



'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


a_					= {
    'configuration_bloom': ['BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BloomConfig', 'BloomOnnxConfig'],
}
try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_					= ['BloomTokenizerFast']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_					= [
      'BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST',
      'BloomForCausalLM',
      'BloomModel',
      'BloomPreTrainedModel',
      'BloomForSequenceClassification',
      'BloomForTokenClassification',
      'BloomForQuestionAnswering',
  ]

if TYPE_CHECKING:
  from .configuration_bloom import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP, BloomConfig, BloomOnnxConfig

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_bloom_fast import BloomTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_bloom import (
        BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST,
        BloomForCausalLM,
        BloomForQuestionAnswering,
        BloomForSequenceClassification,
        BloomForTokenClassification,
        BloomModel,
        BloomPreTrainedModel,
    )

else:
  import sys

  a_					= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_					= logging.get_logger(__name__)

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






class      __SCREAMING_SNAKE_CASE      (			lowerCamelCase				):
 snake_case_  							=							"""gpt_bigcode"""
 snake_case_  							=							["""past_key_values"""]
 snake_case_  							=							{
     """hidden_size""": """n_embd""",
     """max_position_embeddings""": """n_positions""",
     """num_attention_heads""": """n_head""",
     """num_hidden_layers""": """n_layer""",
 }




 def __init__(      self	:							Any					,      __lowercase	:							Any=5_02_57					,      __lowercase	:							int=10_24					,      __lowercase	:							List[str]=7_68					,      __lowercase	:							Optional[int]=12					,      __lowercase	:							Dict=12					,      __lowercase	:							List[str]=None					,      __lowercase	:							int="gelu_pytorch_tanh"					,      __lowercase	:							Union[str, Any]=0.1					,      __lowercase	:							Optional[int]=0.1					,      __lowercase	:							Optional[int]=0.1					,      __lowercase	:							Optional[Any]=1e-5					,      __lowercase	:							List[str]=0.02					,      __lowercase	:							Tuple=True					,      __lowercase	:							Optional[Any]=True					,      __lowercase	:							Union[str, Any]=5_02_56					,      __lowercase	:							List[Any]=5_02_56					,      __lowercase	:							Union[str, Any]=True					,      __lowercase	:							List[str]=True					,      __lowercase	:							Dict=True					,      **__lowercase	:							List[Any]					,      )	->						Optional[int]:
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=vocab_size
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=n_positions
       SCREAMING_SNAKE_CASE__     :				Dict									=n_embd
       SCREAMING_SNAKE_CASE__     :				Dict									=n_layer
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=n_head
       SCREAMING_SNAKE_CASE__     :				List[str]									=n_inner
       SCREAMING_SNAKE_CASE__     :				List[str]									=activation_function
       SCREAMING_SNAKE_CASE__     :				List[Any]									=resid_pdrop
       SCREAMING_SNAKE_CASE__     :				List[Any]									=embd_pdrop
       SCREAMING_SNAKE_CASE__     :				List[str]									=attn_pdrop
       SCREAMING_SNAKE_CASE__     :				Dict									=layer_norm_epsilon
       SCREAMING_SNAKE_CASE__     :				List[str]									=initializer_range
       SCREAMING_SNAKE_CASE__     :				List[Any]									=scale_attn_weights
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=use_cache
       SCREAMING_SNAKE_CASE__     :				Dict									=attention_softmax_in_fpaa
       SCREAMING_SNAKE_CASE__     :				int									=scale_attention_softmax_in_fpaa
       SCREAMING_SNAKE_CASE__     :				Dict									=multi_query

       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=bos_token_id
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=eos_token_id

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