





'''simple docstring'''







from collections import deque
from math import floor
from random import random
from time import time
class 							__SCREAMING_SNAKE_CASE    :






				"""simple docstring"""







				def __init__(    self	:   Union[str, Any]   ):
								_a				      =					{}




				def     UpperCamelCase__  (    self	:   Tuple   ,							__a	:   str   ,							__a	:   str   ,							__a	:   Dict=1   ):
								if self.graph.get(a_   ):
												if self.graph[u].count([w, v]   ) == 0:
																self.graph[u].append([w, v]   )
								else:
												_a				      =					[[w, v]]
								if not self.graph.get(a_   ):
												_a				      =					[]




				def     UpperCamelCase__  (    self	:   Optional[int]   ):
								return list(self.graph   )




				def     UpperCamelCase__  (    self	:   Tuple   ,							__a	:   Union[str, Any]   ,							__a	:   str   ):
								if self.graph.get(a_   ):
												for _ in self.graph[u]:
																if _[1] == v:
																				self.graph[u].remove(a_   )




				def     UpperCamelCase__  (    self	:   Union[str, Any]   ,							__a	:   Dict=-2   ,							__a	:   int=-1   ):
								if s == d:
												return []
								_a				      =					[]
								_a				      =					[]
								if s == -2:
												_a				      =					list(self.graph   )[0]
								stack.append(a_   )
								visited.append(a_   )
								_a				      =					s

								while True:
												# check if there is any non isolated nodes
												if len(self.graph[s]   ) != 0:
																_a				      =					s
																for node in self.graph[s]:
																				if visited.count(node[1]   ) < 1:
																								if node[1] == d:
																												visited.append(a_   )
																												return visited
																								else:
																												stack.append(node[1]   )
																												visited.append(node[1]   )
																												_a				      =					node[1]
																												break

            # check if all the children are visited
												if s == ss:
																stack.pop()
																if len(a_   ) != 0:
																				_a				      =					stack[len(a_   ) - 1]
												else:
																_a				      =					ss

												# check if se have reached the starting point
												if len(a_   ) == 0:
																return visited




				def     UpperCamelCase__  (    self	:   List[Any]   ,							__a	:   int=-1   ):
								if c == -1:
												_a				      =					floor(random() * 1_00_00   ) + 10
								for i in range(a_   ):
												# every vertex has max 100 edges
												for _ in range(floor(random() * 1_02   ) + 1   ):
																_a				      =					floor(random() * c   ) + 1
																if n != i:
																				self.add_pair(a_   ,							a_   ,							1   )




				def     UpperCamelCase__  (    self	:   str   ,							__a	:   List[Any]=-2   ):
								_a				      =					deque()
								_a				      =					[]
								if s == -2:
												_a				      =					list(self.graph   )[0]
								d.append(a_   )
								visited.append(a_   )
								while d:
												_a				      =					d.popleft()
												if len(self.graph[s]   ) != 0:
																for node in self.graph[s]:
																				if visited.count(node[1]   ) < 1:
																								d.append(node[1]   )
																								visited.append(node[1]   )
								return visited




				def     UpperCamelCase__  (    self	:   List[str]   ,							__a	:   str   ):
								_a				      =					0
								for x in self.graph:
												for y in self.graph[x]:
																if y[1] == u:
																				count += 1
								return count




				def     UpperCamelCase__  (    self	:   Optional[int]   ,							__a	:   List[Any]   ):
								return len(self.graph[u]   )




				def     UpperCamelCase__  (    self	:   Tuple   ,							__a	:   Any=-2   ):
								_a				      =					[]
								_a				      =					[]
								if s == -2:
												_a				      =					list(self.graph   )[0]
								stack.append(a_   )
								visited.append(a_   )
								_a				      =					s
								_a				      =					[]

								while True:
												# check if there is any non isolated nodes
												if len(self.graph[s]   ) != 0:
																_a				      =					s
																for node in self.graph[s]:
																				if visited.count(node[1]   ) < 1:
																								stack.append(node[1]   )
																								visited.append(node[1]   )
																								_a				      =					node[1]
																								break

