


"""simple docstring"""


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


_snake_case          =							logging.get_logger(__name__)

_snake_case          =							{
    "bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}



class   _a      (      SCREAMING_SNAKE_CASE_ ):
    a_    :				Optional[int]             =    'gpt_bigcode'
    a_    :				str             =    ['past_key_values']
    a_    :				Union[str, Any]             =    {
        'hidden_size': 'n_embd',
        'max_position_embeddings': 'n_positions',
        'num_attention_heads': 'n_head',
        'num_hidden_layers': 'n_layer',
    }
    def __init__( self							:					Tuple							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=5_02_57							,					SCREAMING_SNAKE_CASE__							:					List[Any]=10_24							,					SCREAMING_SNAKE_CASE__							:					int=7_68							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]=12							,					SCREAMING_SNAKE_CASE__							:					int=12							,					SCREAMING_SNAKE_CASE__							:					List[str]=None							,					SCREAMING_SNAKE_CASE__							:					Tuple="gelu_pytorch_tanh"							,					SCREAMING_SNAKE_CASE__							:					Optional[int]=0.1							,					SCREAMING_SNAKE_CASE__							:					Tuple=0.1							,					SCREAMING_SNAKE_CASE__							:					List[str]=0.1							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]=1e-5							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]=0.02							,					SCREAMING_SNAKE_CASE__							:					Tuple=True							,					SCREAMING_SNAKE_CASE__							:					Dict=True							,					SCREAMING_SNAKE_CASE__							:					List[Any]=5_02_56							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]=5_02_56							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=True							,					SCREAMING_SNAKE_CASE__							:					Any=True							,					SCREAMING_SNAKE_CASE__							:					List[Any]=True							,					**SCREAMING_SNAKE_CASE__							:					Dict							,					):
          lowerCamelCase__           =		vocab_size
          lowerCamelCase__           =		n_positions
          lowerCamelCase__           =		n_embd
          lowerCamelCase__           =		n_layer
          lowerCamelCase__           =		n_head
          lowerCamelCase__           =		n_inner
          lowerCamelCase__           =		activation_function
          lowerCamelCase__           =		resid_pdrop
          lowerCamelCase__           =		embd_pdrop
          lowerCamelCase__           =		attn_pdrop
          lowerCamelCase__           =		layer_norm_epsilon
          lowerCamelCase__           =		initializer_range
          lowerCamelCase__           =		scale_attn_weights
          lowerCamelCase__           =		use_cache
          lowerCamelCase__           =		attention_softmax_in_fpaa
          lowerCamelCase__           =		scale_attention_softmax_in_fpaa
          lowerCamelCase__           =		multi_query

          lowerCamelCase__           =		bos_token_id
          lowerCamelCase__           =		eos_token_id

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







"""simple docstring"""


from typing import TYPE_CHECKING

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


_snake_case          =							{
    "configuration_blenderbot": [
        "BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlenderbotConfig",
        "BlenderbotOnnxConfig",
    ],
    "tokenization_blenderbot": ["BlenderbotTokenizer"],
}

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

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "BlenderbotForCausalLM",
       "BlenderbotForConditionalGeneration",
       "BlenderbotModel",
       "BlenderbotPreTrainedModel",
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "TFBlenderbotForConditionalGeneration",
       "TFBlenderbotModel",
       "TFBlenderbotPreTrainedModel",
   ]


try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "FlaxBlenderbotForConditionalGeneration",
       "FlaxBlenderbotModel",
       "FlaxBlenderbotPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_blenderbot import (
       BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       BlenderbotConfig,
       BlenderbotOnnxConfig,
   )
   from .tokenization_blenderbot import BlenderbotTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_blenderbot import (
          BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
          BlenderbotForCausalLM,
          BlenderbotForConditionalGeneration,
          BlenderbotModel,
          BlenderbotPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_blenderbot import (
          TFBlenderbotForConditionalGeneration,
          TFBlenderbotModel,
          TFBlenderbotPreTrainedModel,
      )

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_blenderbot import (
          FlaxBlenderbotForConditionalGeneration,
          FlaxBlenderbotModel,
          FlaxBlenderbotPreTrainedModel,
      )

else:
   import sys

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



