import argparse
import os


lowerCAmelCase__      		=					{
    'pytorch': {
        '1.13': {
            'torch': '1.13.1',
            'torchvision': '0.14.1',
            'torchaudio': '0.13.1',
            'python': 3.9,
            'cuda': 'cu116',
            'install': (
                'python3 -m pip install --no-cache-dir -U torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1'
                ' --extra-index-url https://download.pytorch.org/whl/cu116'
            ),
            'base_image': 'nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04',
        },
        '1.12': {
            'torch': '1.12.1',
            'torchvision': '0.13.1',
            'torchaudio': '0.12.1',
            'python': 3.9,
            'cuda': 'cu113',
            'install': (
                'python3 -m pip install --no-cache-dir -U torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1'
                ' --extra-index-url https://download.pytorch.org/whl/cu113'
            ),
            'base_image': 'nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04',
        },
        '1.11': {
            'torch': '1.11.0',
            'torchvision': '0.12.0',
            'torchaudio': '0.11.0',
            'python': 3.9,
            'cuda': 'cu113',
            'install': (
                'python3 -m pip install --no-cache-dir -U torch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0'
                ' --extra-index-url https://download.pytorch.org/whl/cu113'
            ),
            'base_image': 'nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04',
        },
        '1.10': {
            'torch': '1.10.2',
            'torchvision': '0.11.3',
            'torchaudio': '0.10.2',
            'python': 3.9,
            'cuda': 'cu113',
            'install': (
                'python3 -m pip install --no-cache-dir -U torch==1.10.2 torchvision==0.11.3 torchaudio==0.10.2'
                ' --extra-index-url https://download.pytorch.org/whl/cu113'
            ),
            'base_image': 'nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04',
        },
        # torchaudio < 0.10 has no CUDA-enabled binary distributions
        '1.9': {
            'torch': '1.9.1',
            'torchvision': '0.10.1',
            'torchaudio': '0.9.1',
            'python': 3.9,
            'cuda': 'cu111',
            'install': (
                'python3 -m pip install --no-cache-dir -U torch==1.9.1 torchvision==0.10.1 torchaudio==0.9.1'
                ' --extra-index-url https://download.pytorch.org/whl/cu111'
            ),
            'base_image': 'nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04',
        },
    },
    'tensorflow': {
        '2.11': {
            'tensorflow': '2.11.1',
            'install': 'python3 -m pip install --no-cache-dir -U tensorflow==2.11.1',
            'base_image': 'nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04',
        },
        '2.10': {
            'tensorflow': '2.10.1',
            'install': 'python3 -m pip install --no-cache-dir -U tensorflow==2.10.1',
            'base_image': 'nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04',
        },
        '2.9': {
            'tensorflow': '2.9.3',
            'install': 'python3 -m pip install --no-cache-dir -U tensorflow==2.9.3',
            'base_image': 'nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04',
        },
        '2.8': {
            'tensorflow': '2.8.2',
            'install': 'python3 -m pip install --no-cache-dir -U tensorflow==2.8.2',
            'base_image': 'nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04',
        },
        '2.7': {
            'tensorflow': '2.7.3',
            'install': 'python3 -m pip install --no-cache-dir -U tensorflow==2.7.3',
            'base_image': 'nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04',
        },
        '2.6': {
            'tensorflow': '2.6.5',
            'install': 'python3 -m pip install --no-cache-dir -U tensorflow==2.6.5',
            'base_image': 'nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04',
        },
        '2.5': {
            'tensorflow': '2.5.3',
            'install': 'python3 -m pip install --no-cache-dir -U tensorflow==2.5.3',
            'base_image': 'nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04',
        },
    },
}


if __name__ == "__main__":
    lowerCAmelCase__      		=					argparse.ArgumentParser('Choose the framework and version to install')
    parser.add_argument(
        '--framework', help='The framework to install. Should be `torch` or `tensorflow`', type=str, required=True
    )
    parser.add_argument('--version', help='The version of the framework to install.', type=str, required=True)
    lowerCAmelCase__      		=					parser.parse_args()

    lowerCAmelCase__      		=					past_versions_testing[args.framework][args.version]

    os.system(F'echo \"export INSTALL_CMD=\'{info["install"]}\'\" >> ~/.profile')
    print(F'echo \"export INSTALL_CMD=\'{info["install"]}\'\" >> ~/.profile')

    lowerCAmelCase__      		=					''
    if args.framework == "pytorch":
        lowerCAmelCase__      		=					info['cuda']
    os.system(F'echo \"export CUDA=\'{cuda}\'\" >> ~/.profile')
    print(F'echo \"export CUDA=\'{cuda}\'\" >> ~/.profile')

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(80_000))
            UpperCAmelCase_    		=				val_dataset.shuffle().select(range(8_000))

      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_096)

      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)