



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

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

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

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

							print(tr_dataset)
							print(val_dataset)

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

							A    =	{
							    """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,
							}
							A    =	build_tx(**tx_args)

							A    =	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,
							)

							A    =	None
							A    =	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`')
							A    =	jax_utils.unreplicate(state.params)
							model.save_pretrained(os.path.join(args.base_dir, 'final-weights'), params=params)








"""simple docstring"""







import unittest

from cer import CER


A    =	CER()

class 			_a     (   unittest.TestCase):



			def 							__lowercase				( self       :							Optional[Any]		)       ->				Tuple:
									snake_case      : Union[str, Any]							=   ["White House"]
									snake_case      : Tuple							=   ["white house"]
									# S = 2, D = 0, I = 0, N = 11, CER = 2 / 11
									snake_case      : int							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.1818181818		) < 1E-6		)



			def 							__lowercase				( self       :							Optional[Any]		)       ->				Dict:
									snake_case      : Tuple							=   ["were wolf"]
									snake_case      : Union[str, Any]							=   ["werewolf"]
									# S = 0, D = 0, I = 1, N = 9, CER = 1 / 9
									snake_case      : List[str]							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.1111111		) < 1E-6		)

									snake_case      : List[str]							=   ["werewolf"]
									snake_case      : Optional[Any]							=   ["weae     wolf"]
									# S = 1, D = 1, I = 0, N = 8, CER = 0.25
									snake_case      : Optional[int]							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.25		) < 1E-6		)

									# consecutive whitespaces case 1
									snake_case      : Optional[int]							=   ["were wolf"]
									snake_case      : Dict							=   ["were               wolf"]
									# S = 0, D = 0, I = 0, N = 9, CER = 0
									snake_case      : Dict							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.0		) < 1E-6		)

									# consecutive whitespaces case 2
									snake_case      : Dict							=   ["were   wolf"]
									snake_case      : Dict							=   ["were               wolf"]
									# S = 0, D = 0, I = 0, N = 9, CER = 0
									snake_case      : Optional[int]							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.0		) < 1E-6		)



			def 							__lowercase				( self       :							List[Any]		)       ->				Union[str, Any]:
									snake_case      : str							=   ["werewolf"]
									snake_case      : List[Any]							=   ["weaewolf"]
									# S = 1, D = 0, I = 0, N = 8, CER = 0.125
									snake_case      : str							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.125		) < 1E-6		)



			def 							__lowercase				( self       :							int		)       ->				int:
									snake_case      : Dict							=   ["werewolf"]
									snake_case      : Optional[Any]							=   ["wereawolf"]
									# S = 0, D = 1, I = 0, N = 8, CER = 0.125
									snake_case      : List[str]							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.125		) < 1E-6		)



			def 							__lowercase				( self       :							Union[str, Any]		)       ->				List[Any]:
									snake_case      : Tuple							=   ["werewolf"]
									snake_case      : Union[str, Any]							=   ["wereolf"]
									# S = 0, D = 0, I = 1, N = 8, CER = 0.125
									snake_case      : str							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.125		) < 1E-6		)



			def 							__lowercase				( self       :							int		)       ->				List[str]:
									snake_case      : int							=   ["werewolf"]
									snake_case      : Optional[Any]							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertEqual(_lowercase      ,  0.0		)



			def 							__lowercase				( self       :							List[Any]		)       ->				Optional[Any]:
									snake_case      : str							=   ["werewolf", "I am your father"]
									snake_case      : str							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertEqual(_lowercase      ,  0.0		)

									snake_case      : Union[str, Any]							=   ["werewolf", "I am your father", "doge"]
									snake_case      : str							=   ["werxwolf", "I       am your father", "doge"]
									# S = 1, D = 0, I = 0, N = 28, CER = 1 / 28
									snake_case      : Dict							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.03571428		) < 1E-6		)



			def 							__lowercase				( self       :							Any		)       ->				Union[str, Any]:
									snake_case      : Union[str, Any]							=   ["My hovercraft", "is full of eels"]
									snake_case      : List[str]							=   ["My hovercraft is full", " of eels"]
									# S = 0, D = 0, I = 2, N = 28, CER = 2 / 28
									# whitespace at the front of " of eels" will be strip during preporcessing
									# so need to insert 2 whitespaces
									snake_case      : int							=   cer.compute(predictions=_lowercase      ,  references=_lowercase      ,  concatenate_texts=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.071428		) < 1E-6		)



			def 							__lowercase				( self       :							Any		)       ->				Dict:
									snake_case      : Dict							=   ["我能吞下玻璃而不伤身体"]
									snake_case      : List[str]							=   [" 能吞虾玻璃而 不霜身体啦"]
									# S = 3, D = 2, I = 0, N = 11, CER = 5 / 11
									snake_case      : str							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.4545454545		) < 1E-6		)

									snake_case      : List[Any]							=   ["我能吞下玻璃", "而不伤身体"]
									snake_case      : int							=   ["我    能 吞 下 玻 璃", "而不伤身体"]
									# S = 0, D = 5, I = 0, N = 11, CER = 5 / 11
									snake_case      : Dict							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.454545454545		) < 1E-6		)

									snake_case      : int							=   ["我能吞下玻璃而不伤身体"]
									snake_case      : int							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertFalse(_lowercase      ,  0.0		)



			def 							__lowercase				( self       :							List[Any]		)       ->				List[Any]:
									snake_case      : int							=   [""]
									snake_case      : Optional[int]							=   ["Hypothesis"]
									with self.assertRaises(_lowercase		):
															cer.compute(predictions=_lowercase      ,  references=_lowercase		)


if __name__ == "__main__":
			unittest.main()



