





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


UpperCAmelCase_											=  logging.get_logger(__name__)

UpperCAmelCase_											=  {
    # pcqm4mv1 now deprecated
    "graphormer-base": "https://huggingface.co/clefourrier/graphormer-base-pcqm4mv2/resolve/main/config.json",
    # See all Graphormer models at https://huggingface.co/models?filter=graphormer
}




class  __UpperCamelCase						(       A__						):
     __A  :     int            =      """graphormer"""
     __A  :     Dict            =      ["""past_key_values"""]





     def __init__(    self							,       _UpperCamelCase = 1							,       _UpperCamelCase = 512 * 9							,       _UpperCamelCase = 512 * 3							,       _UpperCamelCase = 512							,       _UpperCamelCase = 512							,       _UpperCamelCase = 512							,       _UpperCamelCase = 128							,       _UpperCamelCase = 5							,       _UpperCamelCase = 1024							,       _UpperCamelCase = "multi_hop"							,       _UpperCamelCase = 512							,       _UpperCamelCase = False							,       _UpperCamelCase = 12							,       _UpperCamelCase = 768							,       _UpperCamelCase = 768							,       _UpperCamelCase = 32							,       _UpperCamelCase = 0.1							,       _UpperCamelCase = 0.1							,       _UpperCamelCase = 0.0							,       _UpperCamelCase = False							,       _UpperCamelCase = False							,       _UpperCamelCase = False							,       _UpperCamelCase = "gelu"							,       _UpperCamelCase = None							,       _UpperCamelCase = False							,       _UpperCamelCase = 0							,       _UpperCamelCase = False							,       _UpperCamelCase = 0.0							,       _UpperCamelCase = 8							,       _UpperCamelCase = None							,       _UpperCamelCase = None							,       _UpperCamelCase = True							,       _UpperCamelCase = True							,       _UpperCamelCase=0							,       _UpperCamelCase=1							,       _UpperCamelCase=2							,       **_UpperCamelCase							,       ):
        _UpperCAmelCase											=      num_classes
        _UpperCAmelCase											=      num_atoms
        _UpperCAmelCase											=      num_in_degree
        _UpperCAmelCase											=      num_out_degree
        _UpperCAmelCase											=      num_edges
        _UpperCAmelCase											=      num_spatial
        _UpperCAmelCase											=      num_edge_dis
        _UpperCAmelCase											=      edge_type
        _UpperCAmelCase											=      multi_hop_max_dist
        _UpperCAmelCase											=      spatial_pos_max
        _UpperCAmelCase											=      max_nodes
        _UpperCAmelCase											=      num_hidden_layers
        _UpperCAmelCase											=      embedding_dim
        _UpperCAmelCase											=      embedding_dim
        _UpperCAmelCase											=      ffn_embedding_dim
        _UpperCAmelCase											=      num_attention_heads
        _UpperCAmelCase											=      dropout
        _UpperCAmelCase											=      attention_dropout
        _UpperCAmelCase											=      layerdrop
        _UpperCAmelCase											=      encoder_normalize_before
        _UpperCAmelCase											=      pre_layernorm
        _UpperCAmelCase											=      apply_graphormer_init
        _UpperCAmelCase											=      activation_fn
        _UpperCAmelCase											=      embed_scale
        _UpperCAmelCase											=      freeze_embeddings
        _UpperCAmelCase											=      num_trans_layers_to_freeze
        _UpperCAmelCase											=      share_input_output_embed
        _UpperCAmelCase											=      traceable
        _UpperCAmelCase											=      q_noise
        _UpperCAmelCase											=      qn_block_size

        # These parameters are here for future extensions
        # atm, the model only supports self attention
        _UpperCAmelCase											=      kdim
        _UpperCAmelCase											=      vdim
        _UpperCAmelCase											=      self_attention
        _UpperCAmelCase											=      bias

        super().__init__(
            pad_token_id=_UpperCamelCase							,       bos_token_id=_UpperCamelCase							,       eos_token_id=_UpperCamelCase							,       **_UpperCamelCase							,       )






import os
import sys
import time

from . import transposition_cipher as trans_cipher
def     A__					(						)     ->     None:






   """simple docstring"""







   _UpperCAmelCase											=      '''Prehistoric Men.txt'''
   _UpperCAmelCase											=      '''Output.txt'''
   _UpperCAmelCase											=      int(input('''Enter key: '''	)	)
   _UpperCAmelCase											=      input('''Encrypt/Decrypt [e/d]: '''	)

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

   _UpperCAmelCase											=      time.time()
   if mode.lower().startswith('''e'''	):
      with open(SCREAMING_SNAKE_CASE_	) as f:
         _UpperCAmelCase											=      f.read()
      _UpperCAmelCase											=      trans_cipher.encrypt_message(SCREAMING_SNAKE_CASE_							,  SCREAMING_SNAKE_CASE_	)
   elif mode.lower().startswith('''d'''	):
      with open(SCREAMING_SNAKE_CASE_	) as f:
         _UpperCAmelCase											=      f.read()
      _UpperCAmelCase											=      trans_cipher.decrypt_message(SCREAMING_SNAKE_CASE_							,  SCREAMING_SNAKE_CASE_	)

   with open(SCREAMING_SNAKE_CASE_							,  '''w'''	) as output_obj:
      output_obj.write(SCREAMING_SNAKE_CASE_	)

   _UpperCAmelCase											=      round(time.time() - start_time							,  2	)
   print(('''Done (''', total_time, '''seconds )''')	)


if __name__ == "__main__":
   main()