



'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


snake_case_			:     int  	=  {
    'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvNextConfig', 'ConvNextOnnxConfig']
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     List[Any]  	=  ['ConvNextFeatureExtractor']
					snake_case_			:     List[Any]  	=  ['ConvNextImageProcessor']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     Optional[Any]  	=  [
					    'CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'ConvNextForImageClassification',
					    'ConvNextModel',
					    'ConvNextPreTrainedModel',
					    'ConvNextBackbone',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     Tuple  	=  [
					    'TFConvNextForImageClassification',
					    'TFConvNextModel',
					    'TFConvNextPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_convnext import ConvNextFeatureExtractor
										from .image_processing_convnext import ConvNextImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_convnext import (
										    CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ConvNextBackbone,
										    ConvNextForImageClassification,
										    ConvNextModel,
										    ConvNextPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
					import sys

					snake_case_			:     List[Any]  	=  _LazyModule(__name__, globals()['__file__'], _import_structure)







'''simple docstring'''
from typing import TYPE_CHECKING

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


snake_case_			:     Any  	=  {
    'configuration_gpt_neox_japanese': ['GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoXJapaneseConfig'],
    'tokenization_gpt_neox_japanese': ['GPTNeoXJapaneseTokenizer'],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     Optional[int]  	=  [
					    'GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'GPTNeoXJapaneseForCausalLM',
					    'GPTNeoXJapaneseLayer',
					    'GPTNeoXJapaneseModel',
					    'GPTNeoXJapanesePreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
					from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_gpt_neox_japanese import (
										    GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GPTNeoXJapaneseForCausalLM,
										    GPTNeoXJapaneseLayer,
										    GPTNeoXJapaneseModel,
										    GPTNeoXJapanesePreTrainedModel,
										)


else:
					import sys

					snake_case_			:     Any  	=  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