            # check if all the children are visited
												if s == ss:
																sorted_nodes.append(stack.pop()   )
																if len(a_   ) != 0:
																				_a				      =					stack[len(a_   ) - 1]
												else:
																_a				      =					ss

												# check if se have reached the starting point
												if len(a_   ) == 0:
																return sorted_nodes




				def     UpperCamelCase__  (    self	:   List[Any]   ):
								_a				      =					[]
								_a				      =					[]
								_a				      =					list(self.graph   )[0]
								stack.append(a_   )
								visited.append(a_   )
								_a				      =					-2
								_a				      =					[]
								_a				      =					s
								_a				      =					False
								_a				      =					set()

								while True:
												# check if there is any non isolated nodes
												if len(self.graph[s]   ) != 0:
																_a				      =					s
																for node in self.graph[s]:
																				if (
																				    visited.count(node[1]   ) > 0
																				    and node[1] != parent
																				    and indirect_parents.count(node[1]   ) > 0
																				    and not on_the_way_back
																				):
																								_a				      =					len(a_   ) - 1
																								while len_stack >= 0:
																												if stack[len_stack] == node[1]:
																																anticipating_nodes.add(node[1]   )
																																break
																												else:
																																anticipating_nodes.add(stack[len_stack]   )
																																len_stack -= 1
																				if visited.count(node[1]   ) < 1:
																								stack.append(node[1]   )
																								visited.append(node[1]   )
																								_a				      =					node[1]
																								break

            # check if all the children are visited
												if s == ss:
																stack.pop()
																_a				      =					True
																if len(a_   ) != 0:
																				_a				      =					stack[len(a_   ) - 1]
												else:
																_a				      =					False
																indirect_parents.append(a_   )
																_a				      =					s
																_a				      =					ss

												# check if se have reached the starting point
												if len(a_   ) == 0:
																return list(a_   )




				def     UpperCamelCase__  (    self	:   Any   ):
								_a				      =					[]
								_a				      =					[]
								_a				      =					list(self.graph   )[0]
								stack.append(a_   )
								visited.append(a_   )
								_a				      =					-2
								_a				      =					[]
								_a				      =					s
								_a				      =					False
								_a				      =					set()

								while True:
												# check if there is any non isolated nodes
												if len(self.graph[s]   ) != 0:
																_a				      =					s
																for node in self.graph[s]:
																				if (
																				    visited.count(node[1]   ) > 0
																				    and node[1] != parent
																				    and indirect_parents.count(node[1]   ) > 0
																				    and not on_the_way_back
																				):
																								_a				      =					len(a_   ) - 1
																								while len_stack_minus_one >= 0:
																												if stack[len_stack_minus_one] == node[1]:
																																anticipating_nodes.add(node[1]   )
																																break
																												else:
																																return True
																				if visited.count(node[1]   ) < 1:
																								stack.append(node[1]   )
																								visited.append(node[1]   )
																								_a				      =					node[1]
																								break

            # check if all the children are visited
												if s == ss:
																stack.pop()
																_a				      =					True
																if len(a_   ) != 0:
																				_a				      =					stack[len(a_   ) - 1]
												else:
																_a				      =					False
																indirect_parents.append(a_   )
																_a				      =					s
																_a				      =					ss

												# check if se have reached the starting point
												if len(a_   ) == 0:
																return False




				def     UpperCamelCase__  (    self	:   Tuple   ,							__a	:   Any=-2   ,							__a	:   Union[str, Any]=-1   ):
								_a				      =					time()
								self.dfs(a_   ,							a_   )
								_a				      =					time()
								return end - begin




				def     UpperCamelCase__  (    self	:   List[str]   ,							__a	:   Optional[Any]=-2   ):
								_a				      =					time()
								self.bfs(a_   )
								_a				      =					time()
								return end - begin


class 							__SCREAMING_SNAKE_CASE    :






