





'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

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


lowercase_         =			logging.get_logger(__name__)

lowercase_         =			{
    """google/mobilebert-uncased""": """https://huggingface.co/google/mobilebert-uncased/resolve/main/config.json"""
}


class  a_					(    snake_case_	):

    '''simple docstring'''
    UpperCamelCase			   =			MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
    UpperCamelCase			   =			'''mobilebert'''


    def __init__(		self			,		A=3_0522			,		A=512			,		A=24			,		A=4			,		A=512			,		A="relu"			,		A=0.0			,		A=0.1			,		A=512			,		A=2			,		A=0.02			,		A=1e-12			,		A=0			,		A=128			,		A=True			,		A=True			,		A=128			,		A=False			,		A=True			,		A=4			,		A="no_norm"			,		A=True			,		A=None			,		**A			,		)		->       Dict:
        super().__init__(pad_token_id=A			,		**A	)

        _SCREAMING_SNAKE_CASE     =      vocab_size
        _SCREAMING_SNAKE_CASE     =      hidden_size
        _SCREAMING_SNAKE_CASE     =      num_hidden_layers
        _SCREAMING_SNAKE_CASE     =      num_attention_heads
        _SCREAMING_SNAKE_CASE     =      hidden_act
        _SCREAMING_SNAKE_CASE     =      intermediate_size
        _SCREAMING_SNAKE_CASE     =      hidden_dropout_prob
        _SCREAMING_SNAKE_CASE     =      attention_probs_dropout_prob
        _SCREAMING_SNAKE_CASE     =      max_position_embeddings
        _SCREAMING_SNAKE_CASE     =      type_vocab_size
        _SCREAMING_SNAKE_CASE     =      initializer_range
        _SCREAMING_SNAKE_CASE     =      layer_norm_eps
        _SCREAMING_SNAKE_CASE     =      embedding_size
        _SCREAMING_SNAKE_CASE     =      trigram_input
        _SCREAMING_SNAKE_CASE     =      use_bottleneck
        _SCREAMING_SNAKE_CASE     =      intra_bottleneck_size
        _SCREAMING_SNAKE_CASE     =      use_bottleneck_attention
        _SCREAMING_SNAKE_CASE     =      key_query_shared_bottleneck
        _SCREAMING_SNAKE_CASE     =      num_feedforward_networks
        _SCREAMING_SNAKE_CASE     =      normalization_type
        _SCREAMING_SNAKE_CASE     =      classifier_activation

        if self.use_bottleneck:
            _SCREAMING_SNAKE_CASE     =      intra_bottleneck_size
        else:
            _SCREAMING_SNAKE_CASE     =      hidden_size

        _SCREAMING_SNAKE_CASE     =      classifier_dropout




class  a_					(    snake_case_	):

    '''simple docstring'''


    @property
    def       snake_case_(		self	)		->       Mapping[str, Mapping[int, str]]:
        if self.task == "multiple-choice":
            _SCREAMING_SNAKE_CASE     =      {0: """batch""", 1: """choice""", 2: """sequence"""}
        else:
            _SCREAMING_SNAKE_CASE     =      {0: """batch""", 1: """sequence"""}
        return OrderedDict(
            [
                ("""input_ids""", dynamic_axis),
                ("""attention_mask""", dynamic_axis),
                ("""token_type_ids""", dynamic_axis),
            ]	)










'''simple docstring'''

import os
import sys
import time

from . import transposition_cipher as trans_cipher





def lowerCamelCase						(					)						->None:
    _SCREAMING_SNAKE_CASE     =      """Prehistoric Men.txt"""
    _SCREAMING_SNAKE_CASE     =      """Output.txt"""
    _SCREAMING_SNAKE_CASE     =      int(input("""Enter key: """   )   )
    _SCREAMING_SNAKE_CASE     =      input("""Encrypt/Decrypt [e/d]: """   )

    if not os.path.exists(__lowerCamelCase   ):
        print(F'File {input_file} does not exist. Quitting...'   )
        sys.exit()
    if os.path.exists(__lowerCamelCase   ):
        print(F'Overwrite {output_file}? [y/n]'   )
        _SCREAMING_SNAKE_CASE     =      input("""> """   )
        if not response.lower().startswith("""y"""   ):
            sys.exit()

    _SCREAMING_SNAKE_CASE     =      time.time()
    if mode.lower().startswith("""e"""   ):
        with open(__lowerCamelCase   ) as f:
            _SCREAMING_SNAKE_CASE     =      f.read()
        _SCREAMING_SNAKE_CASE     =      trans_cipher.encrypt_message(__lowerCamelCase ,	__lowerCamelCase   )
    elif mode.lower().startswith("""d"""   ):
        with open(__lowerCamelCase   ) as f:
            _SCREAMING_SNAKE_CASE     =      f.read()
        _SCREAMING_SNAKE_CASE     =      trans_cipher.decrypt_message(__lowerCamelCase ,	__lowerCamelCase   )

    with open(__lowerCamelCase ,	"""w"""   ) as output_obj:
        output_obj.write(__lowerCamelCase   )

    _SCREAMING_SNAKE_CASE     =      round(time.time() - start_time ,	2   )
    print(("""Done (""", total_time, """seconds )""")   )


if __name__ == "__main__":
      main()



