
from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__   :			str												=    {
    "configuration_gpt_neo": ["GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoConfig", "GPTNeoOnnxConfig"],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__   :			Tuple												=    [
					    "GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "GPTNeoForCausalLM",
					    "GPTNeoForQuestionAnswering",
					    "GPTNeoForSequenceClassification",
					    "GPTNeoForTokenClassification",
					    "GPTNeoModel",
					    "GPTNeoPreTrainedModel",
					    "load_tf_weights_in_gpt_neo",
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__   :			Union[str, Any]												=    [
					    "FlaxGPTNeoForCausalLM",
					    "FlaxGPTNeoModel",
					    "FlaxGPTNeoPreTrainedModel",
					]


if TYPE_CHECKING:
					from .configuration_gpt_neo import GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoConfig, GPTNeoOnnxConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_gpt_neo import (
										    GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GPTNeoForCausalLM,
										    GPTNeoForQuestionAnswering,
										    GPTNeoForSequenceClassification,
										    GPTNeoForTokenClassification,
										    GPTNeoModel,
										    GPTNeoPreTrainedModel,
										    load_tf_weights_in_gpt_neo,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_gpt_neo import FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel


else:
					import sys

					SCREAMING_SNAKE_CASE__   :			int												=    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





from abc import ABC, abstractmethod
from argparse import ArgumentParser

class    lowerCAmelCase__     (	__lowercase			):






		@staticmethod
		@abstractmethod
		def  __A       (		SCREAMING_SNAKE_CASE__		:							ArgumentParser  )     ->							str:
						raise NotImplementedError()







		@abstractmethod
		def  __A       (		self		:							Optional[int]  )     ->							Union[str, Any]:
						raise NotImplementedError()



