"""simple docstring"""
import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class   __snake_case			(	__lowerCAmelCase			, unittest.TestCase							):
      a__								=						HerbertTokenizer
      a__								=						HerbertTokenizerFast
      a__								=						True



      def     lowerCamelCase_  (		self)      ->     List[str]:





        '''simple docstring'''





        super().setUp()

        # Use a simpler test file without japanese/chinese characters
        with open(f'{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'       ,     encoding='utf-8') as f_data:
          a__:	Union[str, Any]     				=      f_data.read().replace('\n\n'       ,     '\n').strip()

        a__:	Tuple     				=      [
            '<s>',
            '</s>',
            'l',
            'o',
            'w',
            'e',
            'r',
            's',
            't',
            'i',
            'd',
            'n',
            'w</w>',
            'r</w>',
            't</w>',
            'lo',
            'low',
            'er</w>',
            'low</w>',
            'lowest</w>',
            'newer</w>',
            'wider</w>',
            ',</w>',
            '<unk>',
        ]
        a__:	Union[str, Any]     				=      dict(zip(lowercase       ,     range(len(lowercase))))
        a__:	int     				=      ['l o 123', 'lo w 1456', 'e r</w> 1789', '']

        a__:	Any     				=      os.path.join(self.tmpdirname       ,     VOCAB_FILES_NAMES['vocab_file'])
        a__:	Optional[Any]     				=      os.path.join(self.tmpdirname       ,     VOCAB_FILES_NAMES['merges_file'])
        with open(self.vocab_file       ,     'w') as fp:
          fp.write(json.dumps(lowercase))
        with open(self.merges_file       ,     'w') as fp:
          fp.write('\n'.join(lowercase))



      def     lowerCamelCase_  (		self       ,     lowercase)      ->     Optional[Any]:





        '''simple docstring'''





        a__:	Dict     				=      'lower newer'
        a__:	str     				=      'lower newer'
        return input_text, output_text



      def     lowerCamelCase_  (		self)      ->     List[Any]:





        '''simple docstring'''





        a__:	int     				=      self.tokenizer_class(vocab_file=self.vocab_file       ,     merges_file=self.merges_file)

        a__:	List[str]     				=      'lower'
        a__:	Dict     				=      ['low', 'er</w>']
        a__:	List[str]     				=      tokenizer.tokenize(lowercase)
        self.assertListEqual(lowercase       ,     lowercase)

        a__:	int     				=      tokens + ['<unk>']
        a__:	Union[str, Any]     				=      [16, 17, 23]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase)       ,     lowercase)



      def     lowerCamelCase_  (		self)      ->     Optional[int]:





        '''simple docstring'''





        if not self.test_rust_tokenizer:
          return

        a__:	List[str]     				=      self.get_tokenizer()
        a__:	Union[str, Any]     				=      self.get_rust_tokenizer()

        a__:	Dict     				=      'lower,newer'

        a__:	Any     				=      tokenizer.tokenize(lowercase)
        a__:	Optional[Any]     				=      rust_tokenizer.tokenize(lowercase)
        self.assertListEqual(lowercase       ,     lowercase)

        a__:	Dict     				=      tokenizer.encode(lowercase       ,     add_special_tokens=lowercase)
        a__:	Dict     				=      rust_tokenizer.encode(lowercase       ,     add_special_tokens=lowercase)
        self.assertListEqual(lowercase       ,     lowercase)

        a__:	List[Any]     				=      self.get_rust_tokenizer()
        a__:	Union[str, Any]     				=      tokenizer.encode(lowercase)
        a__:	Union[str, Any]     				=      rust_tokenizer.encode(lowercase)
        self.assertListEqual(lowercase       ,     lowercase)



      @slow
      def     lowerCamelCase_  (		self)      ->     str:





        '''simple docstring'''





        a__:	List[Any]     				=      self.tokenizer_class.from_pretrained('allegro/herbert-base-cased')

        a__:	Optional[int]     				=      tokenizer.encode('konstruowanie sekwencji'       ,     add_special_tokens=lowercase)
        a__:	List[Any]     				=      tokenizer.encode('konstruowanie wielu sekwencji'       ,     add_special_tokens=lowercase)

        a__:	Dict     				=      tokenizer.build_inputs_with_special_tokens(lowercase)
        a__:	Optional[int]     				=      tokenizer.build_inputs_with_special_tokens(lowercase       ,     lowercase)

        assert encoded_sentence == [0] + text + [2]
        assert encoded_pair == [0] + text + [2] + text_a + [2]





import argparse
import itertools
import operator
import sys
from collections import OrderedDict

from run_eval import datetime_now, run_generate

from utils import ROUGE_KEYS


# A table of supported tasks and the list of scores in the order of importance to be sorted by.
# To add a new task, simply list the score names that `run_eval.run_generate()` returns
__UpperCAmelCase     					=  {
    'translation': ['bleu'],
    'summarization': ROUGE_KEYS,
}







def 						_snake_case		(     SCREAMING_SNAKE_CASE					)							->   Optional[Any]:

     """simple docstring"""







     _lowerCAmelCase :       Dict	   =     search.split()
     _lowerCAmelCase :       int	   =     dict((g.split("="					) for g in groups)					)
     _lowerCAmelCase :       Dict	   =     list(entries.keys()					)
     _lowerCAmelCase :       Tuple	   =     [[f'''--{k} {v}''' for v in vs.split(":"					)] for k, vs in entries.items()]
     _lowerCAmelCase :       Dict	   =     [list(SCREAMING_SNAKE_CASE					) for x in itertools.product(*SCREAMING_SNAKE_CASE					)]
     return matrix, entry_names







def 						_snake_case		(     )							->   Tuple:

