




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


_lowerCamelCase      :						Optional[int]							=  {
    """configuration_blip""": [
        """BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BlipConfig""",
        """BlipTextConfig""",
        """BlipVisionConfig""",
    ],
    """processing_blip""": ["""BlipProcessor"""],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase      :						List[Any]							=  ["""BlipImageProcessor"""]


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase      :						Optional[Any]							=  [
      """BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """BlipModel""",
      """BlipPreTrainedModel""",
      """BlipForConditionalGeneration""",
      """BlipForQuestionAnswering""",
      """BlipVisionModel""",
      """BlipTextModel""",
      """BlipForImageTextRetrieval""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase      :						Optional[Any]							=  [
      """TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFBlipModel""",
      """TFBlipPreTrainedModel""",
      """TFBlipForConditionalGeneration""",
      """TFBlipForQuestionAnswering""",
      """TFBlipVisionModel""",
      """TFBlipTextModel""",
      """TFBlipForImageTextRetrieval""",
  ]

if TYPE_CHECKING:
  from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
  from .processing_blip import BlipProcessor

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_blip import BlipImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_blip import (
        BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
        BlipForConditionalGeneration,
        BlipForImageTextRetrieval,
        BlipForQuestionAnswering,
        BlipModel,
        BlipPreTrainedModel,
        BlipTextModel,
        BlipVisionModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_blip import (
        TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFBlipForConditionalGeneration,
        TFBlipForImageTextRetrieval,
        TFBlipForQuestionAnswering,
        TFBlipModel,
        TFBlipPreTrainedModel,
        TFBlipTextModel,
        TFBlipVisionModel,
    )

else:
  import sys

  _lowerCamelCase      :						Optional[int]							=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer

def  __lowerCamelCase					( _lowercase						,     _lowercase						,     _lowercase						,     _lowercase=1024			)       ->      Union[str, Any]:
     UpperCamelCase    ,		UpperCamelCase						    =					[], []

     UpperCamelCase						    =					list(zip(_lowercase						,     _lowercase			)			)
     UpperCamelCase    ,		UpperCamelCase						    =					sorted_examples[0]

     def is_too_big(_lowercase			):
          return tok(_lowercase						,     return_tensors='pt'			).input_ids.shape[1] > max_tokens

     for src, tgt in tqdm(sorted_examples[1:]			):
          UpperCamelCase						    =					new_src + ' ' + src
          UpperCamelCase						    =					new_tgt + ' ' + tgt
          if is_too_big(_lowercase			) or is_too_big(_lowercase			):  # cant fit, finalize example
               finished_src.append(_lowercase			)
               finished_tgt.append(_lowercase			)
               UpperCamelCase    ,		UpperCamelCase						    =					src, tgt
          else:  # can fit, keep adding
               UpperCamelCase    ,		UpperCamelCase						    =					cand_src, cand_tgt

    # cleanup
     if new_src:
          assert new_tgt
          finished_src.append(_lowercase			)
          finished_tgt.append(_lowercase			)
     return finished_src, finished_tgt

def  __lowerCamelCase					( _lowercase						,     _lowercase						,     _lowercase						,     _lowercase			)       ->      Union[str, Any]:
     UpperCamelCase						    =					Path(_lowercase			)
     save_path.mkdir(exist_ok=_lowercase			)
     for split in ["train"]:
          UpperCamelCase    ,		UpperCamelCase						    =					data_dir / F'{split}.source', data_dir / F'{split}.target'
          UpperCamelCase						    =					[x.rstrip() for x in Path(_lowercase			).open().readlines()]
          UpperCamelCase						    =					[x.rstrip() for x in Path(_lowercase			).open().readlines()]
          UpperCamelCase    ,		UpperCamelCase						    =					pack_examples(_lowercase						,     _lowercase						,     _lowercase						,     _lowercase			)
          print(F'packed {split} split from {len(_lowercase			)} examples -> {len(_lowercase			)}.'			)
          Path(save_path / F'{split}.source'			).open('w'			).write('\n'.join(_lowercase			)			)
          Path(save_path / F'{split}.target'			).open('w'			).write('\n'.join(_lowercase			)			)
     for split in ["val", "test"]:
          UpperCamelCase    ,		UpperCamelCase						    =					data_dir / F'{split}.source', data_dir / F'{split}.target'
          shutil.copyfile(_lowercase						,     save_path / F'{split}.source'			)
          shutil.copyfile(_lowercase						,     save_path / F'{split}.target'			)

def  __lowerCamelCase					( )       ->      Union[str, Any]:
     UpperCamelCase						    =					argparse.ArgumentParser()
     parser.add_argument('--tok_name'						,     type=_lowercase						,     help='like facebook/bart-large-cnn,t5-base, etc.'			)
     parser.add_argument('--max_seq_len'						,     type=_lowercase						,     default=128			)
     parser.add_argument('--data_dir'						,     type=_lowercase			)
     parser.add_argument('--save_path'						,     type=_lowercase			)
     UpperCamelCase						    =					parser.parse_args()
     UpperCamelCase						    =					AutoTokenizer.from_pretrained(args.tok_name			)
     return pack_data_dir(_lowercase						,     Path(args.data_dir			)						,     args.max_seq_len						,     args.save_path			)


if __name__ == "__main__":
 packer_cli()


