
import warnings
from contextlib import contextmanager

from ....processing_utils import ProcessorMixin




class     _SCREAMING_SNAKE_CASE     (      snake_case_						):
	lowerCAmelCase__         = 'MCTCTFeatureExtractor'
	lowerCAmelCase__         = 'AutoTokenizer'



	def __init__(    self						,  lowercase						,  lowercase )				->       str:
					super().__init__(lowercase						,  lowercase )
					lowerCamelCase_						=			self.feature_extractor
					lowerCamelCase_						=			False



	def __call__(    self						,  *lowercase						,  **lowercase )				->       Dict:
					# For backward compatibility
					if self._in_target_context_manager:
									return self.current_processor(*lowercase						,  **lowercase )

					if "raw_speech" in kwargs:
									warnings.warn("Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead." )
									lowerCamelCase_						=			kwargs.pop("raw_speech" )
					else:
									lowerCamelCase_						=			kwargs.pop("audio"						,  lowercase )
					lowerCamelCase_						=			kwargs.pop("sampling_rate"						,  lowercase )
					lowerCamelCase_						=			kwargs.pop("text"						,  lowercase )
					if len(lowercase ) > 0:
									lowerCamelCase_						=			args[0]
									lowerCamelCase_						=			args[1:]

					if audio is None and text is None:
									raise ValueError("You need to specify either an `audio` or `text` input to process." )

					if audio is not None:
									lowerCamelCase_						=			self.feature_extractor(lowercase						,  *lowercase						,  sampling_rate=lowercase						,  **lowercase )
					if text is not None:
									lowerCamelCase_						=			self.tokenizer(lowercase						,  **lowercase )

					if text is None:
									return inputs
					elif audio is None:
									return encodings
					else:
									lowerCamelCase_						=			encodings["input_ids"]
									return inputs



	def     SCREAMING_SNAKE_CASE_(    self						,  *lowercase						,  **lowercase )				->       List[Any]:
					return self.tokenizer.batch_decode(*lowercase						,  **lowercase )



	def     SCREAMING_SNAKE_CASE_(    self						,  *lowercase						,  **lowercase )				->       List[str]:
					# For backward compatibility
					if self._in_target_context_manager:
									return self.current_processor.pad(*lowercase						,  **lowercase )

					lowerCamelCase_						=			kwargs.pop("input_features"						,  lowercase )
					lowerCamelCase_						=			kwargs.pop("labels"						,  lowercase )
					if len(lowercase ) > 0:
									lowerCamelCase_						=			args[0]
									lowerCamelCase_						=			args[1:]

					if input_features is not None:
									lowerCamelCase_						=			self.feature_extractor.pad(lowercase						,  *lowercase						,  **lowercase )
					if labels is not None:
									lowerCamelCase_						=			self.tokenizer.pad(lowercase						,  **lowercase )

					if labels is None:
									return input_features
					elif input_features is None:
									return labels
					else:
									lowerCamelCase_						=			labels["input_ids"]
									return input_features



	def     SCREAMING_SNAKE_CASE_(    self						,  *lowercase						,  **lowercase )				->       int:
					return self.tokenizer.decode(*lowercase						,  **lowercase )



	@contextmanager
	def     SCREAMING_SNAKE_CASE_(    self )				->       str:
					warnings.warn(
					    "`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your "
					    "labels by using the argument `text` of the regular `__call__` method (either in the same call as "
					    "your audio inputs, or in a separate call." )
					lowerCamelCase_						=			True
					lowerCamelCase_						=			self.tokenizer
					yield
					lowerCamelCase_						=			self.feature_extractor
					lowerCamelCase_						=			False




import math





def 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__ = 0	, lowerCamelCase__ = 0    ):
				lowerCamelCase_						=			end or len(lowerCamelCase__    )
				for i in range(lowerCamelCase__	, lowerCamelCase__    ):
								lowerCamelCase_						=			i
								lowerCamelCase_						=			array[i]
								while temp_index != start and temp_index_value < array[temp_index - 1]:
												lowerCamelCase_						=			array[temp_index - 1]
												temp_index -= 1
								lowerCamelCase_						=			temp_index_value
				return array





def 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    ):  # Max Heap
				lowerCamelCase_						=			index
				lowerCamelCase_						=			2 * index + 1  # Left Node
				lowerCamelCase_						=			2 * index + 2  # Right Node

				if left_index < heap_size and array[largest] < array[left_index]:
								lowerCamelCase_						=			left_index

				if right_index < heap_size and array[largest] < array[right_index]:
								lowerCamelCase_						=			right_index

				if largest != index:
								lowerCamelCase_	,    lowerCamelCase_						=			array[largest], array[index]
								heapify(lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    )





def 			lowerCamelCase_ (				lowerCamelCase__    ):
				lowerCamelCase_						=			len(lowerCamelCase__    )

				for i in range(n // 2	, -1	, -1    ):
								heapify(lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    )

				for i in range(n - 1	, 0	, -1    ):
								lowerCamelCase_	,    lowerCamelCase_						=			array[0], array[i]
								heapify(lowerCamelCase__	, 0	, lowerCamelCase__    )

				return array





def 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    ):
				if (array[first_index] > array[middle_index]) != (
				    array[first_index] > array[last_index]
				):
								return array[first_index]
				elif (array[middle_index] > array[first_index]) != (
				    array[middle_index] > array[last_index]
				):
								return array[middle_index]
				else:
								return array[last_index]





def 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    ):
				lowerCamelCase_						=			low
				lowerCamelCase_						=			high
				while True:
								while array[i] < pivot:
												i += 1
								j -= 1
								while pivot < array[j]:
												j -= 1
								if i >= j:
												return i
								lowerCamelCase_	,    lowerCamelCase_						=			array[j], array[i]
								i += 1





def 			lowerCamelCase_ (				lowerCamelCase__    ):
				if len(lowerCamelCase__    ) == 0:
								return array
				lowerCamelCase_						=			2 * math.ceil(math.loga(len(lowerCamelCase__    )    )    )
				lowerCamelCase_						=			1_6
				return intro_sort(lowerCamelCase__	, 0	, len(lowerCamelCase__    )	, lowerCamelCase__	, lowerCamelCase__    )





def 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    ):
				while end - start > size_threshold:
								if max_depth == 0:
												return heap_sort(lowerCamelCase__    )
								max_depth -= 1
								lowerCamelCase_						=			median_of_a(lowerCamelCase__	, lowerCamelCase__	, start + ((end - start) // 2) + 1	, end - 1    )
								lowerCamelCase_						=			partition(lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    )
								intro_sort(lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    )
								lowerCamelCase_						=			p
				return insertion_sort(lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    )


if __name__ == "__main__":
			import doctest

			doctest.testmod()

			__A				=input('''Enter numbers separated by a comma : ''').strip()
			__A				=[float(item) for item in user_input.split(''',''')]
			print(sort(unsorted))