     """simple docstring"""







     _lowerCAmelCase :       List[str]	   =     sys.argv[0]

     _lowerCAmelCase :       Any	   =     argparse.ArgumentParser(
         usage=(
             "\n\nImportant: this script accepts all arguments `run_eval.py` accepts and then a few extra, therefore"
             " refer to `run_eval.py -h` for the complete list."
         )					)
     parser.add_argument(
         "--search"		,				type=SCREAMING_SNAKE_CASE		,				required=SCREAMING_SNAKE_CASE		,				help="param space to search, e.g. \"num_beams=5:10 length_penalty=0.8:1.0:1.2\""		,				)
     parser.add_argument(
         "--bs"		,				type=SCREAMING_SNAKE_CASE		,				default=8		,				required=SCREAMING_SNAKE_CASE		,				help="initial batch size (may get reduced if it's too big)"					)
     parser.add_argument("--task"		,				type=SCREAMING_SNAKE_CASE		,				help="used for task_specific_params + metrics"					)
     parser.add_argument(
         "--info"		,				nargs="?"		,				type=SCREAMING_SNAKE_CASE		,				const=datetime_now()		,				help=(
             "add custom notes to be printed before the results table. If no value is passed, the current datetime"
             " string will be used."
         )		,				)
     _lowerCAmelCase   ,      _lowerCAmelCase :       List[str]	   =     parser.parse_known_args()
     # we share some of the args
     args_main.extend(["--task", args.task]					)
     _lowerCAmelCase :       str	   =     [prog] + args_main

     # to support variations like translation_en_to_de"
     _lowerCAmelCase :       Any	   =     "translation" if "translation" in args.task else "summarization"

     _lowerCAmelCase   ,      _lowerCAmelCase :       int	   =     parse_search_arg(args.search					)
     _lowerCAmelCase :       Optional[Any]	   =     task_score_names[task]  # score cols first
     _lowerCAmelCase :       int	   =     {col: len(str(SCREAMING_SNAKE_CASE					)					) for col in col_names}
     _lowerCAmelCase :       Optional[int]	   =     []
     for r in matrix:
          _lowerCAmelCase :       List[str]	   =     dict((x.replace("--"		,				""					).split() for x in r)					)
          _lowerCAmelCase :       Any	   =     " ".join(SCREAMING_SNAKE_CASE					).split()
          args_exp.extend(["--bs", str(args.bs					)]					)  # in case we need to reduce its size due to CUDA OOM
          _lowerCAmelCase :       List[str]	   =     args_normal + args_exp

          # XXX: need to trap CUDA OOM and lower args.bs if that happens and retry

          _lowerCAmelCase :       Any	   =     run_generate(verbose=SCREAMING_SNAKE_CASE					)
          # make sure scores are first in the table
          _lowerCAmelCase :       Any	   =     OrderedDict()
          for score in task_score_names[task]:
               _lowerCAmelCase :       Dict	   =     scores[score]
          result.update(SCREAMING_SNAKE_CASE					)
          results.append(SCREAMING_SNAKE_CASE					)

          # find widest entries
          for k, v in result.items():
               _lowerCAmelCase :       Any	   =     len(str(SCREAMING_SNAKE_CASE					)					)
               if l > col_widths[k]:
                    _lowerCAmelCase :       str	   =     l

     _lowerCAmelCase :       Optional[Any]	   =     sorted(SCREAMING_SNAKE_CASE		,				key=operator.itemgetter(*task_score_names[task]					)		,				reverse=SCREAMING_SNAKE_CASE					)
     print(" | ".join([f'''{col:{col_widths[col]}}''' for col in col_names]					)					)
     print(" | ".join([f'''{'-'*col_widths[col]}''' for col in col_names]					)					)
     for row in results_sorted:
          print(" | ".join([f'''{row[col]:{col_widths[col]}}''' for col in col_names]					)					)

     _lowerCAmelCase :       Optional[int]	   =     results_sorted[0]
     for score in task_score_names[task]:
          del best[score]
     _lowerCAmelCase :       Tuple	   =     [f'''--{k} {v}''' for k, v in best.items()]
     _lowerCAmelCase :       Union[str, Any]	   =     ["--bs", str(args.bs					)]
     if args.info:
          print(f'''\nInfo: {args.info}'''					)
     print("\nBest score args:"					)
     print(" ".join(args_main + best_args + dyn_args					)					)

     return results_sorted


if __name__ == "__main__":
  # Usage:
  # [normal-run_eval_search.py cmd plus] \
  # --search="num_beams=1:5:10 length_penalty=0.8:1:1.2 early_stopping=true:false"
  #
  # Example:
  # PYTHONPATH="src:examples/seq2seq" python examples/seq2seq/run_eval_search.py $MODEL_NAME \
  # $DATA_DIR/val.source $SAVE_DIR/test_translations.txt --reference_path $DATA_DIR/val.target \
  # --score_path $SAVE_DIR/test_bleu.json --bs $BS --task translation \
  # --search="num_beams=1:5:10 length_penalty=0.8:1:1.2 early_stopping=true:false"
  run_search()






