
'''simple docstring'''
from typing import TYPE_CHECKING

from ..utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available


__lowerCAmelCase  							= {
    'configuration_utils': ['GenerationConfig'],
    'streamers': ['TextIteratorStreamer', 'TextStreamer'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCAmelCase  							= [
				    'Constraint',
				    'ConstraintListState',
				    'DisjunctiveConstraint',
				    'PhrasalConstraint',
				]
				__lowerCAmelCase  							= [
				    'BeamHypotheses',
				    'BeamScorer',
				    'BeamSearchScorer',
				    'ConstrainedBeamSearchScorer',
				]
				__lowerCAmelCase  							= [
				    'EpsilonLogitsWarper',
				    'EtaLogitsWarper',
				    'ForcedBOSTokenLogitsProcessor',
				    'ForcedEOSTokenLogitsProcessor',
				    'HammingDiversityLogitsProcessor',
				    'InfNanRemoveLogitsProcessor',
				    'LogitsProcessor',
				    'LogitsProcessorList',
				    'LogitsWarper',
				    'MinLengthLogitsProcessor',
				    'MinNewTokensLengthLogitsProcessor',
				    'NoBadWordsLogitsProcessor',
				    'NoRepeatNGramLogitsProcessor',
				    'PrefixConstrainedLogitsProcessor',
				    'RepetitionPenaltyLogitsProcessor',
				    'SequenceBiasLogitsProcessor',
				    'EncoderRepetitionPenaltyLogitsProcessor',
				    'TemperatureLogitsWarper',
				    'TopKLogitsWarper',
				    'TopPLogitsWarper',
				    'TypicalLogitsWarper',
				    'EncoderNoRepeatNGramLogitsProcessor',
				    'ExponentialDecayLengthPenalty',
				    'LogitNormalization',
				]
				__lowerCAmelCase  							= [
				    'MaxNewTokensCriteria',
				    'MaxLengthCriteria',
				    'MaxTimeCriteria',
				    'StoppingCriteria',
				    'StoppingCriteriaList',
				    'validate_stopping_criteria',
				]
				__lowerCAmelCase  							= [
				    'GenerationMixin',
				    'top_k_top_p_filtering',
				    'GreedySearchEncoderDecoderOutput',
				    'GreedySearchDecoderOnlyOutput',
				    'SampleEncoderDecoderOutput',
				    'SampleDecoderOnlyOutput',
				    'BeamSearchEncoderDecoderOutput',
				    'BeamSearchDecoderOnlyOutput',
				    'BeamSampleEncoderDecoderOutput',
				    'BeamSampleDecoderOnlyOutput',
				    'ContrastiveSearchEncoderDecoderOutput',
				    'ContrastiveSearchDecoderOnlyOutput',
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCAmelCase  							= [
				    'TFForcedBOSTokenLogitsProcessor',
				    'TFForcedEOSTokenLogitsProcessor',
				    'TFLogitsProcessor',
				    'TFLogitsProcessorList',
				    'TFLogitsWarper',
				    'TFMinLengthLogitsProcessor',
				    'TFNoBadWordsLogitsProcessor',
				    'TFNoRepeatNGramLogitsProcessor',
				    'TFRepetitionPenaltyLogitsProcessor',
				    'TFTemperatureLogitsWarper',
				    'TFTopKLogitsWarper',
				    'TFTopPLogitsWarper',
				    'TFForceTokensLogitsProcessor',
				    'TFSuppressTokensAtBeginLogitsProcessor',
				    'TFSuppressTokensLogitsProcessor',
				]
				__lowerCAmelCase  							= [
				    'TFGenerationMixin',
				    'tf_top_k_top_p_filtering',
				    'TFGreedySearchDecoderOnlyOutput',
				    'TFGreedySearchEncoderDecoderOutput',
				    'TFSampleEncoderDecoderOutput',
				    'TFSampleDecoderOnlyOutput',
				    'TFBeamSearchEncoderDecoderOutput',
				    'TFBeamSearchDecoderOnlyOutput',
				    'TFBeamSampleEncoderDecoderOutput',
				    'TFBeamSampleDecoderOnlyOutput',
				    'TFContrastiveSearchEncoderDecoderOutput',
				    'TFContrastiveSearchDecoderOnlyOutput',
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCAmelCase  							= [
				    'FlaxForcedBOSTokenLogitsProcessor',
				    'FlaxForcedEOSTokenLogitsProcessor',
				    'FlaxLogitsProcessor',
				    'FlaxLogitsProcessorList',
				    'FlaxLogitsWarper',
				    'FlaxMinLengthLogitsProcessor',
				    'FlaxTemperatureLogitsWarper',
				    'FlaxTopKLogitsWarper',
				    'FlaxTopPLogitsWarper',
				]
				__lowerCAmelCase  							= [
				    'FlaxGenerationMixin',
				    'FlaxGreedySearchOutput',
				    'FlaxSampleOutput',
				    'FlaxBeamSearchOutput',
				]

