



'''simple docstring'''







import argparse
import logging
import os
import sys
from collections import namedtuple

import torch
from modeling_bertabs import BertAbs, build_predictor
from torch.utils.data import DataLoader, SequentialSampler
from tqdm import tqdm

from transformers import BertTokenizer

from .utils_summarization import (
    CNNDMDataset,
    build_mask,
    compute_token_type_ids,
    encode_for_summarization,
    truncate_or_pad,
)


lowercase__  :	List[str]            =      logging.getLogger(__name__)
logging.basicConfig(stream=sys.stdout, level=logging.INFO)


lowercase__  :	List[Any]            =      namedtuple('Batch', ['document_names', 'batch_size', 'src', 'segs', 'mask_src', 'tgt_str'])





def     snake_case__			(lowerCAmelCase_						):
    UpperCamelCase__	     =      BertTokenizer.from_pretrained("bert-base-uncased"       ,	do_lower_case=lowerCAmelCase_						)
    UpperCamelCase__	     =      BertAbs.from_pretrained("remi/bertabs-finetuned-extractive-abstractive-summarization"						)
    model.to(args.device						)
    model.eval()

    UpperCamelCase__	     =      {
        "BOS": tokenizer.vocab["[unused0]"],
        "EOS": tokenizer.vocab["[unused1]"],
        "PAD": tokenizer.vocab["[PAD]"],
    }

    if args.compute_rouge:
        UpperCamelCase__	     =      []
        UpperCamelCase__	     =      []

        import nltk
        import rouge

        nltk.download("punkt"						)
        UpperCamelCase__	     =      rouge.Rouge(
            metrics=["rouge-n", "rouge-l"]       ,	max_n=2       ,	limit_length=lowerCAmelCase_       ,	length_limit=args.beam_size       ,	length_limit_type="words"       ,	apply_avg=lowerCAmelCase_       ,	apply_best=lowerCAmelCase_       ,	alpha=0.5       ,	weight_factor=1.2       ,	stemming=lowerCAmelCase_       ,	)

    # these (unused) arguments are defined to keep the compatibility
    # with the legacy code and will be deleted in a next iteration.
    UpperCamelCase__	     =      ""
    UpperCamelCase__	     =      ""

    UpperCamelCase__	     =      build_data_iterator(lowerCAmelCase_       ,	lowerCAmelCase_						)
    UpperCamelCase__	     =      build_predictor(lowerCAmelCase_       ,	lowerCAmelCase_       ,	lowerCAmelCase_       ,	lowerCAmelCase_						)

    logger.info("***** Running evaluation *****"						)
    logger.info("  Number examples = %d"       ,	len(data_iterator.dataset						)						)
    logger.info("  Batch size = %d"       ,	args.batch_size						)
    logger.info(""						)
    logger.info("***** Beam Search parameters *****"						)
    logger.info("  Beam size = %d"       ,	args.beam_size						)
    logger.info("  Minimum length = %d"       ,	args.min_length						)
    logger.info("  Maximum length = %d"       ,	args.max_length						)
    logger.info("  Alpha (length penalty) = %.2f"       ,	args.alpha						)
    logger.info("  Trigrams %s be blocked"       ,	("will" if args.block_trigram else "will NOT")						)

    for batch in tqdm(lowerCAmelCase_						):
        UpperCamelCase__	     =      predictor.translate_batch(lowerCAmelCase_						)
        UpperCamelCase__	     =      predictor.from_batch(lowerCAmelCase_						)
        UpperCamelCase__	     =      [format_summary(lowerCAmelCase_						) for t in translations]
        save_summaries(lowerCAmelCase_       ,	args.summaries_output_dir       ,	batch.document_names						)

        if args.compute_rouge:
            reference_summaries += batch.tgt_str
            generated_summaries += summaries

    if args.compute_rouge:
        UpperCamelCase__	     =      rouge_evaluator.get_scores(lowerCAmelCase_       ,	lowerCAmelCase_						)
        UpperCamelCase__	     =      format_rouge_scores(lowerCAmelCase_						)
        save_rouge_scores(lowerCAmelCase_						)
        print(lowerCAmelCase_						)





def     snake_case__			(lowerCAmelCase_       ,	lowerCAmelCase_       ,	lowerCAmelCase_						):
    for summary, document_name in zip(lowerCAmelCase_       ,	lowerCAmelCase_						):
        # Prepare the summary file's name
        if "." in document_name:
            UpperCamelCase__	     =      ".".join(document_name.split("."						)[:-1]						)
            UpperCamelCase__	     =      document_name.split("."						)[-1]
            UpperCamelCase__	     =      bare_document_name + "_summary." + extension
        else:
            UpperCamelCase__	     =      document_name + "_summary"

