


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCamelCase				:  Optional[Any]      					=							{
    'configuration_mgp_str': ['MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MgpstrConfig'],
    'processing_mgp_str': ['MgpstrProcessor'],
    'tokenization_mgp_str': ['MgpstrTokenizer'],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase				:  str      					=							[
           'MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST',
           'MgpstrModel',
           'MgpstrPreTrainedModel',
           'MgpstrForSceneTextRecognition',
       ]

if TYPE_CHECKING:
       from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
       from .processing_mgp_str import MgpstrProcessor
       from .tokenization_mgp_str import MgpstrTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_mgp_str import (
                  MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
                  MgpstrForSceneTextRecognition,
                  MgpstrModel,
                  MgpstrPreTrainedModel,
              )
else:
       import sys

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






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


__UpperCamelCase				:  Any      					=							logging.get_logger(__name__)

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





class  lowerCAmelCase__(    snake_case__						):






    '''simple docstring'''





    A_  :     List[str]			= 'gpt_bigcode'
    A_  :     Optional[Any]			= ['past_key_values']
    A_  :     Optional[int]			= {
        'hidden_size': 'n_embd',
        'max_position_embeddings': 'n_positions',
        'num_attention_heads': 'n_head',
        'num_hidden_layers': 'n_layer',
    }





    def __init__(	self				:   int       ,   __snake_case				:   Dict=50_257       ,   __snake_case				:   List[str]=1_024       ,   __snake_case				:   Dict=768       ,   __snake_case				:   Optional[int]=12       ,   __snake_case				:   str=12       ,   __snake_case				:   List[str]=None       ,   __snake_case				:   List[str]="gelu_pytorch_tanh"       ,   __snake_case				:   Optional[Any]=0.1       ,   __snake_case				:   str=0.1       ,   __snake_case				:   Optional[Any]=0.1       ,   __snake_case				:   List[str]=1E-5       ,   __snake_case				:   Dict=0.02       ,   __snake_case				:   Optional[int]=True       ,   __snake_case				:   Tuple=True       ,   __snake_case				:   Optional[Any]=50_256       ,   __snake_case				:   Optional[Any]=50_256       ,   __snake_case				:   Optional[Any]=True       ,   __snake_case				:   Optional[Any]=True       ,   __snake_case				:   List[Any]=True       ,   **__snake_case				:   List[str]       ,   ):





       '''simple docstring'''
       UpperCAmelCase_							:      Any						=   vocab_size
       UpperCAmelCase_							:      int						=   n_positions
       UpperCAmelCase_							:      Any						=   n_embd
       UpperCAmelCase_							:      Union[str, Any]						=   n_layer
       UpperCAmelCase_							:      List[str]						=   n_head
       UpperCAmelCase_							:      List[Any]						=   n_inner
       UpperCAmelCase_							:      Optional[int]						=   activation_function
       UpperCAmelCase_							:      str						=   resid_pdrop
       UpperCAmelCase_							:      Optional[Any]						=   embd_pdrop
       UpperCAmelCase_							:      str						=   attn_pdrop
       UpperCAmelCase_							:      Any						=   layer_norm_epsilon
       UpperCAmelCase_							:      List[str]						=   initializer_range
       UpperCAmelCase_							:      Optional[int]						=   scale_attn_weights
       UpperCAmelCase_							:      Union[str, Any]						=   use_cache
       UpperCAmelCase_							:      Dict						=   attention_softmax_in_fpaa
       UpperCAmelCase_							:      Union[str, Any]						=   scale_attention_softmax_in_fpaa
       UpperCAmelCase_							:      Optional[int]						=   multi_query

       UpperCAmelCase_							:      Optional[Any]						=   bos_token_id
       UpperCAmelCase_							:      Tuple						=   eos_token_id

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