if TYPE_CHECKING:
				from .configuration_utils import GenerationConfig
				from .streamers import TextIteratorStreamer, TextStreamer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .beam_constraints import Constraint, ConstraintListState, DisjunctiveConstraint, PhrasalConstraint
								from .beam_search import BeamHypotheses, BeamScorer, BeamSearchScorer, ConstrainedBeamSearchScorer
								from .logits_process import (
								    EncoderNoRepeatNGramLogitsProcessor,
								    EncoderRepetitionPenaltyLogitsProcessor,
								    EpsilonLogitsWarper,
								    EtaLogitsWarper,
								    ExponentialDecayLengthPenalty,
								    ForcedBOSTokenLogitsProcessor,
								    ForcedEOSTokenLogitsProcessor,
								    HammingDiversityLogitsProcessor,
								    InfNanRemoveLogitsProcessor,
								    LogitNormalization,
								    LogitsProcessor,
								    LogitsProcessorList,
								    LogitsWarper,
								    MinLengthLogitsProcessor,
								    MinNewTokensLengthLogitsProcessor,
								    NoBadWordsLogitsProcessor,
								    NoRepeatNGramLogitsProcessor,
								    PrefixConstrainedLogitsProcessor,
								    RepetitionPenaltyLogitsProcessor,
								    SequenceBiasLogitsProcessor,
								    TemperatureLogitsWarper,
								    TopKLogitsWarper,
								    TopPLogitsWarper,
								    TypicalLogitsWarper,
								)
								from .stopping_criteria import (
								    MaxLengthCriteria,
								    MaxNewTokensCriteria,
								    MaxTimeCriteria,
								    StoppingCriteria,
								    StoppingCriteriaList,
								    validate_stopping_criteria,
								)
								from .utils import (
								    BeamSampleDecoderOnlyOutput,
								    BeamSampleEncoderDecoderOutput,
								    BeamSearchDecoderOnlyOutput,
								    BeamSearchEncoderDecoderOutput,
								    ContrastiveSearchDecoderOnlyOutput,
								    ContrastiveSearchEncoderDecoderOutput,
								    GenerationMixin,
								    GreedySearchDecoderOnlyOutput,
								    GreedySearchEncoderDecoderOutput,
								    SampleDecoderOnlyOutput,
								    SampleEncoderDecoderOutput,
								    top_k_top_p_filtering,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tf_logits_process import (
								    TFForcedBOSTokenLogitsProcessor,
								    TFForcedEOSTokenLogitsProcessor,
								    TFForceTokensLogitsProcessor,
								    TFLogitsProcessor,
								    TFLogitsProcessorList,
								    TFLogitsWarper,
								    TFMinLengthLogitsProcessor,
								    TFNoBadWordsLogitsProcessor,
								    TFNoRepeatNGramLogitsProcessor,
								    TFRepetitionPenaltyLogitsProcessor,
								    TFSuppressTokensAtBeginLogitsProcessor,
								    TFSuppressTokensLogitsProcessor,
								    TFTemperatureLogitsWarper,
								    TFTopKLogitsWarper,
								    TFTopPLogitsWarper,
								)
								from .tf_utils import (
								    TFBeamSampleDecoderOnlyOutput,
								    TFBeamSampleEncoderDecoderOutput,
								    TFBeamSearchDecoderOnlyOutput,
								    TFBeamSearchEncoderDecoderOutput,
								    TFContrastiveSearchDecoderOnlyOutput,
								    TFContrastiveSearchEncoderDecoderOutput,
								    TFGenerationMixin,
								    TFGreedySearchDecoderOnlyOutput,
								    TFGreedySearchEncoderDecoderOutput,
								    TFSampleDecoderOnlyOutput,
								    TFSampleEncoderDecoderOutput,
								    tf_top_k_top_p_filtering,
								)

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .flax_logits_process import (
								    FlaxForcedBOSTokenLogitsProcessor,
								    FlaxForcedEOSTokenLogitsProcessor,
								    FlaxLogitsProcessor,
								    FlaxLogitsProcessorList,
								    FlaxLogitsWarper,
								    FlaxMinLengthLogitsProcessor,
								    FlaxTemperatureLogitsWarper,
								    FlaxTopKLogitsWarper,
								    FlaxTopPLogitsWarper,
								)
								from .flax_utils import FlaxBeamSearchOutput, FlaxGenerationMixin, FlaxGreedySearchOutput, FlaxSampleOutput
else:
				import sys

				__lowerCAmelCase  							= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







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

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

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

				if os.environ.get('TRAIN_ON_SMALL', 'false') == "true":
								__lowerCAmelCase  							= tr_dataset.shuffle().select(range(80_000))
								__lowerCAmelCase  							= val_dataset.shuffle().select(range(8_000))

				print(tr_dataset)
				print(val_dataset)

				__lowerCAmelCase  							= FlaxBigBirdForNaturalQuestions.from_pretrained(
				    args.model_id, block_size=args.block_size, num_random_blocks=args.num_random_blocks
				)
				__lowerCAmelCase  							= BigBirdTokenizerFast.from_pretrained(args.model_id)
				__lowerCAmelCase  							= DataCollator(pad_id=tokenizer.pad_token_id, max_length=4_096)

				__lowerCAmelCase  							= {
				    '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,
				}
				__lowerCAmelCase							,       __lowerCAmelCase  							= build_tx(**tx_args)

				__lowerCAmelCase  							= 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,
				)

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