


"""simple docstring"""






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  lowerCAmelCase_      (_SCREAMING_SNAKE_CASE	:List[Any]  )				-> Union[str, Any]:
						a_							:			Tuple     		=					search.split()
						a_							:			Optional[int]     		=					dict((g.split("="  ) for g in groups)  )
						a_							:			Optional[int]     		=					list(entries.keys()  )
						a_							:			int     		=					[[F'''--{k} {v}''' for v in vs.split(":"  )] for k, vs in entries.items()]
						a_							:			List[str]     		=					[list(__A  ) for x in itertools.product(*__A  )]
						return matrix, entry_names

def  lowerCAmelCase_      ()				-> int:
						a_							:			List[str]     		=					sys.argv[0]

						a_							:			int     		=					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=__A		,			required=__A		,			help="param space to search, e.g. \"num_beams=5:10 length_penalty=0.8:1.0:1.2\""		,			)
						parser.add_argument(
						    "--bs"		,			type=__A		,			default=8		,			required=__A		,			help="initial batch size (may get reduced if it's too big)"  )
						parser.add_argument("--task"		,			type=__A		,			help="used for task_specific_params + metrics"  )
						parser.add_argument(
						    "--info"		,			nargs="?"		,			type=__A		,			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."
						    )		,			)
						a_		,					a_							:			List[Any]     		=					parser.parse_known_args()
						# we share some of the args
						args_main.extend(["--task", args.task]  )
						a_							:			str     		=					[prog] + args_main

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

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

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

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

												# find widest entries
												for k, v in result.items():
																		a_							:			Optional[int]     		=					len(str(__A  )  )
																		if l > col_widths[k]:
																								a_							:			Tuple     		=					l

						a_							:			Optional[Any]     		=					sorted(__A		,			key=operator.itemgetter(*task_score_names[task]  )		,			reverse=__A  )
						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]  )  )

						a_							:			Tuple     		=					results_sorted[0]
						for score in task_score_names[task]:
												del best[score]
						a_							:			Union[str, Any]     		=					[F'''--{k} {v}''' for k, v in best.items()]
						a_							:			str     		=					["--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()





"""simple docstring"""






def  lowerCAmelCase_      (_SCREAMING_SNAKE_CASE	:int  )				-> Optional[int]:
						a_							:			List[Any]     		=					len(_SCREAMING_SNAKE_CASE  )
						for _ in range(
						    0		,			int(((no_of_elements - 1) / 2) + 1  )  ):  # we don't need to traverse to end of list as
												for j in range(0		,			no_of_elements - 1  ):
																		if (
																		    lst[j + 1] < lst[j]
																		):  # applying bubble sort algorithm from left to right (or forwards)
																								a_							:			List[str]     		=					lst[j + 1]
																								a_							:			Optional[Any]     		=					lst[j]
																								a_							:			Optional[Any]     		=					temp
																		if (
																		    lst[no_of_elements - 1 - j] < lst[no_of_elements - 2 - j]
																		):  # applying bubble sort algorithm from right to left (or backwards)
																								a_							:			Dict     		=					lst[no_of_elements - 1 - j]
																								a_							:			Dict     		=					lst[no_of_elements - 2 - j]
																								a_							:			Any     		=					temp
						return lst


if __name__ == "__main__":
				print('enter the list to be sorted')
				UpperCamelCase     					=     [int(x) for x in input().split()]  # inputing elements of the list in one line
				UpperCamelCase     					=     double_sort(lst)
				print('the sorted list is')
				print(sorted_lst)




