





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

a__    :		List[Any]      						=     logging.get_logger(__name__)

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






class  lowercase    (      UpperCAmelCase__       ):






					"""simple docstring"""



					snake_case_						  =			'''imagegpt'''
					snake_case_						  =			['''past_key_values''']
					snake_case_						  =			{
					    '''hidden_size''': '''n_embd''',
					    '''max_position_embeddings''': '''n_positions''',
					    '''num_attention_heads''': '''n_head''',
					    '''num_hidden_layers''': '''n_layer''',
					}





					def __init__(    self						:     Optional[Any] ,					a_						:     Any=5_12 + 1 ,					a_						:     Dict=32 * 32 ,					a_						:     str=5_12 ,					a_						:     str=24 ,					a_						:     Union[str, Any]=8 ,					a_						:     Union[str, Any]=None ,					a_						:     List[str]="quick_gelu" ,					a_						:     Any=0.1 ,					a_						:     Optional[Any]=0.1 ,					a_						:     Dict=0.1 ,					a_						:     Union[str, Any]=1e-5 ,					a_						:     List[Any]=0.0_2 ,					a_						:     int=True ,					a_						:     Tuple=True ,					a_						:     Union[str, Any]=False ,					a_						:     int=False ,					a_						:     List[Any]=False ,					**a_						:     str ,					):

						"""simple docstring"""



						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__										=			scale_attn_by_inverse_layer_idx
						lowerCamelCase__										=			reorder_and_upcast_attn
						lowerCamelCase__										=			tie_word_embeddings

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






class  lowercase    (      UpperCAmelCase__       ):






					"""simple docstring"""



					@property
					def       _UpperCamelCase       (    self						:     Dict							):

						"""simple docstring"""



						return OrderedDict(
						    [
						        ("""input_ids""", {0: """batch""", 1: """sequence"""}),
						    ]							)





					def       _UpperCamelCase       (    self						:     List[str] ,					a_						:     "FeatureExtractionMixin" ,					a_						:     int = 1 ,					a_						:     int = -1 ,					a_						:     bool = False ,					a_						:     Optional["TensorType"] = None ,					a_						:     int = 3 ,					a_						:     int = 32 ,					a_						:     int = 32 ,					):

						"""simple docstring"""



						lowerCamelCase__										=			self._generate_dummy_images(__lowerCAmelCase ,					__lowerCAmelCase ,					__lowerCAmelCase ,					__lowerCAmelCase							)
						lowerCamelCase__										=			dict(preprocessor(images=__lowerCAmelCase ,					return_tensors=__lowerCAmelCase							)							)

						return inputs






'''simple docstring'''


from math import isqrt, loga
def 						lowerCamelCase__   (				a							):
						__snake_case						 =   [True] * max_number
						for i in range(2    ,	isqrt(max_number - 1							) + 1							):
												if is_prime[i]:
																		for j in range(i**2    ,	a    ,	a							):
																								__snake_case						 =   False

						return [i for i in range(2    ,	a							) if is_prime[i]]
def 						lowerCamelCase__   (				a = 800800    ,	a = 800800							):
						__snake_case						 =   degree * loga(a							)
						__snake_case						 =   int(a							)
						__snake_case						 =   calculate_prime_numbers(a							)

						__snake_case						 =   0
						__snake_case						 =   0
						__snake_case						 =   len(a							) - 1
						while left < right:
												while (
												    prime_numbers[right] * loga(prime_numbers[left]							)
												    + prime_numbers[left] * loga(prime_numbers[right]							)
												    > upper_bound
												):
																		right -= 1
												hybrid_integers_count += right - left
												left += 1

						return hybrid_integers_count


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

