






'''simple docstring'''




import fire
from torch.utils.data import DataLoader
from tqdm import tqdm

from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save

def 						__UpperCAmelCase							(			__magic_name__  ,__magic_name__  ,__magic_name__=1024  ,__magic_name__=1024  ,__magic_name__=False  ,**__magic_name__    )->     Union[str, Any]:



			"""simple docstring"""



			snake_case_					:       Dict =							AutoTokenizer.from_pretrained(__lowerCamelCase    )
			snake_case_					:       List[Any] =							SeqaSeqDataset(__lowerCamelCase  ,__lowerCamelCase  ,__lowerCamelCase  ,__lowerCamelCase  ,type_path="train"  ,**__lowerCamelCase    )
			snake_case_					:       Any =							tok.pad_token_id

			def get_lens(__magic_name__    ):
						snake_case_					:       Union[str, Any] =							tqdm(
						    DataLoader(__lowerCamelCase  ,batch_size=512  ,num_workers=8  ,shuffle=__lowerCamelCase  ,collate_fn=ds.collate_fn    )  ,desc=str(ds.len_file    )  ,)
						snake_case_					:       Optional[int] =							[]
						for batch in dl:
									snake_case_					:       List[Any] =							batch["input_ids"].ne(__lowerCamelCase    ).sum(1    ).tolist()
									snake_case_					:       str =							batch["labels"].ne(__lowerCamelCase    ).sum(1    ).tolist()
									if consider_target:
												for src, tgt in zip(__lowerCamelCase  ,__lowerCamelCase    ):
															max_lens.append(max(__lowerCamelCase  ,__lowerCamelCase    )    )
									else:
												max_lens.extend(__lowerCamelCase    )
						return max_lens

			snake_case_					:       str =							get_lens(__lowerCamelCase    )
			snake_case_					:       Dict =							SeqaSeqDataset(__lowerCamelCase  ,__lowerCamelCase  ,__lowerCamelCase  ,__lowerCamelCase  ,type_path="val"  ,**__lowerCamelCase    )
			snake_case_					:       List[str] =							get_lens(__lowerCamelCase    )
			pickle_save(__lowerCamelCase  ,train_ds.len_file    )
			pickle_save(__lowerCamelCase  ,val_ds.len_file    )


if __name__ == "__main__":
		fire.Fire(save_len_file)






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCamelCase				=			{
    """configuration_chinese_clip""": [
        """CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ChineseCLIPConfig""",
        """ChineseCLIPOnnxConfig""",
        """ChineseCLIPTextConfig""",
        """ChineseCLIPVisionConfig""",
    ],
    """processing_chinese_clip""": ["""ChineseCLIPProcessor"""],
}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase				=			["""ChineseCLIPFeatureExtractor"""]
   __lowerCamelCase				=			["""ChineseCLIPImageProcessor"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase				=			[
       """CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """ChineseCLIPModel""",
       """ChineseCLIPPreTrainedModel""",
       """ChineseCLIPTextModel""",
       """ChineseCLIPVisionModel""",
   ]

if TYPE_CHECKING:
   from .configuration_chinese_clip import (
       CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
       ChineseCLIPConfig,
       ChineseCLIPOnnxConfig,
       ChineseCLIPTextConfig,
       ChineseCLIPVisionConfig,
   )
   from .processing_chinese_clip import ChineseCLIPProcessor

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_chinese_clip import (
          CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
          ChineseCLIPModel,
          ChineseCLIPPreTrainedModel,
          ChineseCLIPTextModel,
          ChineseCLIPVisionModel,
      )

else:
   import sys

   __lowerCamelCase				=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





