





'''simple docstring'''


from typing import TYPE_CHECKING

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


_lowerCamelCase					:						Optional[int]					     =							{'configuration_gptj': ['GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTJConfig', 'GPTJOnnxConfig']}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCamelCase					:						str					     =							[
				    'GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'GPTJForCausalLM',
				    'GPTJForQuestionAnswering',
				    'GPTJForSequenceClassification',
				    'GPTJModel',
				    'GPTJPreTrainedModel',
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCamelCase					:						Dict					     =							[
				    'TFGPTJForCausalLM',
				    'TFGPTJForQuestionAnswering',
				    'TFGPTJForSequenceClassification',
				    'TFGPTJModel',
				    'TFGPTJPreTrainedModel',
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCamelCase					:						List[str]					     =							[
				    'FlaxGPTJForCausalLM',
				    'FlaxGPTJModel',
				    'FlaxGPTJPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_gptj import GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTJConfig, GPTJOnnxConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_gptj import (
								    GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST,
								    GPTJForCausalLM,
								    GPTJForQuestionAnswering,
								    GPTJForSequenceClassification,
								    GPTJModel,
								    GPTJPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_gptj import (
								    TFGPTJForCausalLM,
								    TFGPTJForQuestionAnswering,
								    TFGPTJForSequenceClassification,
								    TFGPTJModel,
								    TFGPTJPreTrainedModel,
								)

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_gptj import FlaxGPTJForCausalLM, FlaxGPTJModel, FlaxGPTJPreTrainedModel

else:
				import sys

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








'''simple docstring'''


from typing import TYPE_CHECKING

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


_lowerCamelCase					:						Dict					     =							{
    'configuration_donut_swin': ['DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DonutSwinConfig'],
    'processing_donut': ['DonutProcessor'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCamelCase					:						List[str]					     =							[
				    'DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'DonutSwinModel',
				    'DonutSwinPreTrainedModel',
				]

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCamelCase					:						Any					     =							['DonutFeatureExtractor']
				_lowerCamelCase					:						Union[str, Any]					     =							['DonutImageProcessor']


if TYPE_CHECKING:
				from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
				from .processing_donut import DonutProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_donut_swin import (
								    DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
								    DonutSwinModel,
								    DonutSwinPreTrainedModel,
								)

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_donut import DonutFeatureExtractor
								from .image_processing_donut import DonutImageProcessor

else:
				import sys

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

