



import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig







class       _snake_case				(     __snake_case ):






   '''simple docstring'''






   A__      : int       =						CustomConfig


   def __init__(    self:     List[str]  ,lowerCamelCase_:     Dict							)	->      Tuple:
       super().__init__(lowerCamelCase_							)
       UpperCAmelCase_     :       List[str]  		=					torch.nn.Linear(config.hidden_size  ,config.hidden_size							)


   def       A__    (    self:     List[Any]  ,lowerCamelCase_:     Union[str, Any]							)	->      str:
       return self.linear(lowerCamelCase_							)






   def       A__    (    self:     int  ,lowerCamelCase_:     Dict							)	->      str:
       pass







class       _snake_case				(     __snake_case ):






   '''simple docstring'''






   A__      : str       =						NoSuperInitConfig


   def __init__(    self:     Any  ,lowerCamelCase_:     int							)	->      List[str]:
       super().__init__(lowerCamelCase_							)
       UpperCAmelCase_     :       Any  		=					torch.nn.Linear(config.attribute  ,config.attribute							)


   def       A__    (    self:     int  ,lowerCamelCase_:     int							)	->      List[str]:
       return self.linear(lowerCamelCase_							)






   def       A__    (    self:     Optional[Any]  ,lowerCamelCase_:     List[str]							)	->      str:
       pass







'''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,
)


UpperCAmelCase       :		Dict		=				{
    'configuration_marian': ['MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MarianConfig', 'MarianOnnxConfig'],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase       :		Tuple		=				['MarianTokenizer']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase       :		List[str]		=				[
       'MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST',
       'MarianForCausalLM',
       'MarianModel',
       'MarianMTModel',
       'MarianPreTrainedModel',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase       :		Any		=				['TFMarianModel', 'TFMarianMTModel', 'TFMarianPreTrainedModel']

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase       :		Optional[Any]		=				['FlaxMarianModel', 'FlaxMarianMTModel', 'FlaxMarianPreTrainedModel']

if TYPE_CHECKING:
   from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_marian import MarianTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_marian import (
          MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
          MarianForCausalLM,
          MarianModel,
          MarianMTModel,
          MarianPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
   import sys

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


