




from __future__ import annotations

import math







class 				lowerCAmelCase_       :






				def __init__(			self      ,snake_case__ ):
							SCREAMING_SNAKE_CASE_   : List[Any]					  =      size
							# approximate the overall size of segment tree with given value
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      [0 for i in range(0      ,4 * size )]
							# create array to store lazy update
							SCREAMING_SNAKE_CASE_   : List[Any]					  =      [0 for i in range(0      ,4 * size )]
							SCREAMING_SNAKE_CASE_   : Any					  =      [0 for i in range(0      ,4 * size )]  # flag for lazy update






				def 		snake_case	(			self      ,snake_case__ ):
							return idx * 2






				def 		snake_case	(			self      ,snake_case__ ):
							return idx * 2 + 1






				def 		snake_case	(			self      ,snake_case__      ,snake_case__      ,snake_case__      ,snake_case__ ):
							if left_element == right_element:
										SCREAMING_SNAKE_CASE_   : List[str]					  =      a[left_element - 1]
							else:
										SCREAMING_SNAKE_CASE_   : Optional[int]					  =      (left_element + right_element) // 2
										self.build(self.left(snake_case__ )      ,snake_case__      ,snake_case__      ,snake_case__ )
										self.build(self.right(snake_case__ )      ,mid + 1      ,snake_case__      ,snake_case__ )
										SCREAMING_SNAKE_CASE_   : List[str]					  =      max(
										    self.segment_tree[self.left(snake_case__ )]      ,self.segment_tree[self.right(snake_case__ )] )






				def 		snake_case	(			self      ,snake_case__      ,snake_case__      ,snake_case__      ,snake_case__      ,snake_case__      ,snake_case__ ):
							if self.flag[idx] is True:
										SCREAMING_SNAKE_CASE_   : int					  =      self.lazy[idx]
										SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      False
										if left_element != right_element:
													SCREAMING_SNAKE_CASE_   : List[Any]					  =      self.lazy[idx]
													SCREAMING_SNAKE_CASE_   : str					  =      self.lazy[idx]
													SCREAMING_SNAKE_CASE_   : Any					  =      True
													SCREAMING_SNAKE_CASE_   : List[Any]					  =      True

							if right_element < a or left_element > b:
										return True
							if left_element >= a and right_element <= b:
										SCREAMING_SNAKE_CASE_   : Tuple					  =      val
										if left_element != right_element:
													SCREAMING_SNAKE_CASE_   : Any					  =      val
													SCREAMING_SNAKE_CASE_   : Tuple					  =      val
													SCREAMING_SNAKE_CASE_   : Optional[int]					  =      True
													SCREAMING_SNAKE_CASE_   : List[Any]					  =      True
										return True
							SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      (left_element + right_element) // 2
							self.update(self.left(snake_case__ )      ,snake_case__      ,snake_case__      ,snake_case__      ,snake_case__      ,snake_case__ )
							self.update(self.right(snake_case__ )      ,mid + 1      ,snake_case__      ,snake_case__      ,snake_case__      ,snake_case__ )
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      max(
							    self.segment_tree[self.left(snake_case__ )]      ,self.segment_tree[self.right(snake_case__ )] )
							return True






				def 		snake_case	(			self      ,snake_case__      ,snake_case__      ,snake_case__      ,snake_case__      ,snake_case__ ):
							if self.flag[idx] is True:
										SCREAMING_SNAKE_CASE_   : str					  =      self.lazy[idx]
										SCREAMING_SNAKE_CASE_   : Tuple					  =      False
										if left_element != right_element:
													SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      self.lazy[idx]
													SCREAMING_SNAKE_CASE_   : Optional[int]					  =      self.lazy[idx]
													SCREAMING_SNAKE_CASE_   : str					  =      True
													SCREAMING_SNAKE_CASE_   : Optional[int]					  =      True
							if right_element < a or left_element > b:
										return -math.inf
							if left_element >= a and right_element <= b:
										return self.segment_tree[idx]
							SCREAMING_SNAKE_CASE_   : Any					  =      (left_element + right_element) // 2
							SCREAMING_SNAKE_CASE_   : int					  =      self.query(self.left(snake_case__ )      ,snake_case__      ,snake_case__      ,snake_case__      ,snake_case__ )
							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      self.query(self.right(snake_case__ )      ,mid + 1      ,snake_case__      ,snake_case__      ,snake_case__ )
							return max(snake_case__      ,snake_case__ )






				def __str__(			self ):
							return str([self.query(1      ,1      ,self.size      ,snake_case__      ,snake_case__ ) for i in range(1      ,self.size + 1 )] )


if __name__ == "__main__":
						UpperCamelCase__ :   str						=							[1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
						UpperCamelCase__ :   int						=							15
						UpperCamelCase__ :   str						=							SegmentTree(size)
						segt.build(1, 1, size, A)
						print(segt.query(1, 1, size, 4, 6))
						print(segt.query(1, 1, size, 7, 11))
						print(segt.query(1, 1, size, 7, 12))
						segt.update(1, 1, size, 1, 3, 1_11)
						print(segt.query(1, 1, size, 1, 15))
						segt.update(1, 1, size, 7, 8, 2_35)
						print(segt)






'''simple docstring'''

import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / '''utils'''))

from test_module.custom_feature_extraction import CustomFeatureExtractor  # noqa E402


