[str, Any]      )					->				T:



												'''simple docstring'''

												if self.is_empty():
																	raise IndexError("pop from empty stack"      )
												assert isinstance(self.top	,							_UpperCamelCase      )
												SCREAMING_SNAKE_CASE    			=       self.top
												SCREAMING_SNAKE_CASE    			=       self.top.next
												return pop_node.data




							def 	__snake_case(						self   :					Union[str, Any]      )					->				T:



												'''simple docstring'''

												if self.is_empty():
																	raise IndexError("peek from empty stack"      )

												assert self.top is not None
												return self.top.data





							def 	__snake_case(						self   :					Dict      )					->				None:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       None


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

							testmod()




