
from typing import TYPE_CHECKING

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


__UpperCAmelCase   						=     {
    "configuration_xlm_prophetnet": ["XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMProphetNetConfig"],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __UpperCAmelCase   						=     ["XLMProphetNetTokenizer"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __UpperCAmelCase   						=     [
       "XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST",
       "XLMProphetNetDecoder",
       "XLMProphetNetEncoder",
       "XLMProphetNetForCausalLM",
       "XLMProphetNetForConditionalGeneration",
       "XLMProphetNetModel",
       "XLMProphetNetPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_xlm_prophetnet import (
          XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
          XLMProphetNetDecoder,
          XLMProphetNetEncoder,
          XLMProphetNetForCausalLM,
          XLMProphetNetForConditionalGeneration,
          XLMProphetNetModel,
          XLMProphetNetPreTrainedModel,
      )

else:
   import sys

   __UpperCAmelCase   						=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




from typing import TYPE_CHECKING

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


__UpperCAmelCase   						=     {
    "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:
   __UpperCAmelCase   						=     [
       "DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
       "DonutSwinModel",
       "DonutSwinPreTrainedModel",
   ]

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __UpperCAmelCase   						=     ["DonutFeatureExtractor"]
   __UpperCAmelCase   						=     ["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

   __UpperCAmelCase   						=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


