


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


__lowerCAmelCase		       =							logging.get_logger(__name__)

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





class   __a			(    _a      ):
 __lowercase :							Union[str, Any]        = 'gpt_bigcode'
 __lowercase :							List[str]        = ['past_key_values']
 __lowercase :							Dict        = {
     'hidden_size': 'n_embd',
     'max_position_embeddings': 'n_positions',
     'num_attention_heads': 'n_head',
     'num_hidden_layers': 'n_layer',
 }
 def __init__(   self				, lowerCAmelCase__=50_257				, lowerCAmelCase__=1_024				, lowerCAmelCase__=768				, lowerCAmelCase__=12				, lowerCAmelCase__=12				, lowerCAmelCase__=None				, lowerCAmelCase__="gelu_pytorch_tanh"				, lowerCAmelCase__=0.1				, lowerCAmelCase__=0.1				, lowerCAmelCase__=0.1				, lowerCAmelCase__=1E-5				, lowerCAmelCase__=0.0_2				, lowerCAmelCase__=True				, lowerCAmelCase__=True				, lowerCAmelCase__=50_256				, lowerCAmelCase__=50_256				, lowerCAmelCase__=True				, lowerCAmelCase__=True				, lowerCAmelCase__=True				, **lowerCAmelCase__				, )					->				Optional[Any]:




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

        lowercase__:   Optional[int]  			=   bos_token_id
        lowercase__:   int  			=   eos_token_id

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







'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__a          =		{
    "configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __a          =		[
           "TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TimesformerModel",
           "TimesformerForVideoClassification",
           "TimesformerPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_timesformer import (
                  TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TimesformerForVideoClassification,
                  TimesformerModel,
                  TimesformerPreTrainedModel,
              )

else:
       import sys

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