
'''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
lowerCAmelCase :  Optional[int]      =      {
    'translation': ['bleu'],
    'summarization': ROUGE_KEYS,
}







def 						A_(			A		:						Optional[Any]):
							UpperCamelCase					       =			search.split()
							UpperCamelCase					       =			dict((g.split('=') for g in groups))
							UpperCamelCase					       =			list(entries.keys())
							UpperCamelCase					       =			[[f'''--{k} {v}''' for v in vs.split(':')] for k, vs in entries.items()]
							UpperCamelCase					       =			[list(A) for x in itertools.product(*A)]
							return matrix, entry_names







def 						A_(			):
							UpperCamelCase					       =			sys.argv[0]

							UpperCamelCase					       =			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.'
							    )						,			)
							UpperCamelCase       ,     UpperCamelCase					       =			parser.parse_known_args()
							# we share some of the args
							args_main.extend(['--task', args.task])
							UpperCamelCase					       =			[prog] + args_main

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

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

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

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

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

							UpperCamelCase					       =			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]))

							UpperCamelCase					       =			results_sorted[0]
							for score in task_score_names[task]:
														del best[score]
							UpperCamelCase					       =			[f'''--{k} {v}''' for k, v in best.items()]
							UpperCamelCase					       =			['--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'''
from __future__ import annotations

from PIL import Image

# Define the first generation of cells
# fmt: off
lowerCAmelCase :  Union[str, Any]      =      [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]







def 						A_(			A		:						int):
							return [int(A) for c in f'''{ruleset:08}'''[:8]]







def 						A_(			A		:						list[list[int]]						,			A		:						list[int]						,			A		:						int):
							UpperCamelCase					       =			len(cells[0])  # 31
							UpperCamelCase					       =			[]
							for i in range(A):
														# Get the neighbors of each cell
														# Handle neighbours outside bounds by using 0 as their value
														UpperCamelCase					       =			0 if i == 0 else cells[time][i - 1]
														UpperCamelCase					       =			0 if i == population - 1 else cells[time][i + 1]
														# Define a new cell and add it to the new generation
														UpperCamelCase					       =			7 - int(f'''{left_neighbor}{cells[time][i]}{right_neighbor}'''						,			2)
														next_generation.append(rule[situation])
							return next_generation







def 						A_(			A		:						list[list[int]]):
							UpperCamelCase					       =			Image.new('RGB'						,			(len(cells[0]), len(A)))
							UpperCamelCase					       =			img.load()
							# Generates image
							for w in range(img.width):
														for h in range(img.height):
																					UpperCamelCase					       =			255 - int(255 * cells[h][w])
																					UpperCamelCase					       =			(color, color, color)
							return img


if __name__ == "__main__":
						lowerCAmelCase :  Optional[int]      =      bin(int(input('Rule:\n').strip()))[2:]
						lowerCAmelCase :  Tuple      =      format_ruleset(int(rule_num))
						for time in range(16):
												CELLS.append(new_generation(CELLS, rule, time))
						lowerCAmelCase :  List[str]      =      generate_image(CELLS)
						# Uncomment to save the image
						# img.save(f"rule_{rule_num}.png")
						img.show()




