


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


UpperCAmelCase					:  Optional[Any]			=						logging.get_logger(__name__)

UpperCAmelCase					:  List[str]			=						{
    """tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
        """https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json"""
    ),
}







class     __lowercase    (				__UpperCamelCase   ):



		"""simple docstring"""

		UpperCamelCase			: Any           =						"gptsan-japanese"
		UpperCamelCase			: List[str]           =						[
		    "past_key_values",
		]
		UpperCamelCase			: Union[str, Any]           =						{
		    "hidden_size": "d_model",
		    "num_attention_heads": "num_heads",
		    "num_hidden_layers": "num_layers",
		}







		def __init__(      self						,	A=3_60_00						,	A=12_80						,	A=10_24						,	A=81_92						,	A=40_96						,	A=1_28						,	A=10						,	A=0						,	A=16						,	A=16						,	A=1_28						,	A=0.0						,	A=1e-5						,	A=False						,	A=0.0						,	A="float32"						,	A=False						,	A=False						,	A=False						,	A=0.002						,	A=False						,	A=True						,	A=3_59_98						,	A=3_59_95						,	A=3_59_99						,	**A						,	)   ->      List[str]:







					'''simple docstring'''







					lowerCamelCase  						=   vocab_size
					lowerCamelCase  						=   max_position_embeddings
					lowerCamelCase  						=   d_model
					lowerCamelCase  						=   d_ff
					lowerCamelCase  						=   d_ext
					lowerCamelCase  						=   d_spout
					lowerCamelCase  						=   num_switch_layers
					lowerCamelCase  						=   num_ext_layers
					lowerCamelCase  						=   num_switch_layers + num_ext_layers
					lowerCamelCase  						=   num_heads
					lowerCamelCase  						=   num_experts
					lowerCamelCase  						=   expert_capacity
					lowerCamelCase  						=   dropout_rate
					lowerCamelCase  						=   layer_norm_epsilon
					lowerCamelCase  						=   router_bias
					lowerCamelCase  						=   router_jitter_noise
					lowerCamelCase  						=   router_dtype
					lowerCamelCase  						=   router_ignore_padding_tokens
					lowerCamelCase  						=   output_hidden_states
					lowerCamelCase  						=   output_attentions
					lowerCamelCase  						=   initializer_factor
					lowerCamelCase  						=   output_router_logits
					lowerCamelCase  						=   use_cache

					super().__init__(
					    separator_token_id=A						,	pad_token_id=A						,	eos_token_id=A						,	**A						,	)








def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase = 100_0000 )			->     int:
    lowerCamelCase__    :      int					 =		limit + 1
    lowerCamelCase__    :      Optional[Any]					 =		[0] * limit
    for first_term in range(1						,	_UpperCAmelCase ):
        for n in range(_UpperCAmelCase						,	_UpperCAmelCase						,	_UpperCAmelCase ):
            lowerCamelCase__    :      Optional[Any]					 =		first_term + n / first_term
            if common_difference % 4:  # d must be divisble by 4
                continue
            else:
                common_difference /= 4
                if (
                    first_term > common_difference
                    and first_term < 4 * common_difference
                ):  # since x,y,z are positive integers
                    frequency[n] += 1  # so z>0 and a>d ,also 4d<a

    lowerCamelCase__    :      List[str]					 =		sum(1 for x in frequency[1:limit] if x == 10 )

    return count


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





