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


__magic_name__           =					logging.get_logger(__name__)

__magic_name__           =					{
    '''uw-madison/nystromformer-512''': '''https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json''',
    # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
}




class    _SCREAMING_SNAKE_CASE					( __UpperCamelCase	):
      _A  :						Optional[Any]      		=       'nystromformer'
      def __init__(     self						,		lowerCamelCase=3_00_00						,		lowerCamelCase=7_68						,		lowerCamelCase=12						,		lowerCamelCase=12						,		lowerCamelCase=30_72						,		lowerCamelCase="gelu_new"						,		lowerCamelCase=0.1						,		lowerCamelCase=0.1						,		lowerCamelCase=5_10						,		lowerCamelCase=2						,		lowerCamelCase=64						,		lowerCamelCase=64						,		lowerCamelCase=65						,		lowerCamelCase=False						,		lowerCamelCase=0.0_2						,		lowerCamelCase=1e-5						,		lowerCamelCase=1						,		lowerCamelCase=0						,		lowerCamelCase=2						,		**lowerCamelCase						,		):
          snake_case__  =			vocab_size
          snake_case__  =			max_position_embeddings
          snake_case__  =			hidden_size
          snake_case__  =			num_hidden_layers
          snake_case__  =			num_attention_heads
          snake_case__  =			intermediate_size
          snake_case__  =			hidden_act
          snake_case__  =			hidden_dropout_prob
          snake_case__  =			attention_probs_dropout_prob
          snake_case__  =			initializer_range
          snake_case__  =			type_vocab_size
          snake_case__  =			segment_means_seq_len
          snake_case__  =			num_landmarks
          snake_case__  =			conv_kernel_size
          snake_case__  =			inv_coeff_init_option
          snake_case__  =			layer_norm_eps
          super().__init__(pad_token_id=lowerCamelCase						,		bos_token_id=lowerCamelCase						,		eos_token_id=lowerCamelCase						,		**lowerCamelCase	)





from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__magic_name__           =					logging.get_logger(__name__)

__magic_name__           =					{
    '''MBZUAI/swiftformer-xs''': '''https://huggingface.co/MBZUAI/swiftformer-xs/resolve/main/config.json''',
}




class    _SCREAMING_SNAKE_CASE					( __UpperCamelCase	):
      _A  :						Any      		=       'swiftformer'
      def __init__(     self						,		lowerCamelCase=3						,		lowerCamelCase=[3, 3, 6, 4]						,		lowerCamelCase=[48, 56, 1_12, 2_20]						,		lowerCamelCase=4						,		lowerCamelCase=[True, True, True, True]						,		lowerCamelCase="gelu"						,		lowerCamelCase=3						,		lowerCamelCase=2						,		lowerCamelCase=1						,		lowerCamelCase=0.0						,		lowerCamelCase=True						,		lowerCamelCase=1e-5						,		lowerCamelCase=1e-5						,		**lowerCamelCase						,		):
          super().__init__(**lowerCamelCase	)
          snake_case__  =			num_channels
          snake_case__  =			depths
          snake_case__  =			embed_dims
          snake_case__  =			mlp_ratio
          snake_case__  =			downsamples
          snake_case__  =			hidden_act
          snake_case__  =			down_patch_size
          snake_case__  =			down_stride
          snake_case__  =			down_pad
          snake_case__  =			drop_path_rate
          snake_case__  =			use_layer_scale
          snake_case__  =			layer_scale_init_value
          snake_case__  =			batch_norm_eps





class    _SCREAMING_SNAKE_CASE					( __UpperCamelCase	):
      _A  :						int      		=       version.parse('1.11'	)
      @property
      def A_     (     self	):
          return OrderedDict(
              [
                  ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
              ]	)



      @property
      def A_     (     self	):
          return 1e-4



