


from __future__ import annotations




def 			_SCREAMING_SNAKE_CASE      (	_lowerCamelCase				:    str		,						_lowerCamelCase				:    str)      ->					bool:






							'''simple docstring'''





							__UpperCamelCase			:     Union[str, Any]         =      get_failure_array(_lowerCamelCase)

							# 2) Step through text searching for pattern
							__UpperCamelCase			:     Dict         =      0, 0  # index into text, pattern
							while i < len(_lowerCamelCase):
														if pattern[j] == text[i]:
																					if j == (len(_lowerCamelCase) - 1):
																												return True
																					j += 1

														# if this is a prefix in our pattern
														# just go back far enough to continue
														elif j > 0:
																					__UpperCamelCase			:     Optional[Any]         =      failure[j - 1]
																					continue
														i += 1
							return False




def 			_SCREAMING_SNAKE_CASE      (	_lowerCamelCase				:    str)      ->					list[int]:






							'''simple docstring'''





							__UpperCamelCase			:     int         =      [0]
							__UpperCamelCase			:     List[Any]         =      0
							__UpperCamelCase			:     Union[str, Any]         =      1
							while j < len(_lowerCamelCase):
														if pattern[i] == pattern[j]:
																					i += 1
														elif i > 0:
																					__UpperCamelCase			:     Dict         =      failure[i - 1]
																					continue
														j += 1
														failure.append(_lowerCamelCase)
							return failure


if __name__ == "__main__":
		# Test 1)
		lowercase						:      Optional[int]									= "abc1abc12"
		lowercase						:      Optional[int]									= "alskfjaldsabc1abc1abc12k23adsfabcabc"
		lowercase						:      List[Any]									= "alskfjaldsk23adsfabcabc"
		assert kmp(pattern, texta) and not kmp(pattern, texta)

		# Test 2)
		lowercase						:      List[Any]									= "ABABX"
		lowercase						:      List[Any]									= "ABABZABABYABABX"
		assert kmp(pattern, text)

		# Test 3)
		lowercase						:      Union[str, Any]									= "AAAB"
		lowercase						:      Union[str, Any]									= "ABAAAAAB"
		assert kmp(pattern, text)

		# Test 4)
		lowercase						:      Optional[int]									= "abcdabcy"
		lowercase						:      Union[str, Any]									= "abcxabcdabxabcdabcdabcy"
		assert kmp(pattern, text)

		# Test 5)
		lowercase						:      Tuple									= "aabaabaaa"
		assert get_failure_array(pattern) == [0, 1, 0, 1, 2, 3, 4, 5, 2]

import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict




@dataclass
class 				lowerCamelCase__							(       __lowercase):




	'''simple docstring'''




	_A			=  ComputeEnvironment.AMAZON_SAGEMAKER
	_A			=  True
	_A			=  'ml.p3.2xlarge'
	_A			=  'accelerate_sagemaker_execution_role'
	_A			=  'hf-sm'
	_A			=  'us-east-1'
	_A			=  1
	_A			=  'accelerate-sagemaker-1'
	_A			=  '1.6'
	_A			=  '4.4'
	_A			=  'train.py'
	_A			=  [
	    '--model_name_or_path',
	    'bert',
	    '--do_train',
	    'False',
	    '--epochs',
	    '3',
	    '--learning_rate',
	    '5e-5',
	    '--max_steps',
	    '50.5',
	]
	_A			=  [
	    '--model_name_or_path',
	    'bert',
	    '--do_train',
	    '--do_test',
	    'False',
	    '--do_predict',
	    '--epochs',
	    '3',
	    '--learning_rate',
	    '5e-5',
	    '--max_steps',
	    '50.5',
	]




class 				lowerCamelCase__							(       unittest.TestCase):




	'''simple docstring'''




	def      _lowerCamelCase       (      self	:Tuple		)	->				str:
								# If no defaults are changed, `to_kwargs` returns an empty dict.
								__UpperCamelCase			:     str         =      _convert_nargs_to_dict(MockLaunchConfig.success_training_script_args		)
								assert isinstance(converted_args["model_name_or_path"]  ,     a		)
								assert isinstance(converted_args["do_train"]  ,     a		)
								assert isinstance(converted_args["epochs"]  ,     a		)
								assert isinstance(converted_args["learning_rate"]  ,     a		)
								assert isinstance(converted_args["max_steps"]  ,     a		)

								with pytest.raises(a		):
															_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args		)