
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
_lowerCamelCase       :				Tuple       =			logging.getLogger()






def        a_		(       __lowercase   :	Path       ,					__lowercase   :	list ) ->  List[str]:
			_snake_case		=			'\n'.join(__lowercase )
			Path(__lowercase ).open('w' ).writelines(__lowercase )


_lowerCamelCase       :				Dict       =			'''patrickvonplaten/t5-tiny-random'''
_lowerCamelCase       :				Tuple       =			'''sshleifer/bart-tiny-random'''
_lowerCamelCase       :				Union[str, Any]       =			'''sshleifer/tiny-mbart'''

_lowerCamelCase       :				List[str]       =			logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks




class    SCREAMING_SNAKE_CASE__     (	UpperCAmelCase					):





	'''simple docstring'''



	def  A							(  self	:    str			,  lowercase	:    List[Any]	):


				'''simple docstring'''


				_snake_case		=			Path(self.get_auto_remove_tmp_dir()	) / 'utest_input.source'
				_snake_case		=			input_file_name.parent / 'utest_output.txt'
				assert not output_file_name.exists()
				_snake_case		=			[' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.']
				_dump_articles(lowercase			,  lowercase	)

				_snake_case		=			str(Path(self.get_auto_remove_tmp_dir()	) / 'scores.json'	)
				_snake_case		=			'translation_en_to_de' if model == T5_TINY else 'summarization'
				_snake_case		=			f'''
            run_eval_search.py
            {model}
            {input_file_name}
            {output_file_name}
            --score_path {score_path}
            --task {task}
            --num_beams 2
            --length_penalty 2.0
            '''.split()

				with patch.object(lowercase			,  'argv'			,  lowercase	):
							run_generate()
							assert Path(lowercase	).exists()
							# os.remove(Path(output_file_name))



	def  A							(  self	:    Tuple	):


				'''simple docstring'''


				self.run_eval_tester(lowercase	)



	@parameterized.expand([BART_TINY, MBART_TINY]	)
	@slow
	def  A							(  self	:    Optional[Any]			,  lowercase	:    Optional[Any]	):


				'''simple docstring'''


				self.run_eval_tester(lowercase	)





	@parameterized.expand([T5_TINY, MBART_TINY]	)
	@slow
	def  A							(  self	:    Optional[int]			,  lowercase	:    Any	):


				'''simple docstring'''


				_snake_case		=			Path(self.get_auto_remove_tmp_dir()	) / 'utest_input.source'
				_snake_case		=			input_file_name.parent / 'utest_output.txt'
				assert not output_file_name.exists()

				_snake_case		=			{
				    'en': ['Machine learning is great, isn\'t it?', 'I like to eat bananas', 'Tomorrow is another great day!'],
				    'de': [
				        'Maschinelles Lernen ist großartig, oder?',
				        'Ich esse gerne Bananen',
				        'Morgen ist wieder ein toller Tag!',
				    ],
				}

				_snake_case		=			Path(self.get_auto_remove_tmp_dir()	)
				_snake_case		=			str(tmp_dir / 'scores.json'	)
				_snake_case		=			str(tmp_dir / 'val.target'	)
				_dump_articles(lowercase			,  text['en']	)
				_dump_articles(lowercase			,  text['de']	)
				_snake_case		=			'translation_en_to_de' if model == T5_TINY else 'summarization'
				_snake_case		=			f'''
            run_eval_search.py
            {model}
            {str(lowercase	)}
            {str(lowercase	)}
            --score_path {score_path}
            --reference_path {reference_path}
            --task {task}
            '''.split()
				testargs.extend(['--search', 'num_beams=1:2 length_penalty=0.9:1.0']	)

				with patch.object(lowercase			,  'argv'			,  lowercase	):
							with CaptureStdout() as cs:
										run_search()
							_snake_case		=			[' num_beams | length_penalty', model, 'Best score args']
							_snake_case		=			['Info']
							if "translation" in task:
										expected_strings.append('bleu'	)
							else:
										expected_strings.extend(lowercase	)
							for w in expected_strings:
										assert w in cs.out
							for w in un_expected_strings:
										assert w not in cs.out
							assert Path(lowercase	).exists()
							os.remove(Path(lowercase	)	)

from __future__ import annotations

import time
from collections.abc import Sequence
from random import randint

from matplotlib import pyplot as plt






def        a_		(       __lowercase   :	Sequence[float]       ,					__lowercase   :	int       ,					__lowercase   :	int ) ->  tuple[int | None, int | None, float]:
			if not arr:
						return None, None, 0
			if low == high:
						return low, high, arr[low]

			_snake_case		=			(low + high) // 2
			_snake_case	,					_snake_case	,					_snake_case		=			max_subarray(__lowercase       ,					__lowercase       ,					__lowercase )
			_snake_case	,					_snake_case	,					_snake_case		=			max_subarray(__lowercase       ,					mid + 1       ,					__lowercase )
			_snake_case	,					_snake_case	,					_snake_case		=			max_cross_sum(__lowercase       ,					__lowercase       ,					__lowercase       ,					__lowercase )
			if left_sum >= right_sum and left_sum >= cross_sum:
						return left_low, left_high, left_sum
			elif right_sum >= left_sum and right_sum >= cross_sum:
						return right_low, right_high, right_sum
			return cross_left, cross_right, cross_sum






def        a_		(       __lowercase   :	Sequence[float]       ,					__lowercase   :	int       ,					__lowercase   :	int       ,					__lowercase   :	int ) ->  tuple[int, int, float]:
			_snake_case	,					_snake_case		=			float('-inf' ), -1
			_snake_case	,					_snake_case		=			float('-inf' ), -1

			_snake_case		=			0
			for i in range(__lowercase       ,					low - 1       ,					-1 ):
						summ += arr[i]
						if summ > left_sum:
									_snake_case		=			summ
									_snake_case		=			i

			_snake_case		=			0
			for i in range(mid + 1       ,					high + 1 ):
						summ += arr[i]
						if summ > right_sum:
									_snake_case		=			summ
									_snake_case		=			i

			return max_left, max_right, (left_sum + right_sum)






def        a_		(       __lowercase   :	int ) ->  float:
			_snake_case		=			[randint(1       ,					__lowercase ) for _ in range(__lowercase )]
			_snake_case		=			time.time()
			max_subarray(__lowercase       ,					0       ,					input_size - 1 )
			_snake_case		=			time.time()
			return end - start






def        a_		(       ) ->  None:
			_snake_case		=			[10, 100, 1_000, 10_000, 50_000, 100_000, 200_000, 300_000, 400_000, 500_000]
			_snake_case		=			[time_max_subarray(__lowercase ) for input_size in input_sizes]
			print('No of Inputs\t\tTime Taken' )
			for input_size, runtime in zip(__lowercase       ,					__lowercase ):
						print(__lowercase       ,					'\t\t'       ,					__lowercase )
			plt.plot(__lowercase       ,					__lowercase )
			plt.xlabel('Number of Inputs' )
			plt.ylabel('Time taken in seconds' )
			plt.show()


if __name__ == "__main__":
			from doctest import testmod

			testmod()