






'''simple docstring'''







from typing import TYPE_CHECKING

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


_A			:    Tuple					  ={'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XGLMConfig''']}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A			:    Dict					  =['''XGLMTokenizer''']

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A			:    Tuple					  =['''XGLMTokenizerFast''']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A			:    str					  =[
			    '''XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''XGLMForCausalLM''',
			    '''XGLMModel''',
			    '''XGLMPreTrainedModel''',
			]


try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A			:    List[str]					  =[
			    '''FlaxXGLMForCausalLM''',
			    '''FlaxXGLMModel''',
			    '''FlaxXGLMPreTrainedModel''',
			]


try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A			:    Optional[Any]					  =[
			    '''TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''TFXGLMForCausalLM''',
			    '''TFXGLMModel''',
			    '''TFXGLMPreTrainedModel''',
			]


if TYPE_CHECKING:
			from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_xglm import XGLMTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_xglm_fast import XGLMTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_xglm import (
						    TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFXGLMForCausalLM,
						    TFXGLMModel,
						    TFXGLMPreTrainedModel,
						)


else:
			import sys

			_A			:    Tuple					  =_LazyModule(__name__, globals()['''__file__'''], _import_structure)









'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


_A			:    Any					  ={
    '''configuration_trocr''': ['''TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TrOCRConfig'''],
    '''processing_trocr''': ['''TrOCRProcessor'''],
}


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A			:    str					  =[
			    '''TROCR_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''TrOCRForCausalLM''',
			    '''TrOCRPreTrainedModel''',
			]


if TYPE_CHECKING:
			from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
			from .processing_trocr import TrOCRProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
			import sys

			_A			:    Dict					  =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

