



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_          =				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)



from __future__ import annotations

from abc import abstractmethod
from collections.abc import Iterable
from typing import Generic, Protocol, TypeVar





class 			lowerCAmelCase__(     snake_case__    ):






    '''simple docstring'''





    @abstractmethod
    def __lt__(						self					: T							, __snake_case					: T						):





       '''simple docstring'''
       pass





    @abstractmethod
    def __gt__(						self					: T							, __snake_case					: T						):





       '''simple docstring'''
       pass





    @abstractmethod
    def __eq__(						self					: T							, __snake_case					: object						):





       '''simple docstring'''
       pass





__UpperCamelCase					:	Dict          =				TypeVar('T', bound=Comparable)





class 			lowerCAmelCase__(     Generic[T]    ):






    '''simple docstring'''





    def __init__(						self					: Tuple						):





       '''simple docstring'''
       UpperCAmelCase_				:   list[T]							= []
       UpperCAmelCase_				:   int							= 0





    def __repr__(						self					: Any						):





       '''simple docstring'''
       return str(self.h						)





    def        _lowerCamelCase			(						self					: str							, __snake_case					: int						):





       '''simple docstring'''
       if child_idx > 0:
          return (child_idx - 1) // 2
       return None





    def        _lowerCamelCase			(						self					: str							, __snake_case					: int						):





       '''simple docstring'''
       UpperCAmelCase_				:   Dict							= 2 * parent_idx + 1
       if left_child_index < self.heap_size:
          return left_child_index
       return None





    def        _lowerCamelCase			(						self					: int							, __snake_case					: int						):





       '''simple docstring'''
       UpperCAmelCase_				:   Union[str, Any]							= 2 * parent_idx + 2
       if right_child_index < self.heap_size:
          return right_child_index
       return None





    def        _lowerCamelCase			(						self					: Union[str, Any]							, __snake_case					: int						):





       '''simple docstring'''
       if index < self.heap_size:
          UpperCAmelCase_				:   int							= index
          UpperCAmelCase_				:   List[str]							= self.left_child_idx(__snake_case						)
          UpperCAmelCase_				:   List[str]							= self.right_child_idx(__snake_case						)
          # check which child is larger than its parent
          if left_child is not None and self.h[left_child] > self.h[violation]:
             UpperCAmelCase_				:   List[str]							= left_child
          if right_child is not None and self.h[right_child] > self.h[violation]:
             UpperCAmelCase_				:   List[str]							= right_child
          # if violation indeed exists
          if violation != index:
             # swap to fix the violation
             UpperCAmelCase_		,   UpperCAmelCase_				:   List[Any]							= self.h[index], self.h[violation]
             # fix the subsequent violation recursively if any
             self.max_heapify(__snake_case						)





    def        _lowerCamelCase			(						self					: Optional[Any]							, __snake_case					: Iterable[T]						):





       '''simple docstring'''
       UpperCAmelCase_				:   Union[str, Any]							= list(__snake_case						)
       UpperCAmelCase_				:   int							= len(self.h						)
       if self.heap_size > 1:
          # max_heapify from right to left but exclude leaves (last level)
          for i in range(self.heap_size // 2 - 1							, -1							, -1						):
             self.max_heapify(__snake_case						)





    def        _lowerCamelCase			(						self					: Tuple						):





       '''simple docstring'''
       if self.heap_size >= 2:
          UpperCAmelCase_				:   List[str]							= self.h[0]
          UpperCAmelCase_				:   Dict							= self.h.pop(-1						)
          self.heap_size -= 1
          self.max_heapify(0						)
          return me
       elif self.heap_size == 1:
          self.heap_size -= 1
          return self.h.pop(-1						)
       else:
          raise Exception('''Empty heap'''						)





    def        _lowerCamelCase			(						self					: List[str]							, __snake_case					: T						):





       '''simple docstring'''
       self.h.append(__snake_case						)
       UpperCAmelCase_				:   Tuple							= (self.heap_size - 1) // 2
       self.heap_size += 1
       while idx >= 0:
          self.max_heapify(__snake_case						)
          UpperCAmelCase_				:   int							= (idx - 1) // 2





    def        _lowerCamelCase			(						self					: List[str]						):





       '''simple docstring'''
       UpperCAmelCase_				:   Tuple							= self.heap_size
       for j in range(size - 1							, 0							, -1						):
          UpperCAmelCase_		,   UpperCAmelCase_				:   Any							= self.h[j], self.h[0]
          self.heap_size -= 1
          self.max_heapify(0						)
       UpperCAmelCase_				:   Union[str, Any]							= size


if __name__ == "__main__":
       import doctest

       # run doc test
       doctest.testmod()

       # demo
       for unsorted in [
           [0],
           [2],
           [3, 5],
           [5, 3],
           [5, 5],
           [0, 0, 0, 0],
           [1, 1, 1, 1],
           [2, 2, 3, 5],
           [0, 2, 2, 3, 5],
           [2, 5, 3, 0, 2, 3, 0, 3],
           [6, 1, 2, 7, 9, 3, 4, 5, 10, 8],
           [103, 9, 1, 7, 11, 15, 25, 201, 209, 107, 5],
           [-45, -2, -5],
       ]:
              print(F'unsorted array: {unsorted}')

              __UpperCamelCase					:	Heap[int]          =				Heap()
              heap.build_max_heap(unsorted)
              print(F'after build heap: {heap}')

              print(F'max value: {heap.extract_max()}')
              print(F'after max value removed: {heap}')

              heap.insert(100)
              print(F'after new value 100 inserted: {heap}')

              heap.heap_sort()
              print(F'heap-sorted array: {heap}\n')