


from typing import TYPE_CHECKING

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


lowerCAmelCase					 =	{
    '''configuration_gpt2''': ['''GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPT2Config''', '''GPT2OnnxConfig'''],
    '''tokenization_gpt2''': ['''GPT2Tokenizer'''],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase					 =	['''GPT2TokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase					 =	[
	    '''GPT2_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''GPT2DoubleHeadsModel''',
	    '''GPT2ForQuestionAnswering''',
	    '''GPT2ForSequenceClassification''',
	    '''GPT2ForTokenClassification''',
	    '''GPT2LMHeadModel''',
	    '''GPT2Model''',
	    '''GPT2PreTrainedModel''',
	    '''load_tf_weights_in_gpt2''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase					 =	[
	    '''TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFGPT2DoubleHeadsModel''',
	    '''TFGPT2ForSequenceClassification''',
	    '''TFGPT2LMHeadModel''',
	    '''TFGPT2MainLayer''',
	    '''TFGPT2Model''',
	    '''TFGPT2PreTrainedModel''',
	]

try:
	if not is_keras_nlp_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase					 =	['''TFGPT2Tokenizer''']

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase					 =	['''FlaxGPT2LMHeadModel''', '''FlaxGPT2Model''', '''FlaxGPT2PreTrainedModel''']

if TYPE_CHECKING:
	from .configuration_gpta import GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTaConfig, GPTaOnnxConfig
	from .tokenization_gpta import GPTaTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_gpta_fast import GPTaTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_gpta import (
		    GPT2_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GPTaDoubleHeadsModel,
		    GPTaForQuestionAnswering,
		    GPTaForSequenceClassification,
		    GPTaForTokenClassification,
		    GPTaLMHeadModel,
		    GPTaModel,
		    GPTaPreTrainedModel,
		    load_tf_weights_in_gpta,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_gpta import (
		    TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFGPTaDoubleHeadsModel,
		    TFGPTaForSequenceClassification,
		    TFGPTaLMHeadModel,
		    TFGPTaMainLayer,
		    TFGPTaModel,
		    TFGPTaPreTrainedModel,
		)

	try:
		if not is_keras_nlp_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_gpta_tf import TFGPTaTokenizer

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_gpta import FlaxGPTaLMHeadModel, FlaxGPTaModel, FlaxGPTaPreTrainedModel

else:
	import sys

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










from __future__ import annotations

from enum import Enum





class    A					(     A_				):
							UpperCamelCase_     :							List[Any] =24
							UpperCamelCase_     :							List[Any] =21
							UpperCamelCase_     :							int =18
							UpperCamelCase_     :							Optional[int] =15
							UpperCamelCase_     :							Tuple =12
							UpperCamelCase_     :							List[str] =9
							UpperCamelCase_     :							Any =6
							UpperCamelCase_     :							List[str] =3
							UpperCamelCase_     :							str =2
							UpperCamelCase_     :							str =1
							UpperCamelCase_     :							Optional[int] =-1
							UpperCamelCase_     :							List[Any] =-2
							UpperCamelCase_     :							str =-3
							UpperCamelCase_     :							Tuple =-6
							UpperCamelCase_     :							Tuple =-9
							UpperCamelCase_     :							Optional[int] =-12
							UpperCamelCase_     :							str =-15
							UpperCamelCase_     :							Optional[Any] =-18
							UpperCamelCase_     :							Any =-21
							UpperCamelCase_     :							List[str] =-24





class    A					(     A_				):
							UpperCamelCase_     :							str =8
							UpperCamelCase_     :							Optional[Any] =7
							UpperCamelCase_     :							Tuple =6
							UpperCamelCase_     :							List[Any] =5
							UpperCamelCase_     :							Optional[Any] =4
							UpperCamelCase_     :							Union[str, Any] =3
							UpperCamelCase_     :							Union[str, Any] =2
							UpperCamelCase_     :							int =1







def  _lowerCamelCase(			lowercase__     ,				lowercase__     ,				lowercase__     ,				)		->			float:

		'''simple docstring'''







		if isinstance(lowercase__     ,				lowercase__			):
				__lowercase=    SIUnit[known_prefix.lower()]
		if isinstance(lowercase__     ,				lowercase__			):
				__lowercase=    SIUnit[unknown_prefix.lower()]
		__lowercase=    known_amount * (
		    1_0 ** (known_prefix.value - unknown_prefix.value)
		)
		return unknown_amount







def  _lowerCamelCase(			lowercase__     ,				lowercase__     ,				lowercase__     ,				)		->			float:

		'''simple docstring'''







		if isinstance(lowercase__     ,				lowercase__			):
				__lowercase=    BinaryUnit[known_prefix.lower()]
		if isinstance(lowercase__     ,				lowercase__			):
				__lowercase=    BinaryUnit[unknown_prefix.lower()]
		__lowercase=    known_amount * (
		    2 ** ((known_prefix.value - unknown_prefix.value) * 1_0)
		)
		return unknown_amount


if __name__ == "__main__":
	import doctest

	doctest.testmod()