UpperCAmelCase					 =	get_tests_dir('''fixtures''')


class 	lowerCAmelCase  (   unittest.TestCase ):







       def       snake_case (				self      :			str   ):







            """simple docstring"""







            __lowercase      		=mock.Mock()
            __lowercase      		=500
            __lowercase      		={}
            __lowercase      		=HTTPError
            __lowercase      		={}

            # Download this model to make sure it's in the cache.
            __lowercase      		=WavaVecaFeatureExtractor.from_pretrained('hf-internal-testing/tiny-random-wav2vec2'   )
            # Under the mock environment we get a 500 error when trying to reach the model.
            with mock.patch('requests.Session.request'    ,   return_value=__lowercase   ) as mock_head:
                 __lowercase      		=WavaVecaFeatureExtractor.from_pretrained('hf-internal-testing/tiny-random-wav2vec2'   )
                 # This check we did call the fake head request
                 mock_head.assert_called()







       def       snake_case (				self      :			Dict   ):







            """simple docstring"""







            __lowercase      		=WavaVecaFeatureExtractor.from_pretrained(
                'https://huggingface.co/hf-internal-testing/tiny-random-wav2vec2/resolve/main/preprocessor_config.json'   )






@is_staging_test
class 	lowerCAmelCase  (   unittest.TestCase ):







       @classmethod
       def       snake_case (				cls      :			str   ):







            """simple docstring"""







            __lowercase      		=TOKEN
            HfFolder.save_token(__lowercase   )







       @classmethod
       def       snake_case (				cls      :			str   ):







            """simple docstring"""







            try:
                 delete_repo(token=cls._token    ,   repo_id='test-feature-extractor'   )
            except HTTPError:
                 pass

            try:
                 delete_repo(token=cls._token    ,   repo_id='valid_org/test-feature-extractor-org'   )
            except HTTPError:
                 pass

            try:
                 delete_repo(token=cls._token    ,   repo_id='test-dynamic-feature-extractor'   )
            except HTTPError:
                 pass







       def       snake_case (				self      :			int   ):







            """simple docstring"""







            __lowercase      		=WavaVecaFeatureExtractor.from_pretrained(__lowercase   )
            feature_extractor.push_to_hub('test-feature-extractor'    ,   use_auth_token=self._token   )

            __lowercase      		=WavaVecaFeatureExtractor.from_pretrained(f'''{USER}/test-feature-extractor'''   )
            for k, v in feature_extractor.__dict__.items():
                 self.assertEqual(__lowercase    ,   getattr(__lowercase    ,   __lowercase   )   )

            # Reset repo
            delete_repo(token=self._token    ,   repo_id='test-feature-extractor'   )

            # Push to hub via save_pretrained
            with tempfile.TemporaryDirectory() as tmp_dir:
                 feature_extractor.save_pretrained(
                     __lowercase    ,   repo_id='test-feature-extractor'    ,   push_to_hub=__lowercase    ,   use_auth_token=self._token   )

            __lowercase      		=WavaVecaFeatureExtractor.from_pretrained(f'''{USER}/test-feature-extractor'''   )
            for k, v in feature_extractor.__dict__.items():
                 self.assertEqual(__lowercase    ,   getattr(__lowercase    ,   __lowercase   )   )







       def       snake_case (				self      :			List[Any]   ):







            """simple docstring"""







            __lowercase      		=WavaVecaFeatureExtractor.from_pretrained(__lowercase   )
            feature_extractor.push_to_hub('valid_org/test-feature-extractor'    ,   use_auth_token=self._token   )

            __lowercase      		=WavaVecaFeatureExtractor.from_pretrained('valid_org/test-feature-extractor'   )
            for k, v in feature_extractor.__dict__.items():
                 self.assertEqual(__lowercase    ,   getattr(__lowercase    ,   __lowercase   )   )

            # Reset repo
            delete_repo(token=self._token    ,   repo_id='valid_org/test-feature-extractor'   )

            # Push to hub via save_pretrained
            with tempfile.TemporaryDirectory() as tmp_dir:
                 feature_extractor.save_pretrained(
                     __lowercase    ,   repo_id='valid_org/test-feature-extractor-org'    ,   push_to_hub=__lowercase    ,   use_auth_token=self._token   )

            __lowercase      		=WavaVecaFeatureExtractor.from_pretrained('valid_org/test-feature-extractor-org'   )
            for k, v in feature_extractor.__dict__.items():
                 self.assertEqual(__lowercase    ,   getattr(__lowercase    ,   __lowercase   )   )







       def       snake_case (				self      :			Optional[Any]   ):







            """simple docstring"""







            CustomFeatureExtractor.register_for_auto_class()
            __lowercase      		=CustomFeatureExtractor.from_pretrained(__lowercase   )

            feature_extractor.push_to_hub('test-dynamic-feature-extractor'    ,   use_auth_token=self._token   )

            # This has added the proper auto_map field to the config
            self.assertDictEqual(
                feature_extractor.auto_map    ,   {'AutoFeatureExtractor': 'custom_feature_extraction.CustomFeatureExtractor'}    ,   )

            __lowercase      		=AutoFeatureExtractor.from_pretrained(
                f'''{USER}/test-dynamic-feature-extractor'''    ,   trust_remote_code=__lowercase   )
            # Can't make an isinstance check because the new_feature_extractor is from the CustomFeatureExtractor class of a dynamic module
            self.assertEqual(new_feature_extractor.__class__.__name__    ,   'CustomFeatureExtractor'   )


