"""simple docstring"""





from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional

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


if TYPE_CHECKING:
       from ... import FeatureExtractionMixin, TensorType

_UpperCamelCase     :		Optional[int]											=					logging.get_logger(__name__)

_UpperCamelCase     :		List[str]											=					{
    "openai/imagegpt-small": "",
    "openai/imagegpt-medium": "",
    "openai/imagegpt-large": "",
}


class   UpperCAmelCase_			(					_a):
      lowerCamelCase__	:					List[Any]										=						"imagegpt"
      lowerCamelCase__	:					Optional[int]										=						["past_key_values"]
      lowerCamelCase__	:					Dict										=						{
          "hidden_size": "n_embd",
          "max_position_embeddings": "n_positions",
          "num_attention_heads": "n_head",
          "num_hidden_layers": "n_layer",
      }


      def __init__(     self	,    a=5_1_2 + 1	,    a=3_2 * 3_2	,    a=5_1_2	,    a=2_4	,    a=8	,    a=None	,    a="quick_gelu"	,    a=0.1	,    a=0.1	,    a=0.1	,    a=1e-5	,    a=0.02	,    a=True	,    a=True	,    a=False	,    a=False	,    a=False	,    **a	,    ) ->      Any:
             lowercase__    :	Optional[int]     					=			vocab_size
             lowercase__    :	Optional[int]     					=			n_positions
             lowercase__    :	List[Any]     					=			n_embd
             lowercase__    :	Dict     					=			n_layer
             lowercase__    :	Optional[int]     					=			n_head
             lowercase__    :	Union[str, Any]     					=			n_inner
             lowercase__    :	List[str]     					=			activation_function
             lowercase__    :	Tuple     					=			resid_pdrop
             lowercase__    :	int     					=			embd_pdrop
             lowercase__    :	Optional[int]     					=			attn_pdrop
             lowercase__    :	Any     					=			layer_norm_epsilon
             lowercase__    :	Any     					=			initializer_range
             lowercase__    :	Optional[int]     					=			scale_attn_weights
             lowercase__    :	int     					=			use_cache
             lowercase__    :	List[str]     					=			scale_attn_by_inverse_layer_idx
             lowercase__    :	List[str]     					=			reorder_and_upcast_attn
             lowercase__    :	int     					=			tie_word_embeddings

             super().__init__(tie_word_embeddings=a	,    **a							)





class   UpperCAmelCase_			(					_a):


      @property
      def 	_UpperCAmelCase (     self							) ->      Mapping[str, Mapping[int, str]]:
             return OrderedDict(
                 [
                     ('input_ids', {0: 'batch', 1: 'sequence'}),
                 ]							)


      def 	_UpperCAmelCase (     self	,    a	,    a = 1	,    a = -1	,    a = False	,    a = None	,    a = 3	,    a = 3_2	,    a = 3_2	,    ) ->      Mapping[str, Any]:
             lowercase__    :	Union[str, Any]     					=			self._generate_dummy_images(a	,    a	,    a	,    a							)
             lowercase__    :	int     					=			dict(preprocessor(images=a	,    return_tensors=a							)							)

             return inputs


"""simple docstring"""





import math





def        a_  (   _lowerCAmelCase						:				int = 100  ):





       '''simple docstring'''

       lowercase__    :	Union[str, Any]     					=			sum(i * i for i in range(1     ,				n + 1  )  )
       lowercase__    :	str     					=			int(math.pow(sum(range(1     ,				n + 1  )  )     ,				2  )  )
       return square_of_sum - sum_of_squares


if __name__ == "__main__":
       print(f'''{solution() = }''')

