


"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case__		:     str    				=				{
    '''configuration_time_series_transformer''': [
        '''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''TimeSeriesTransformerConfig''',
    ],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__		:     Optional[int]    				=				[
     '''TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TimeSeriesTransformerForPrediction''',
     '''TimeSeriesTransformerModel''',
     '''TimeSeriesTransformerPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_time_series_transformer import (
     TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
     TimeSeriesTransformerConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_time_series_transformer import (
      TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TimeSeriesTransformerForPrediction,
      TimeSeriesTransformerModel,
      TimeSeriesTransformerPreTrainedModel,
  )

else:
 import sys

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






"""simple docstring"""





from torch import nn



class 		snake_case_(       nn.Module			):






     def __init__(	self  :					int					,				UpperCamelCase_  :					int					,				UpperCamelCase_  :					int				):
           super().__init__()
           lowerCAmelCase					:	str       =   class_size
           lowerCAmelCase					:	Dict       =   embed_size
           # self.mlp1 = nn.Linear(embed_size, embed_size)
           # self.mlp2 = (nn.Linear(embed_size, class_size))
           lowerCAmelCase					:	Any       =   nn.Linear(UpperCamelCase_					,				UpperCamelCase_				)






     def      lowerCamelCase__     (	self  :					List[Any]					,				UpperCamelCase_  :					Tuple				):
           # hidden_state = nn.functional.relu(self.mlp1(hidden_state))
           # hidden_state = self.mlp2(hidden_state)
           lowerCAmelCase					:	int       =   self.mlp(UpperCamelCase_				)
           return logits


