





'''simple docstring'''



def 				_lowerCAmelCase  (			lowerCamelCase_     :					Optional[int]			):
			# if the collection is empty, returns empty
			if collection == []:
						return []

			# get some information about the collection
			__lowercase			  =							len(lowerCamelCase_			)
			__lowercase			  =							max(lowerCamelCase_			)
			__lowercase			  =							min(lowerCamelCase_			)

			# create the counting array
			__lowercase			  =							coll_max + 1 - coll_min
			__lowercase			  =							[0] * counting_arr_length

			# count how much a number appears in the collection
			for number in collection:
						counting_arr[number - coll_min] += 1

			# sum each position with it's predecessors. now, counting_arr[i] tells
			# us how many elements <= i has in the collection
			for i in range(1						,    lowerCamelCase_			):
						__lowercase			  =							counting_arr[i] + counting_arr[i - 1]

			# create the output collection
			__lowercase			  =							[0] * coll_len

			# place the elements in the output, respecting the original order (stable
			# sort) from end to begin, updating counting_arr
			for i in reversed(range(0						,    lowerCamelCase_			)			):
						__lowercase			  =							collection[i]
						counting_arr[collection[i] - coll_min] -= 1

			return ordered




def 				_lowerCAmelCase  (			lowerCamelCase_     :					Dict			):
			return "".join([chr(lowerCamelCase_			) for i in counting_sort([ord(lowerCamelCase_			) for c in string]			)]			)


if __name__ == "__main__":
	# Test string sort
	assert counting_sort_string('''thisisthestring''') == "eghhiiinrsssttt"

	_SCREAMING_SNAKE_CASE   =      input('''Enter numbers separated by a comma:\n''').strip()
	_SCREAMING_SNAKE_CASE   =      [int(item) for item in user_input.split(''',''')]
	print(counting_sort(unsorted))












'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_SCREAMING_SNAKE_CASE   =      {
    '''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
    '''tokenization_mvp''': ['''MvpTokenizer'''],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE   =      ['''MvpTokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE   =      [
	    '''MVP_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''MvpForCausalLM''',
	    '''MvpForConditionalGeneration''',
	    '''MvpForQuestionAnswering''',
	    '''MvpForSequenceClassification''',
	    '''MvpModel''',
	    '''MvpPreTrainedModel''',
	]

if TYPE_CHECKING:
	from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
	from .tokenization_mvp import MvpTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_mvp_fast import MvpTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_mvp import (
		    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MvpForCausalLM,
		    MvpForConditionalGeneration,
		    MvpForQuestionAnswering,
		    MvpForSequenceClassification,
		    MvpModel,
		    MvpPreTrainedModel,
		)

else:
	import sys

	_SCREAMING_SNAKE_CASE   =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