        UpperCamelCase__	     =      os.path.join(lowerCAmelCase_       ,	lowerCAmelCase_						)
        with open(lowerCAmelCase_       ,	"w"						) as output:
            output.write(lowerCAmelCase_						)





def     snake_case__			(lowerCAmelCase_						):
    UpperCamelCase__     ,	UpperCamelCase__     ,	UpperCamelCase__	     =      translation
    UpperCamelCase__	     =      (
        raw_summary.replace("[unused0]"       ,	""						)
        .replace("[unused3]"       ,	""						)
        .replace("[PAD]"       ,	""						)
        .replace("[unused1]"       ,	""						)
        .replace(R" +"       ,	" "						)
        .replace(" [unused2] "       ,	". "						)
        .replace("[unused2]"       ,	""						)
        .strip()
    )

    return summary





def     snake_case__			(lowerCAmelCase_						):
    return """\n
****** ROUGE SCORES ******

** ROUGE 1
F1        >> {:.3f}
Precision >> {:.3f}
Recall    >> {:.3f}

** ROUGE 2
F1        >> {:.3f}
Precision >> {:.3f}
Recall    >> {:.3f}

** ROUGE L
F1        >> {:.3f}
Precision >> {:.3f}
Recall    >> {:.3f}""".format(
        scores["rouge-1"]["f"]       ,	scores["rouge-1"]["p"]       ,	scores["rouge-1"]["r"]       ,	scores["rouge-2"]["f"]       ,	scores["rouge-2"]["p"]       ,	scores["rouge-2"]["r"]       ,	scores["rouge-l"]["f"]       ,	scores["rouge-l"]["p"]       ,	scores["rouge-l"]["r"]       ,	)





def     snake_case__			(lowerCAmelCase_						):
    with open("rouge_scores.txt"       ,	"w"						) as output:
        output.write(lowerCAmelCase_						)





def     snake_case__			(lowerCAmelCase_       ,	lowerCAmelCase_						):
    UpperCamelCase__	     =      load_and_cache_examples(lowerCAmelCase_       ,	lowerCAmelCase_						)
    UpperCamelCase__	     =      SequentialSampler(lowerCAmelCase_						)

    def collate_fn(lowerCAmelCase_						):
        return collate(lowerCAmelCase_       ,	lowerCAmelCase_       ,	block_size=5_12       ,	device=args.device						)

    UpperCamelCase__	     =      DataLoader(
        lowerCAmelCase_       ,	sampler=lowerCAmelCase_       ,	batch_size=args.batch_size       ,	collate_fn=lowerCAmelCase_       ,	)

    return iterator





def     snake_case__			(lowerCAmelCase_       ,	lowerCAmelCase_						):
    UpperCamelCase__	     =      CNNDMDataset(args.documents_dir						)
    return dataset





def     snake_case__			(lowerCAmelCase_       ,	lowerCAmelCase_       ,	lowerCAmelCase_       ,	lowerCAmelCase_						):
    UpperCamelCase__	     =      [x for x in data if not len(x[1]						) == 0]  # remove empty_files
    UpperCamelCase__	     =      [name for name, _, _ in data]
    UpperCamelCase__	     =      [" ".join(lowerCAmelCase_						) for _, _, summary_list in data]

    UpperCamelCase__	     =      [encode_for_summarization(lowerCAmelCase_       ,	lowerCAmelCase_       ,	lowerCAmelCase_						) for _, story, summary in data]
    UpperCamelCase__	     =      torch.tensor(
        [truncate_or_pad(lowerCAmelCase_       ,	lowerCAmelCase_       ,	tokenizer.pad_token_id						) for story, _ in encoded_text]						)
    UpperCamelCase__	     =      compute_token_type_ids(lowerCAmelCase_       ,	tokenizer.cls_token_id						)
    UpperCamelCase__	     =      build_mask(lowerCAmelCase_       ,	tokenizer.pad_token_id						)