				"""simple docstring"""







				def __init__(    self	:   Union[str, Any]   ):
								_a				      =					{}




				def     UpperCamelCase__  (    self	:   Tuple   ,							__a	:   str   ,							__a	:   str   ,							__a	:   Any=1   ):
								# check if the u exists
								if self.graph.get(a_   ):
												# if there already is a edge
												if self.graph[u].count([w, v]   ) == 0:
																self.graph[u].append([w, v]   )
								else:
												# if u does not exist
												_a				      =					[[w, v]]
								# add the other way
								if self.graph.get(a_   ):
												# if there already is a edge
												if self.graph[v].count([w, u]   ) == 0:
																self.graph[v].append([w, u]   )
								else:
												# if u does not exist
												_a				      =					[[w, u]]




				def     UpperCamelCase__  (    self	:   List[str]   ,							__a	:   Any   ,							__a	:   Any   ):
								if self.graph.get(a_   ):
												for _ in self.graph[u]:
																if _[1] == v:
																				self.graph[u].remove(a_   )
        # the other way round
								if self.graph.get(a_   ):
												for _ in self.graph[v]:
																if _[1] == u:
																				self.graph[v].remove(a_   )




				def     UpperCamelCase__  (    self	:   List[Any]   ,							__a	:   Optional[Any]=-2   ,							__a	:   str=-1   ):
								if s == d:
												return []
								_a				      =					[]
								_a				      =					[]
								if s == -2:
												_a				      =					list(self.graph   )[0]
								stack.append(a_   )
								visited.append(a_   )
								_a				      =					s

								while True:
												# check if there is any non isolated nodes
												if len(self.graph[s]   ) != 0:
																_a				      =					s
																for node in self.graph[s]:
																				if visited.count(node[1]   ) < 1:
																								if node[1] == d:
																												visited.append(a_   )
																												return visited
																								else:
																												stack.append(node[1]   )
																												visited.append(node[1]   )
																												_a				      =					node[1]
																												break

            # check if all the children are visited
												if s == ss:
																stack.pop()
																if len(a_   ) != 0:
																				_a				      =					stack[len(a_   ) - 1]
												else:
																_a				      =					ss

												# check if se have reached the starting point
												if len(a_   ) == 0:
																return visited




				def     UpperCamelCase__  (    self	:   List[str]   ,							__a	:   Tuple=-1   ):
								if c == -1:
												_a				      =					floor(random() * 1_00_00   ) + 10
								for i in range(a_   ):
												# every vertex has max 100 edges
												for _ in range(floor(random() * 1_02   ) + 1   ):
																_a				      =					floor(random() * c   ) + 1
																if n != i:
																				self.add_pair(a_   ,							a_   ,							1   )




				def     UpperCamelCase__  (    self	:   Union[str, Any]   ,							__a	:   List[Any]=-2   ):
								_a				      =					deque()
								_a				      =					[]
								if s == -2:
												_a				      =					list(self.graph   )[0]
								d.append(a_   )
								visited.append(a_   )
								while d:
												_a				      =					d.popleft()
												if len(self.graph[s]   ) != 0:
																for node in self.graph[s]:
																				if visited.count(node[1]   ) < 1:
																								d.append(node[1]   )
																								visited.append(node[1]   )
								return visited




				def     UpperCamelCase__  (    self	:   Union[str, Any]   ,							__a	:   Optional[Any]   ):
								return len(self.graph[u]   )




				def     UpperCamelCase__  (    self	:   Union[str, Any]   ):
								_a				      =					[]
								_a				      =					[]
								_a				      =					list(self.graph   )[0]
								stack.append(a_   )
								visited.append(a_   )
								_a				      =					-2
								_a				      =					[]
								_a				      =					s
								_a				      =					False
								_a				      =					set()

								while True:
												# check if there is any non isolated nodes
												if len(self.graph[s]   ) != 0:
																_a				      =					s
																for node in self.graph[s]:
																				if (
																				    visited.count(node[1]   ) > 0
																				    and node[1] != parent
																				    and indirect_parents.count(node[1]   ) > 0
																				    and not on_the_way_back
																				):
																								_a				      =					len(a_   ) - 1
																								while len_stack >= 0:
																												if stack[len_stack] == node[1]:
																																anticipating_nodes.add(node[1]   )
																																break
																												else:
																																anticipating_nodes.add(stack[len_stack]   )
																																len_stack -= 1
																				if visited.count(node[1]   ) < 1:
																								stack.append(node[1]   )
																								visited.append(node[1]   )
																								_a				      =					node[1]
																								break

