




'''simple docstring'''




import os
from dataclasses import replace

import jax
import wandb
from bigbird_flax import Args, DataCollator, FlaxBigBirdForNaturalQuestions, Trainer, build_tx, train_step, val_step
from datasets import load_dataset
from flax import jax_utils

from transformers import BigBirdTokenizerFast


if __name__ == "__main__":
    print('#################### AVAILABLE DEVICES ####################')
    print(jax.devices())
    print('###########################################################')

    # setup for wandb sweep
    UpperCAmelCase_       				=      Args()
    UpperCAmelCase_       				=      wandb.init(project='bigbird-natural-questions', config=args.__dict__)
    UpperCAmelCase_       				=      dict(logger.config)
    del wandb_args["batch_size"]
    UpperCAmelCase_       				=      replace(args, **wandb_args)
    UpperCAmelCase_       				=      args.base_dir + '-' + wandb.run.id
    UpperCAmelCase_       				=      replace(args, base_dir=base_dir)
    print(args)

    UpperCAmelCase_       				=      load_dataset('json', data_files=args.tr_data_path)['train']
    UpperCAmelCase_       				=      load_dataset('json', data_files=args.val_data_path)['train']

    # drop extra batch for now
    UpperCAmelCase_       				=      range(len(tr_dataset) - len(tr_dataset) % args.batch_size)
    UpperCAmelCase_       				=      tr_dataset.shuffle().select(indices)
    UpperCAmelCase_       				=      range(len(val_dataset) - len(val_dataset) % args.batch_size)
    UpperCAmelCase_       				=      val_dataset.shuffle().select(indices)

    if os.environ.get('TRAIN_ON_SMALL', 'false') == "true":
        UpperCAmelCase_       				=      tr_dataset.shuffle().select(range(8_0_0_0_0))
        UpperCAmelCase_       				=      val_dataset.shuffle().select(range(8_0_0_0))

    print(tr_dataset)
    print(val_dataset)

    UpperCAmelCase_       				=      FlaxBigBirdForNaturalQuestions.from_pretrained(
        args.model_id, block_size=args.block_size, num_random_blocks=args.num_random_blocks
    )
    UpperCAmelCase_       				=      BigBirdTokenizerFast.from_pretrained(args.model_id)
    UpperCAmelCase_       				=      DataCollator(pad_id=tokenizer.pad_token_id, max_length=4_0_9_6)

    UpperCAmelCase_       				=      {
        'lr': args.lr,
        'init_lr': args.init_lr,
        'warmup_steps': args.warmup_steps,
        'num_train_steps': args.max_epochs * (len(tr_dataset) // args.batch_size),
        'weight_decay': args.weight_decay,
    }
    UpperCAmelCase_				,		UpperCAmelCase_       				=      build_tx(**tx_args)

    UpperCAmelCase_       				=      Trainer(
        args=args,
        data_collator=data_collator,
        model_save_fn=model.save_pretrained,
        train_step_fn=train_step,
        val_step_fn=val_step,
        logger=logger,
        scheduler_fn=lr,
    )

    UpperCAmelCase_       				=      None
    UpperCAmelCase_       				=      trainer.create_state(model, tx, num_train_steps=tx_args['num_train_steps'], ckpt_dir=ckpt_dir)
    try:
        trainer.train(state, tr_dataset, val_dataset)
    except KeyboardInterrupt:
        print('Oooops; TRAINING STOPPED UNFORTUNATELY')

    print('SAVING WEIGHTS IN `final-weights`')
    UpperCAmelCase_       				=      jax_utils.unreplicate(state.params)
    model.save_pretrained(os.path.join(args.base_dir, 'final-weights'), params=params)






'''simple docstring'''




from __future__ import annotations

import random
import string

class 						lowerCAmelCase_   :







  '''simple docstring'''







  def __init__(						self    :	int						,		_UpperCAmelCase    :	str | None = None ):






   """simple docstring"""






   UpperCAmelCase__										=    passcode or self.__passcode_creator()
   UpperCAmelCase__										=    self.__make_key_list()
   UpperCAmelCase__										=    self.__make_shift_key()


  def __str__(						self    :	int ):






   """simple docstring"""






   return "".join(self.__passcode )


  def 							SCREAMING_SNAKE_CASE__			(						self    :	List[str]						,		_UpperCAmelCase    :	list[int] ):






   """simple docstring"""






   for i in range(1						,		len(_UpperCAmelCase )						,		2 ):
    iterlist[i] *= -1
   return iterlist


  def 							SCREAMING_SNAKE_CASE__			(						self    :	int ):






   """simple docstring"""






   UpperCAmelCase__										=    string.ascii_letters + string.digits
   UpperCAmelCase__										=    [random.choice(_UpperCAmelCase ) for _ in range(random.randint(10						,		20 ) )]
   return password


  def 							SCREAMING_SNAKE_CASE__			(						self    :	Tuple ):






   """simple docstring"""






   UpperCAmelCase__										=    (
       string.ascii_letters + string.digits + string.punctuation + """ \t\n"""
   )

   UpperCAmelCase__										=    []

   # creates points known as breakpoints to break the key_list_options at those
   # points and pivot each substring
   UpperCAmelCase__										=    sorted(set(self.__passcode ) )
   UpperCAmelCase__										=    []

   # algorithm for creating a new shuffled list, keys_l, out of key_list_options
   for i in key_list_options:
    temp_list.extend(_UpperCAmelCase )

    # checking breakpoints at which to pivot temporary sublist and add it into
    # keys_l
    if i in breakpoints or i == key_list_options[-1]:
     keys_l.extend(temp_list[::-1] )
     temp_list.clear()

        # returning a shuffled keys_l to prevent brute force guessing of shift key
   return keys_l


  def 							SCREAMING_SNAKE_CASE__			(						self    :	Tuple ):






   """simple docstring"""






   UpperCAmelCase__										=    sum(self.__neg_pos([ord(_UpperCAmelCase ) for x in self.__passcode] ) )
   return num if num > 0 else len(self.__passcode )


  def 							SCREAMING_SNAKE_CASE__			(						self    :	Optional[Any]						,		_UpperCAmelCase    :	str ):






   """simple docstring"""






   UpperCAmelCase__										=    """"""

   # decoding shift like Caesar cipher algorithm implementing negative shift or
   # reverse shift or left shift
   for i in encoded_message:
    UpperCAmelCase__										=    self.__key_list.index(_UpperCAmelCase )
    decoded_message += self.__key_list[
        (position - self.__shift_key) % -len(self.__key_list )
    ]

   return decoded_message



  def 							SCREAMING_SNAKE_CASE__			(						self    :	List[str]						,		_UpperCAmelCase    :	str ):






   """simple docstring"""






   UpperCAmelCase__										=    """"""

   # encoding shift like Caesar cipher algorithm implementing positive shift or
   # forward shift or right shift
   for i in plaintext:
    UpperCAmelCase__										=    self.__key_list.index(_UpperCAmelCase )
    encoded_message += self.__key_list[
        (position + self.__shift_key) % len(self.__key_list )
    ]

   return encoded_message

def    _UpperCamelCase      (				SCREAMING_SNAKE_CASE__			:      str = "Hello, this is a modified Caesar cipher"       ):
 '''simple docstring'''





 UpperCAmelCase__										=    ShuffledShiftCipher()
 return cipa.decrypt(cipa.encrypt(SCREAMING_SNAKE_CASE__       )       )


if __name__ == "__main__":
    import doctest

    doctest.testmod()