    UpperCamelCase__	     =      Batch(
        document_names=lowerCAmelCase_       ,	batch_size=len(lowerCAmelCase_						)       ,	src=encoded_stories.to(lowerCAmelCase_						)       ,	segs=encoder_token_type_ids.to(lowerCAmelCase_						)       ,	mask_src=encoder_mask.to(lowerCAmelCase_						)       ,	tgt_str=lowerCAmelCase_       ,	)

    return batch





def     snake_case__			(lowerCAmelCase_       ,	lowerCAmelCase_						):
    UpperCamelCase__	     =      summary_tokens.to("cpu"						).numpy()
    UpperCamelCase__	     =      tokenizer.decode(lowerCAmelCase_						)
    UpperCamelCase__	     =      summary.split("."						)
    UpperCamelCase__	     =      [s + "." for s in sentences]
    return sentences





def     snake_case__			():
    UpperCamelCase__	     =      argparse.ArgumentParser()
    parser.add_argument(
        "--documents_dir"       ,	default=lowerCAmelCase_       ,	type=lowerCAmelCase_       ,	required=lowerCAmelCase_       ,	help="The folder where the documents to summarize are located."       ,	)
    parser.add_argument(
        "--summaries_output_dir"       ,	default=lowerCAmelCase_       ,	type=lowerCAmelCase_       ,	required=lowerCAmelCase_       ,	help="The folder in wich the summaries should be written. Defaults to the folder where the documents are"       ,	)
    parser.add_argument(
        "--compute_rouge"       ,	default=lowerCAmelCase_       ,	type=lowerCAmelCase_       ,	required=lowerCAmelCase_       ,	help="Compute the ROUGE metrics during evaluation. Only available for the CNN/DailyMail dataset."       ,	)
    # EVALUATION options
    parser.add_argument(
        "--no_cuda"       ,	default=lowerCAmelCase_       ,	type=lowerCAmelCase_       ,	help="Whether to force the execution on CPU."       ,	)
    parser.add_argument(
        "--batch_size"       ,	default=4       ,	type=lowerCAmelCase_       ,	help="Batch size per GPU/CPU for training."       ,	)
    # BEAM SEARCH arguments
    parser.add_argument(
        "--min_length"       ,	default=50       ,	type=lowerCAmelCase_       ,	help="Minimum number of tokens for the summaries."       ,	)
    parser.add_argument(
        "--max_length"       ,	default=2_00       ,	type=lowerCAmelCase_       ,	help="Maixmum number of tokens for the summaries."       ,	)
    parser.add_argument(
        "--beam_size"       ,	default=5       ,	type=lowerCAmelCase_       ,	help="The number of beams to start with for each example."       ,	)
    parser.add_argument(
        "--alpha"       ,	default=0.95       ,	type=lowerCAmelCase_       ,	help="The value of alpha for the length penalty in the beam search."       ,	)
    parser.add_argument(
        "--block_trigram"       ,	default=lowerCAmelCase_       ,	type=lowerCAmelCase_       ,	help="Whether to block the existence of repeating trigrams in the text generated by beam search."       ,	)
    UpperCamelCase__	     =      parser.parse_args()

    # Select device (distibuted not available)
    UpperCamelCase__	     =      torch.device("cuda" if torch.cuda.is_available() and not args.no_cuda else "cpu"						)

    # Check the existence of directories
    if not args.summaries_output_dir:
        UpperCamelCase__	     =      args.documents_dir

    if not documents_dir_is_valid(args.documents_dir						):
        raise FileNotFoundError(
            "We could not find the directory you specified for the documents to summarize, or it was empty. Please"
            " specify a valid path."						)
    os.makedirs(args.summaries_output_dir       ,	exist_ok=lowerCAmelCase_						)

    evaluate(lowerCAmelCase_						)





def     snake_case__			(lowerCAmelCase_						):
    if not os.path.exists(lowerCAmelCase_						):
        return False

    UpperCamelCase__	     =      os.listdir(lowerCAmelCase_						)
    if len(lowerCAmelCase_						) == 0:
        return False

    return True


if __name__ == "__main__":
      main()