            # check if all the children are visited
												if s == ss:
																stack.pop()
																_a				      =					True
																if len(a_   ) != 0:
																				_a				      =					stack[len(a_   ) - 1]
												else:
																_a				      =					False
																indirect_parents.append(a_   )
																_a				      =					s
																_a				      =					ss

												# check if se have reached the starting point
												if len(a_   ) == 0:
																return list(a_   )




				def     UpperCamelCase__  (    self	:   Dict   ):
								_a				      =					[]
								_a				      =					[]
								_a				      =					list(self.graph   )[0]
								stack.append(a_   )
								visited.append(a_   )
								_a				      =					-2
								_a				      =					[]
								_a				      =					s
								_a				      =					False
								_a				      =					set()

								while True:
												# check if there is any non isolated nodes
												if len(self.graph[s]   ) != 0:
																_a				      =					s
																for node in self.graph[s]:
																				if (
																				    visited.count(node[1]   ) > 0
																				    and node[1] != parent
																				    and indirect_parents.count(node[1]   ) > 0
																				    and not on_the_way_back
																				):
																								_a				      =					len(a_   ) - 1
																								while len_stack_minus_one >= 0:
																												if stack[len_stack_minus_one] == node[1]:
																																anticipating_nodes.add(node[1]   )
																																break
																												else:
																																return True
																				if visited.count(node[1]   ) < 1:
																								stack.append(node[1]   )
																								visited.append(node[1]   )
																								_a				      =					node[1]
																								break

            # check if all the children are visited
												if s == ss:
																stack.pop()
																_a				      =					True
																if len(a_   ) != 0:
																				_a				      =					stack[len(a_   ) - 1]
												else:
																_a				      =					False
																indirect_parents.append(a_   )
																_a				      =					s
																_a				      =					ss

												# check if se have reached the starting point
												if len(a_   ) == 0:
																return False




				def     UpperCamelCase__  (    self	:   List[Any]   ):
								return list(self.graph   )




				def     UpperCamelCase__  (    self	:   Union[str, Any]   ,							__a	:   str=-2   ,							__a	:   Any=-1   ):
								_a				      =					time()
								self.dfs(a_   ,							a_   )
								_a				      =					time()
								return end - begin




				def     UpperCamelCase__  (    self	:   List[Any]   ,							__a	:   Union[str, Any]=-2   ):
								_a				      =					time()
								self.bfs(a_   )
								_a				      =					time()
								return end - begin





'''simple docstring'''

import itertools
import os
import random
import tempfile
import unittest

import numpy as np

from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available

from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin


if is_torch_available():
	import torch

if is_datasets_available():
	from datasets import load_dataset

a							   =				random.Random()







def a_     (    __UpperCAmelCase				,							__UpperCAmelCase=1.0				,							__UpperCAmelCase=None				,							__UpperCAmelCase=None					)				->					List[str]:





			"""simple docstring"""







			if rng is None:
						snake_case:    Dict      							=global_rng

			snake_case:    Tuple      							=[]
			for batch_idx in range(shape[0]					):
						values.append([]					)
						for _ in range(shape[1]					):
									values[-1].append(rng.random() * scale					)

			return values






class 						a_		(     unittest.TestCase    ):


							def __init__(				self   :						int      ,						a_   :						Any      ,						a_   :						str=7      ,						a_   :						Tuple=4_0_0      ,						a_   :						List[Any]=2_0_0_0      ,						a_   :						str=2_0_4_8      ,						a_   :						List[str]=1_2_8      ,						a_   :						int=1      ,						a_   :						Tuple=5_1_2      ,						a_   :						Dict=3_0      ,						a_   :						Optional[int]=4_4_1_0_0      ,						)			->					Union[str, Any]:
										snake_case:    Union[str, Any]      							=parent
										snake_case:    Optional[Any]      							=batch_size
										snake_case:    Union[str, Any]      							=min_seq_length
										snake_case:    List[str]      							=max_seq_length
										snake_case:    str      							=(self.max_seq_length - self.min_seq_length) // (self.batch_size - 1)
										snake_case:    int      							=spectrogram_length
										snake_case:    List[str]      							=feature_size
										snake_case:    Dict      							=num_audio_channels
										snake_case:    int      							=hop_length
										snake_case:    List[Any]      							=chunk_length
										snake_case:    Optional[Any]      							=sampling_rate


