


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


_snake_case          =							logging.get_logger(__name__)

_snake_case          =							{
    "microsoft/swinv2-tiny-patch4-window8-256": (
        "https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"
    ),
}



class   _a      (      SCREAMING_SNAKE_CASE_ ):
    a_    :				Union[str, Any]             =    'swinv2'

    a_    :				Optional[int]             =    {
        'num_attention_heads': 'num_heads',
        'num_hidden_layers': 'num_layers',
    }
    def __init__( self							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					int=2_24							,					SCREAMING_SNAKE_CASE__							:					str=4							,					SCREAMING_SNAKE_CASE__							:					List[Any]=3							,					SCREAMING_SNAKE_CASE__							:					str=96							,					SCREAMING_SNAKE_CASE__							:					Dict=[2, 2, 6, 2]							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=[3, 6, 12, 24]							,					SCREAMING_SNAKE_CASE__							:					Tuple=7							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=4.0							,					SCREAMING_SNAKE_CASE__							:					List[str]=True							,					SCREAMING_SNAKE_CASE__							:					List[Any]=0.0							,					SCREAMING_SNAKE_CASE__							:					Optional[int]=0.0							,					SCREAMING_SNAKE_CASE__							:					Dict=0.1							,					SCREAMING_SNAKE_CASE__							:					Tuple="gelu"							,					SCREAMING_SNAKE_CASE__							:					Tuple=False							,					SCREAMING_SNAKE_CASE__							:					Any=0.02							,					SCREAMING_SNAKE_CASE__							:					List[Any]=1e-5							,					SCREAMING_SNAKE_CASE__							:					int=32							,					**SCREAMING_SNAKE_CASE__							:					List[str]							,					):
          super().__init__(**SCREAMING_SNAKE_CASE__				)

          lowerCamelCase__           =		image_size
          lowerCamelCase__           =		patch_size
          lowerCamelCase__           =		num_channels
          lowerCamelCase__           =		embed_dim
          lowerCamelCase__           =		depths
          lowerCamelCase__           =		len(SCREAMING_SNAKE_CASE__				)
          lowerCamelCase__           =		num_heads
          lowerCamelCase__           =		window_size
          lowerCamelCase__           =		mlp_ratio
          lowerCamelCase__           =		qkv_bias
          lowerCamelCase__           =		hidden_dropout_prob
          lowerCamelCase__           =		attention_probs_dropout_prob
          lowerCamelCase__           =		drop_path_rate
          lowerCamelCase__           =		hidden_act
          lowerCamelCase__           =		use_absolute_embeddings
          lowerCamelCase__           =		layer_norm_eps
          lowerCamelCase__           =		initializer_range
          lowerCamelCase__           =		encoder_stride
          # we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
          # this indicates the channel dimension after the last stage of the model
          lowerCamelCase__           =		int(embed_dim * 2 ** (len(SCREAMING_SNAKE_CASE__				) - 1)				)
          lowerCamelCase__           =		(0, 0, 0, 0)



