




from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase_					    = logging.get_logger(__name__)

lowerCAmelCase_					    = {
    """edbeeching/decision-transformer-gym-hopper-medium""": (
        """https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json"""
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}






class  _lowerCAmelCase     (  _lowercase	):
      A__		     =		'decision_transformer'
      A__		     =		['past_key_values']
      A__		     =		{
          'max_position_embeddings': 'n_positions',
          'num_attention_heads': 'n_head',
          'num_hidden_layers': 'n_layer',
      }

      def __init__(   self      ,				__UpperCAmelCase=17      ,				__UpperCAmelCase=4      ,				__UpperCAmelCase=128      ,				__UpperCAmelCase=4096      ,				__UpperCAmelCase=True      ,				__UpperCAmelCase=1      ,				__UpperCAmelCase=1024      ,				__UpperCAmelCase=3      ,				__UpperCAmelCase=1      ,				__UpperCAmelCase=None      ,				__UpperCAmelCase="relu"      ,				__UpperCAmelCase=0.1      ,				__UpperCAmelCase=0.1      ,				__UpperCAmelCase=0.1      ,				__UpperCAmelCase=1e-5      ,				__UpperCAmelCase=0.02      ,				__UpperCAmelCase=True      ,				__UpperCAmelCase=True      ,				__UpperCAmelCase=5_0256      ,				__UpperCAmelCase=5_0256      ,				__UpperCAmelCase=False      ,				__UpperCAmelCase=False      ,				**__UpperCAmelCase      ,				):
        lowerCAmelCase__				:  Dict		       =     state_dim
        lowerCAmelCase__				:  Tuple		       =     act_dim
        lowerCAmelCase__				:  Optional[int]		       =     hidden_size
        lowerCAmelCase__				:  Optional[int]		       =     max_ep_len
        lowerCAmelCase__				:  Dict		       =     action_tanh
        lowerCAmelCase__				:  List[str]		       =     vocab_size
        lowerCAmelCase__				:  Any		       =     n_positions
        lowerCAmelCase__				:  int		       =     n_layer
        lowerCAmelCase__				:  List[str]		       =     n_head
        lowerCAmelCase__				:  Optional[Any]		       =     n_inner
        lowerCAmelCase__				:  Any		       =     activation_function
        lowerCAmelCase__				:  str		       =     resid_pdrop
        lowerCAmelCase__				:  Optional[int]		       =     embd_pdrop
        lowerCAmelCase__				:  Any		       =     attn_pdrop
        lowerCAmelCase__				:  Optional[Any]		       =     layer_norm_epsilon
        lowerCAmelCase__				:  str		       =     initializer_range
        lowerCAmelCase__				:  Dict		       =     scale_attn_weights
        lowerCAmelCase__				:  Tuple		       =     use_cache
        lowerCAmelCase__				:  str		       =     scale_attn_by_inverse_layer_idx
        lowerCAmelCase__				:  Optional[Any]		       =     reorder_and_upcast_attn

        lowerCAmelCase__				:  Any		       =     bos_token_id
        lowerCAmelCase__				:  Tuple		       =     eos_token_id

        super().__init__(bos_token_id=__UpperCAmelCase      ,				eos_token_id=__UpperCAmelCase      ,				**__UpperCAmelCase		)






from typing import TYPE_CHECKING

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


lowerCAmelCase_					    = {
    """configuration_longformer""": [
        """LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """LongformerConfig""",
        """LongformerOnnxConfig""",
    ],
    """tokenization_longformer""": ["""LongformerTokenizer"""],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase_					    = ["""LongformerTokenizerFast"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase_					    = [
         """LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """LongformerForMaskedLM""",
         """LongformerForMultipleChoice""",
         """LongformerForQuestionAnswering""",
         """LongformerForSequenceClassification""",
         """LongformerForTokenClassification""",
         """LongformerModel""",
         """LongformerPreTrainedModel""",
         """LongformerSelfAttention""",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase_					    = [
         """TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """TFLongformerForMaskedLM""",
         """TFLongformerForMultipleChoice""",
         """TFLongformerForQuestionAnswering""",
         """TFLongformerForSequenceClassification""",
         """TFLongformerForTokenClassification""",
         """TFLongformerModel""",
         """TFLongformerPreTrainedModel""",
         """TFLongformerSelfAttention""",
     ]


if TYPE_CHECKING:
     from .configuration_longformer import (
         LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
         LongformerConfig,
         LongformerOnnxConfig,
     )
     from .tokenization_longformer import LongformerTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_longformer_fast import LongformerTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_longformer import (
              LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              LongformerForMaskedLM,
              LongformerForMultipleChoice,
              LongformerForQuestionAnswering,
              LongformerForSequenceClassification,
              LongformerForTokenClassification,
              LongformerModel,
              LongformerPreTrainedModel,
              LongformerSelfAttention,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_longformer import (
              TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFLongformerForMaskedLM,
              TFLongformerForMultipleChoice,
              TFLongformerForQuestionAnswering,
              TFLongformerForSequenceClassification,
              TFLongformerForTokenClassification,
              TFLongformerModel,
              TFLongformerPreTrainedModel,
              TFLongformerSelfAttention,
          )

else:
     import sys

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