							def    UpperCamelCase     (				self   :						Any			)			->					Dict:
										return {
										    "spectrogram_length": self.spectrogram_length,
										    "feature_size": self.feature_size,
										    "num_audio_channels": self.num_audio_channels,
										    "hop_length": self.hop_length,
										    "chunk_length": self.chunk_length,
										    "sampling_rate": self.sampling_rate,
										}




							def    UpperCamelCase     (				self   :						Tuple      ,						a_   :						Optional[Any]=False      ,						a_   :						Tuple=False			)			->					Optional[int]:
										def _flatten(a_   :						Dict			):
													return list(itertools.chain(*a_			)			)

										if equal_length:
													snake_case:    Union[str, Any]      							=[floats_list((self.max_seq_length, self.feature_size)			) for _ in range(self.batch_size			)]
										else:
													# make sure that inputs increase in size
													snake_case:    Union[str, Any]      							=[
													    floats_list((x, self.feature_size)			)
													    for x in range(self.min_seq_length      ,						self.max_seq_length      ,						self.seq_length_diff			)
													]
										if numpify:
													snake_case:    Any      							=[np.asarray(a_			) for x in speech_inputs]
										return speech_inputs






@require_torch
@require_torchaudio
class 						a_		(     snake_case    ,   unittest.TestCase    ):
							UpperCAmelCase			:		Optional[Any]        =				TvltFeatureExtractor


							def    UpperCamelCase     (				self   :						int			)			->					int:
										snake_case:    Union[str, Any]      							=TvltFeatureExtractionTester(self			)


							def    UpperCamelCase     (				self   :						Optional[Any]			)			->					str:
										snake_case:    int      							=self.feature_extraction_class(**self.feat_extract_dict			)
										self.assertTrue(hasattr(a_      ,						'spectrogram_length'			)			)
										self.assertTrue(hasattr(a_      ,						'feature_size'			)			)
										self.assertTrue(hasattr(a_      ,						'num_audio_channels'			)			)
										self.assertTrue(hasattr(a_      ,						'hop_length'			)			)
										self.assertTrue(hasattr(a_      ,						'chunk_length'			)			)
										self.assertTrue(hasattr(a_      ,						'sampling_rate'			)			)


							def    UpperCamelCase     (				self   :						Tuple			)			->					Optional[int]:
										snake_case:    Tuple      							=self.feature_extraction_class(**self.feat_extract_dict			)

										with tempfile.TemporaryDirectory() as tmpdirname:
													snake_case:    Optional[Any]      							=feat_extract_first.save_pretrained(a_			)[0]
													check_json_file_has_correct_format(a_			)
													snake_case:    str      							=self.feature_extraction_class.from_pretrained(a_			)

										snake_case:    Optional[int]      							=feat_extract_first.to_dict()
										snake_case:    List[str]      							=feat_extract_second.to_dict()
										snake_case:    Optional[int]      							=dict_first.pop('mel_filters'			)
										snake_case:    List[Any]      							=dict_second.pop('mel_filters'			)
										self.assertTrue(np.allclose(a_      ,						a_			)			)
										self.assertEqual(a_      ,						a_			)


							def    UpperCamelCase     (				self   :						str			)			->					str:
										snake_case:    Any      							=self.feature_extraction_class(**self.feat_extract_dict			)

										with tempfile.TemporaryDirectory() as tmpdirname:
													snake_case:    int      							=os.path.join(a_      ,						'feat_extract.json'			)
													feat_extract_first.to_json_file(a_			)
													snake_case:    Union[str, Any]      							=self.feature_extraction_class.from_json_file(a_			)

										snake_case:    Optional[Any]      							=feat_extract_first.to_dict()
										snake_case:    Optional[Any]      							=feat_extract_second.to_dict()
										snake_case:    Union[str, Any]      							=dict_first.pop('mel_filters'			)
										snake_case:    Union[str, Any]      							=dict_second.pop('mel_filters'			)
										self.assertTrue(np.allclose(a_      ,						a_			)			)
										self.assertEqual(a_      ,						a_			)


							def    UpperCamelCase     (				self   :						Union[str, Any]			)			->					List[str]:
										# Initialize feature_extractor
										snake_case:    Tuple      							=self.feature_extraction_class(**self.feat_extract_dict			)

