from collections import OrderedDict
from typing import Mapping

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


A_      =      logging.get_logger(__name__)

A_      =      {
    "xlm-mlm-en-2048": "https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json",
    "xlm-mlm-ende-1024": "https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json",
    "xlm-mlm-enfr-1024": "https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json",
    "xlm-mlm-enro-1024": "https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json",
    "xlm-mlm-tlm-xnli15-1024": "https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json",
    "xlm-mlm-xnli15-1024": "https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json",
    "xlm-clm-enfr-1024": "https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json",
    "xlm-clm-ende-1024": "https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json",
    "xlm-mlm-17-1280": "https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json",
    "xlm-mlm-100-1280": "https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json",
}






class      __lowercase					(    _A    ):
      lowercase					 =     'xlm'
      lowercase					 =     {
          'hidden_size': 'emb_dim',
          'num_attention_heads': 'n_heads',
          'num_hidden_layers': 'n_layers',
          'n_words': 'vocab_size',  # For backward compatibility
      }

      def __init__(	self				:      Union[str, Any]							,							__lowerCamelCase				:      List[Any]=3_01_45							,							__lowerCamelCase				:      int=20_48							,							__lowerCamelCase				:      Any=12							,							__lowerCamelCase				:      Any=16							,							__lowerCamelCase				:      Union[str, Any]=0.1							,							__lowerCamelCase				:      Optional[Any]=0.1							,							__lowerCamelCase				:      Optional[Any]=True							,							__lowerCamelCase				:      str=False							,							__lowerCamelCase				:      str=False							,							__lowerCamelCase				:      str=False							,							__lowerCamelCase				:      Tuple=1							,							__lowerCamelCase				:      List[str]=True							,							__lowerCamelCase				:      List[Any]=5_12							,							__lowerCamelCase				:      str=20_48**-0.5							,							__lowerCamelCase				:      Union[str, Any]=1E-12							,							__lowerCamelCase				:      Optional[int]=0.02							,							__lowerCamelCase				:      Any=0							,							__lowerCamelCase				:      List[str]=1							,							__lowerCamelCase				:      str=2							,							__lowerCamelCase				:      Optional[Any]=3							,							__lowerCamelCase				:      List[Any]=5							,							__lowerCamelCase				:      Dict=True							,							__lowerCamelCase				:      int="first"							,							__lowerCamelCase				:      int=True							,							__lowerCamelCase				:      Optional[int]=None							,							__lowerCamelCase				:      List[Any]=True							,							__lowerCamelCase				:      Any=0.1							,							__lowerCamelCase				:      Any=5							,							__lowerCamelCase				:      Optional[int]=5							,							__lowerCamelCase				:      Tuple=0							,							__lowerCamelCase				:      Tuple=0							,							__lowerCamelCase				:      Optional[Any]=2							,							__lowerCamelCase				:      Tuple=0							,							**__lowerCamelCase				:      List[str]							,							)							->		Tuple:


         '''simple docstring'''

         lowercase							=		vocab_size
         lowercase							=		emb_dim
         lowercase							=		n_layers
         lowercase							=		n_heads
         lowercase							=		dropout
         lowercase							=		attention_dropout
         lowercase							=		gelu_activation
         lowercase							=		sinusoidal_embeddings
         lowercase							=		causal
         lowercase							=		asm
         lowercase							=		n_langs
         lowercase							=		use_lang_emb
         lowercase							=		layer_norm_eps
         lowercase							=		bos_index
         lowercase							=		eos_index
         lowercase							=		pad_index
         lowercase							=		unk_index
         lowercase							=		mask_index
         lowercase							=		is_encoder
         lowercase							=		max_position_embeddings
         lowercase							=		embed_init_std
         lowercase							=		init_std
         lowercase							=		summary_type
         lowercase							=		summary_use_proj
         lowercase							=		summary_activation
         lowercase							=		summary_proj_to_labels
         lowercase							=		summary_first_dropout
         lowercase							=		start_n_top
         lowercase							=		end_n_top
         lowercase							=		mask_token_id
         lowercase							=		lang_id

         if "n_words" in kwargs:
            lowercase							=		kwargs["n_words"]

         super().__init__(pad_token_id=__lowerCamelCase							,							bos_token_id=__lowerCamelCase							,							**__lowerCamelCase   )






class      __lowercase					(    _A    ):

      @property
      def        __a		(	self				:      Union[str, Any]   )							->		Mapping[str, Mapping[int, str]]:


         '''simple docstring'''

         if self.task == "multiple-choice":
            lowercase							=		{0: "batch", 1: "choice", 2: "sequence"}
         else:
            lowercase							=		{0: "batch", 1: "sequence"}
         return OrderedDict(
             [
                 ('''input_ids''', dynamic_axis),
                 ('''attention_mask''', dynamic_axis),
                 ('''token_type_ids''', dynamic_axis),
             ]   )






from __future__ import annotations

import math






def        __UpperCAmelCase    (       UpperCAmelCase       )->       list[int]:



			"""simple docstring"""







			if num <= 0:
						lowercase							=		f'{num}: Invalid input, please enter a positive integer.'
						raise ValueError(UpperCAmelCase       )

			lowercase							=		[True] * (num + 1)
			lowercase							=		[]
			lowercase							=		2
			lowercase							=		int(math.sqrt(UpperCAmelCase       )       )

			while start <= end:
						# If start is a prime
						if sieve[start] is True:
									prime.append(UpperCAmelCase       )

									# Set multiples of start be False
									for i in range(start * start,		num + 1,		UpperCAmelCase       ):
												if sieve[i] is True:
															lowercase							=		False

						start += 1

			for j in range(end + 1,		num + 1       ):
						if sieve[j] is True:
									prime.append(UpperCAmelCase       )

			return prime


if __name__ == "__main__":
						print(prime_sieve(int(input("Enter a positive integer: ").strip())))





