




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,
)


lowercase__				:      Optional[Any]	   = {
    "configuration_xlm_roberta": [
        "XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "XLMRobertaConfig",
        "XLMRobertaOnnxConfig",
    ],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__				:      Tuple	   = ["XLMRobertaTokenizer"]

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__				:      Tuple	   = ["XLMRobertaTokenizerFast"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__				:      Tuple	   = [
       "XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
       "XLMRobertaForCausalLM",
       "XLMRobertaForMaskedLM",
       "XLMRobertaForMultipleChoice",
       "XLMRobertaForQuestionAnswering",
       "XLMRobertaForSequenceClassification",
       "XLMRobertaForTokenClassification",
       "XLMRobertaModel",
       "XLMRobertaPreTrainedModel",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__				:      Dict	   = [
       "TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
       "TFXLMRobertaForCausalLM",
       "TFXLMRobertaForMaskedLM",
       "TFXLMRobertaForMultipleChoice",
       "TFXLMRobertaForQuestionAnswering",
       "TFXLMRobertaForSequenceClassification",
       "TFXLMRobertaForTokenClassification",
       "TFXLMRobertaModel",
       "TFXLMRobertaPreTrainedModel",
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__				:      int	   = [
       "FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
       "FlaxXLMRobertaForMaskedLM",
       "FlaxXLMRobertaForCausalLM",
       "FlaxXLMRobertaForMultipleChoice",
       "FlaxXLMRobertaForQuestionAnswering",
       "FlaxXLMRobertaForSequenceClassification",
       "FlaxXLMRobertaForTokenClassification",
       "FlaxXLMRobertaModel",
       "FlaxXLMRobertaPreTrainedModel",
   ]

if TYPE_CHECKING:
   from .configuration_xlm_roberta import (
       XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP,
       XLMRobertaConfig,
       XLMRobertaOnnxConfig,
   )

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_xlm_roberta import XLMRobertaTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_xlm_roberta_fast import XLMRobertaTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_xlm_roberta import (
          XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
          XLMRobertaForCausalLM,
          XLMRobertaForMaskedLM,
          XLMRobertaForMultipleChoice,
          XLMRobertaForQuestionAnswering,
          XLMRobertaForSequenceClassification,
          XLMRobertaForTokenClassification,
          XLMRobertaModel,
          XLMRobertaPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_xlm_roberta import (
          TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFXLMRobertaForCausalLM,
          TFXLMRobertaForMaskedLM,
          TFXLMRobertaForMultipleChoice,
          TFXLMRobertaForQuestionAnswering,
          TFXLMRobertaForSequenceClassification,
          TFXLMRobertaForTokenClassification,
          TFXLMRobertaModel,
          TFXLMRobertaPreTrainedModel,
      )

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_xlm_roberta import (
          FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
          FlaxXLMRobertaForCausalLM,
          FlaxXLMRobertaForMaskedLM,
          FlaxXLMRobertaForMultipleChoice,
          FlaxXLMRobertaForQuestionAnswering,
          FlaxXLMRobertaForSequenceClassification,
          FlaxXLMRobertaForTokenClassification,
          FlaxXLMRobertaModel,
          FlaxXLMRobertaPreTrainedModel,
      )

else:
   import sys

   lowercase__				:      Any	   = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)







lowercase__				:      Optional[int]	   = [
    "DownloadConfig",
    "DownloadManager",
    "DownloadMode",
    "StreamingDownloadManager",
]

from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager

