


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
lowerCamelCase		      = {
    '''translation''': ['''bleu'''],
    '''summarization''': ROUGE_KEYS,
}




def 			a_   (					SCREAMING_SNAKE_CASE__      :   int  ):
       '''simple docstring'''





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




def 			a_   (					):
       '''simple docstring'''





       _lowerCamelCase :	Tuple						=sys.argv[0]

       _lowerCamelCase :	str						=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=snake_case__	,    required=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=snake_case__	,    default=8	,    required=snake_case__	,    help='initial batch size (may get reduced if it\'s too big)'  )
       parser.add_argument('--task'	,    type=snake_case__	,    help='used for task_specific_params + metrics'  )
       parser.add_argument(
           '--info'	,    nargs='?'	,    type=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 :	int						=parser.parse_known_args()
       # we share some of the args
       args_main.extend(['--task', args.task]  )
       _lowerCamelCase :	Tuple						=[prog] + args_main

       # to support variations like translation_en_to_de"
       _lowerCamelCase :	str						='translation' if 'translation' in args.task else 'summarization'

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

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

              _lowerCamelCase :	str						=run_generate(verbose=snake_case__  )
              # make sure scores are first in the table
              _lowerCamelCase :	List[str]						=OrderedDict()
              for score in task_score_names[task]:
                     _lowerCamelCase :	Union[str, Any]						=scores[score]
              result.update(snake_case__  )
              results.append(snake_case__  )

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

       _lowerCamelCase :	List[Any]						=sorted(snake_case__	,    key=operator.itemgetter(*task_score_names[task]  )	,    reverse=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 :	List[Any]						=results_sorted[0]
       for score in task_score_names[task]:
              del best[score]
       _lowerCamelCase :	Dict						=[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()






from __future__ import annotations

from collections.abc import Generator




def 			a_   (					SCREAMING_SNAKE_CASE__      :   int  ):
       '''simple docstring'''





       if not isinstance(SCREAMING_SNAKE_CASE__	,    SCREAMING_SNAKE_CASE__  ) or n < 1:
              raise Exception('Sequence only defined for positive integers'  )

       yield n
       while n != 1:
              if n % 2 == 0:
                     n //= 2
              else:
                     _lowerCamelCase :	Optional[int]						=3 * n + 1
              yield n




def 			a_   (					):
       '''simple docstring'''





       _lowerCamelCase :	Dict						=43
       _lowerCamelCase :	Dict						=tuple(collatz_sequence(SCREAMING_SNAKE_CASE__  )  )
       print(SCREAMING_SNAKE_CASE__  )
       print(F'''Collatz sequence from {n} took {len(SCREAMING_SNAKE_CASE__  )} steps.'''  )


if __name__ == "__main__":
 main()


