


"""simple docstring"""







from typing import TYPE_CHECKING

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


__lowercase    					=      {
    """configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconConfig"""],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowercase    					=      [
     """FALCON_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """FalconForCausalLM""",
     """FalconModel""",
     """FalconPreTrainedModel""",
     """FalconForSequenceClassification""",
     """FalconForTokenClassification""",
     """FalconForQuestionAnswering""",
 ]


if TYPE_CHECKING:
 from .configuration_falcon import FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP, FalconConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_falcon import (
      FALCON_PRETRAINED_MODEL_ARCHIVE_LIST,
      FalconForCausalLM,
      FalconForQuestionAnswering,
      FalconForSequenceClassification,
      FalconForTokenClassification,
      FalconModel,
      FalconPreTrainedModel,
  )


else:
 import sys

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







'''simple docstring'''





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


SCREAMING_SNAKE_CASE_:     Dict  =logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_:     Tuple  ={}




class        __A      ( UpperCamelCase__	):
    a__       :						int          =  """llama"""
    a__       :						Any          =  ["""past_key_values"""]



    def __init__(self    :    List[str]   ,			__a    :    List[str]=32000   ,			__a    :    Tuple=4096   ,			__a    :    List[Any]=11008   ,			__a    :    Dict=32   ,			__a    :    Tuple=32   ,			__a    :    Any=None   ,			__a    :    Any="silu"   ,			__a    :    List[Any]=2048   ,			__a    :    List[Any]=0.02   ,			__a    :    str=1E-6   ,			__a    :    Optional[Any]=True   ,			__a    :    Union[str, Any]=0   ,			__a    :    Any=1   ,			__a    :    Dict=2   ,			__a    :    Dict=1   ,			__a    :    str=False   ,			__a    :    str=None   ,			**__a    :    Optional[Any]   ,			):
         UpperCAmelCase_           =   vocab_size
         UpperCAmelCase_           =   max_position_embeddings
         UpperCAmelCase_           =   hidden_size
         UpperCAmelCase_           =   intermediate_size
         UpperCAmelCase_           =   num_hidden_layers
         UpperCAmelCase_           =   num_attention_heads

         # for backward compatibility
         if num_key_value_heads is None:
              UpperCAmelCase_           =   num_attention_heads

         UpperCAmelCase_           =   num_key_value_heads
         UpperCAmelCase_           =   hidden_act
         UpperCAmelCase_           =   initializer_range
         UpperCAmelCase_           =   rms_norm_eps
         UpperCAmelCase_           =   pretraining_tp
         UpperCAmelCase_           =   use_cache
         UpperCAmelCase_           =   rope_scaling
         self._rope_scaling_validation()

         super().__init__(
             pad_token_id=__a   ,			bos_token_id=__a   ,			eos_token_id=__a   ,			tie_word_embeddings=__a   ,			**__a   ,			)






    def 					_lowercase						(self    :    List[str] ):
         if self.rope_scaling is None:
              return

         if not isinstance(self.rope_scaling   ,			__a ) or len(self.rope_scaling ) != 2:
              raise ValueError(
                  "`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, "
                  f"""got {self.rope_scaling}""" )
         UpperCAmelCase_           =   self.rope_scaling.get("type"   ,			__a )
         UpperCAmelCase_           =   self.rope_scaling.get("factor"   ,			__a )
         if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
              raise ValueError(
                  f"""`rope_scaling`'s name field must be one of ['linear', 'dynamic'], got {rope_scaling_type}""" )
         if rope_scaling_factor is None or not isinstance(__a   ,			__a ) or rope_scaling_factor <= 1.0:
              raise ValueError(f"""`rope_scaling`'s factor field must be an float > 1, got {rope_scaling_factor}""" )