"""simple docstring"""


import posixpath
from pathlib import Path
from unittest.mock import patch

import pytest
from fsspec.implementations.local import AbstractFileSystem, LocalFileSystem, stringify_path
from fsspec.registry import _registry as _fsspec_registry




class 					UpperCamelCase   (							lowerCAmelCase__  ):
       SCREAMING_SNAKE_CASE_						      = "mock"







       def __init__(					self,				*lowerCAmelCase__,				lowerCAmelCase__,				**lowerCAmelCase__) -> Dict:
            super().__init__()
            snake_case_   			=   LocalFileSystem(*lowerCAmelCase__,				**lowerCAmelCase__)
            snake_case_   			=   Path(lowerCAmelCase__).resolve().as_posix() + '/'







       def 						a_		(					self,				lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__) -> Any:
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            return self._fs.mkdir(lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__)







       def 						a_		(					self,				lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__) -> str:
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            return self._fs.makedirs(lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__)







       def 						a_		(					self,				lowerCAmelCase__) -> Union[str, Any]:
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            return self._fs.rmdir(lowerCAmelCase__)







       def 						a_		(					self,				lowerCAmelCase__,				lowerCAmelCase__=True,				*lowerCAmelCase__,				**lowerCAmelCase__) -> Optional[Any]:
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            snake_case_   			=   self._fs.ls(lowerCAmelCase__,				detail=lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__)
            if detail:
                 return [{**info, "name": info["name"][len(self.local_root_dir) :]} for info in out]
            else:
                 return [name[len(self.local_root_dir) :] for name in out]







       def 						a_		(					self,				lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__) -> Dict:
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            snake_case_   			=   dict(self._fs.info(lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__))
            snake_case_   			=   out['name'][len(self.local_root_dir) :]
            return out







       def 						a_		(					self,				lowerCAmelCase__,				lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__) -> str:
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            return self._fs.cp_file(lowerCAmelCase__,				lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__)







       def 						a_		(					self,				lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__) -> Union[str, Any]:
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            return self._fs.rm_file(lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__)







       def 						a_		(					self,				lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__) -> List[Any]:
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            return self._fs.rm(lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__)







       def 						a_		(					self,				lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__) -> Optional[Any]:
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            return self._fs._open(lowerCAmelCase__,				*lowerCAmelCase__,				**lowerCAmelCase__)







       def 						a_		(					self,				lowerCAmelCase__) -> Tuple:
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            return self._fs.created(lowerCAmelCase__)







       def 						a_		(					self,				lowerCAmelCase__) -> int:
            snake_case_   			=   posixpath.join(self.local_root_dir,				self._strip_protocol(lowerCAmelCase__))
            return self._fs.modified(lowerCAmelCase__)







       @classmethod
       def 						a_		(					cls,				lowerCAmelCase__) -> Any:
            snake_case_   			=   stringify_path(lowerCAmelCase__)
            if path.startswith('mock://'):
                 snake_case_   			=   path[7:]
            return path




class 					UpperCamelCase   (							lowerCAmelCase__  ):
       SCREAMING_SNAKE_CASE_						      = "tmp"
       SCREAMING_SNAKE_CASE_						      = None







       def __init__(					self,				*lowerCAmelCase__,				**lowerCAmelCase__) -> str:
            assert self.tmp_dir is not None, "TmpDirFileSystem.tmp_dir is not set"
            super().__init__(*lowerCAmelCase__,				**lowerCAmelCase__,				local_root_dir=self.tmp_dir,				auto_mkdir=lowerCAmelCase__)







       @classmethod
       def 						a_		(					cls,				lowerCAmelCase__) -> List[str]:
            snake_case_   			=   stringify_path(lowerCAmelCase__)
            if path.startswith('tmp://'):
                 snake_case_   			=   path[6:]
            return path







@pytest.fixture
def    UpperCAmelCase       (						)							-> Tuple:
     snake_case_   			=   MockFileSystem
     snake_case_   			=   TmpDirFileSystem
     yield
     del _fsspec_registry["mock"]
     del _fsspec_registry["tmp"]







@pytest.fixture
def    UpperCAmelCase       (						UpperCAmelCase		,   UpperCAmelCase   )							-> Tuple:
     snake_case_   			=   tmp_path_factory.mktemp('mockfs'   )
     return MockFileSystem(local_root_dir=UpperCAmelCase		,   auto_mkdir=UpperCAmelCase   )







@pytest.fixture
def    UpperCAmelCase       (						UpperCAmelCase		,   UpperCAmelCase   )							-> int:
     snake_case_   			=   tmp_path_factory.mktemp('tmpfs'   )
     with patch.object(UpperCAmelCase		,   'tmp_dir'		,   UpperCAmelCase   ):
          yield TmpDirFileSystem()