										# create three inputs of length 800, 1000, and 1200
										snake_case:    Any      							=[floats_list((1, x)			)[0] for x in range(8_0_0      ,						1_4_0_0      ,						2_0_0			)]
										snake_case:    Optional[Any]      							=[np.asarray(a_			) for speech_input in speech_inputs]

										# Test not batched input
										snake_case:    List[Any]      							=feature_extractor(np_speech_inputs[0]      ,						return_tensors='np'      ,						sampling_rate=4_4_1_0_0			).audio_values

										self.assertTrue(encoded_audios.ndim == 4			)
										self.assertTrue(encoded_audios.shape[-1] == feature_extractor.feature_size			)
										self.assertTrue(encoded_audios.shape[-2] <= feature_extractor.spectrogram_length			)
										self.assertTrue(encoded_audios.shape[-3] == feature_extractor.num_channels			)

										# Test batched
										snake_case:    Any      							=feature_extractor(a_      ,						return_tensors='np'      ,						sampling_rate=4_4_1_0_0			).audio_values

										self.assertTrue(encoded_audios.ndim == 4			)
										self.assertTrue(encoded_audios.shape[-1] == feature_extractor.feature_size			)
										self.assertTrue(encoded_audios.shape[-2] <= feature_extractor.spectrogram_length			)
										self.assertTrue(encoded_audios.shape[-3] == feature_extractor.num_channels			)

										# Test audio masking
										snake_case:    Optional[Any]      							=feature_extractor(
										    a_      ,						return_tensors='np'      ,						sampling_rate=4_4_1_0_0      ,						mask_audio=a_			).audio_values

										self.assertTrue(encoded_audios.ndim == 4			)
										self.assertTrue(encoded_audios.shape[-1] == feature_extractor.feature_size			)
										self.assertTrue(encoded_audios.shape[-2] <= feature_extractor.spectrogram_length			)
										self.assertTrue(encoded_audios.shape[-3] == feature_extractor.num_channels			)

										# Test 2-D numpy arrays are batched.
										snake_case:    List[Any]      							=[floats_list((1, x)			)[0] for x in (8_0_0, 8_0_0, 8_0_0)]
										snake_case:    List[str]      							=np.asarray(a_			)
										snake_case:    str      							=feature_extractor(a_      ,						return_tensors='np'      ,						sampling_rate=4_4_1_0_0			).audio_values
										self.assertTrue(encoded_audios.ndim == 4			)
										self.assertTrue(encoded_audios.shape[-1] == feature_extractor.feature_size			)
										self.assertTrue(encoded_audios.shape[-2] <= feature_extractor.spectrogram_length			)
										self.assertTrue(encoded_audios.shape[-3] == feature_extractor.num_channels			)


							def    UpperCamelCase     (				self   :						Any      ,						a_   :						str			)			->					Union[str, Any]:
										snake_case:    Dict      							=load_dataset('hf-internal-testing/librispeech_asr_dummy'      ,						'clean'      ,						split='validation'			)
										# automatic decoding with librispeech
										snake_case:    Optional[int]      							=ds.sort('id'			).select(range(a_			)			)[:num_samples]['audio']

										return [x["array"] for x in speech_samples]




							def    UpperCamelCase     (				self   :						Optional[Any]			)			->					Optional[int]:
										snake_case:    Tuple      							=self._load_datasamples(1			)
										snake_case:    Any      							=TvltFeatureExtractor()
										snake_case:    Any      							=feature_extractor(a_      ,						return_tensors='pt'			).audio_values

										self.assertEquals(audio_values.shape      ,						(1, 1, 1_9_2, 1_2_8)			)

										snake_case:    int      							=torch.tensor([[-0.3_0_3_2, -0.2_7_0_8], [-0.4_4_3_4, -0.4_0_0_7]]			)
										self.assertTrue(torch.allclose(audio_values[0, 0, :2, :2]      ,						a_      ,						atol=1E-4			)			)




