


'''simple docstring'''

from __future__ import annotations

from math import pi, pow



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					int | float )		->       float:





   '''simple docstring'''







   if side_length < 0:
      raise ValueError("vol_cube() only accepts non-negative values" )
   return pow(_UpperCamelCase     ,		3 )



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if height < 0 or radius < 0:
      raise ValueError("vol_spherical_cap() only accepts non-negative values" )
   # Volume is 1/3 pi * height squared * (3 * radius - height)
   return 1 / 3 * pi * pow(_UpperCamelCase     ,		2 ) * (3 * radius - height)



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if radius_a < 0 or radius_a < 0 or centers_distance < 0:
      raise ValueError("vol_spheres_intersect() only accepts non-negative values" )
   if centers_distance == 0:
      return vol_sphere(min(_UpperCamelCase     ,		_UpperCamelCase ) )

   UpperCamelCase__			    =    (
       (radius_a - radius_a + centers_distance)
       * (radius_a + radius_a - centers_distance)
       / (2 * centers_distance)
   )
   UpperCamelCase__			    =    (
       (radius_a - radius_a + centers_distance)
       * (radius_a + radius_a - centers_distance)
       / (2 * centers_distance)
   )

   return vol_spherical_cap(_UpperCamelCase     ,		_UpperCamelCase ) + vol_spherical_cap(_UpperCamelCase     ,		_UpperCamelCase )



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if radius_a <= 0 or radius_a <= 0 or centers_distance < 0:
      raise ValueError(
          "vol_spheres_union() only accepts non-negative values, non-zero radius" )

   if centers_distance == 0:
      return vol_sphere(max(_UpperCamelCase     ,		_UpperCamelCase ) )

   return (
       vol_sphere(_UpperCamelCase )
       + vol_sphere(_UpperCamelCase )
       - vol_spheres_intersect(_UpperCamelCase     ,		_UpperCamelCase     ,		_UpperCamelCase )
   )



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if width < 0 or height < 0 or length < 0:
      raise ValueError("vol_cuboid() only accepts non-negative values" )
   return float(width * height * length )



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if height < 0 or area_of_base < 0:
      raise ValueError("vol_cone() only accepts non-negative values" )
   return area_of_base * height / 3.0



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if height < 0 or radius < 0:
      raise ValueError("vol_right_circ_cone() only accepts non-negative values" )
   return pi * pow(_UpperCamelCase     ,		2 ) * height / 3.0



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if height < 0 or area_of_base < 0:
      raise ValueError("vol_prism() only accepts non-negative values" )
   return float(area_of_base * height )



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if height < 0 or area_of_base < 0:
      raise ValueError("vol_pyramid() only accepts non-negative values" )
   return area_of_base * height / 3.0



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if radius < 0:
      raise ValueError("vol_sphere() only accepts non-negative values" )
   # Volume is 4/3 * pi * radius cubed
   return 4 / 3 * pi * pow(_UpperCamelCase     ,		3 )



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if radius < 0:
      raise ValueError("vol_hemisphere() only accepts non-negative values" )
   # Volume is radius cubed * pi * 2/3
   return pow(_UpperCamelCase     ,		3 ) * pi * 2 / 3



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if height < 0 or radius < 0:
      raise ValueError("vol_circular_cylinder() only accepts non-negative values" )
   # Volume is radius squared * height * pi
   return pow(_UpperCamelCase     ,		2 ) * height * pi



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if inner_radius < 0 or outer_radius < 0 or height < 0:
      raise ValueError(
          "vol_hollow_circular_cylinder() only accepts non-negative values" )
   if outer_radius <= inner_radius:
      raise ValueError("outer_radius must be greater than inner_radius" )
   return pi * (pow(_UpperCamelCase     ,		2 ) - pow(_UpperCamelCase     ,		2 )) * height



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if radius_a < 0 or radius_a < 0 or height < 0:
      raise ValueError("vol_conical_frustum() only accepts non-negative values" )
   return (
       1
       / 3
       * pi
       * height
       * (pow(_UpperCamelCase     ,		2 ) + pow(_UpperCamelCase     ,		2 ) + radius_a * radius_a)
   )



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					float     ,		_UpperCamelCase   :					float )		->       float:





   '''simple docstring'''







   if torus_radius < 0 or tube_radius < 0:
      raise ValueError("vol_torus() only accepts non-negative values" )
   return 2 * pow(_UpperCamelCase     ,		2 ) * torus_radius * pow(_UpperCamelCase     ,		2 )



def 							SCREAMING_SNAKE_CASE__(		)		->       int:





   '''simple docstring'''







   print("Volumes:" )
   print(F'Cube: {vol_cube(2 ) = }' )  # = 8
   print(F'Cuboid: {vol_cuboid(2     ,		2     ,		2 ) = }' )  # = 8
   print(F'Cone: {vol_cone(2     ,		2 ) = }' )  # ~= 1.33
   print(F'Right Circular Cone: {vol_right_circ_cone(2     ,		2 ) = }' )  # ~= 8.38
   print(F'Prism: {vol_prism(2     ,		2 ) = }' )  # = 4
   print(F'Pyramid: {vol_pyramid(2     ,		2 ) = }' )  # ~= 1.33
   print(F'Sphere: {vol_sphere(2 ) = }' )  # ~= 33.5
   print(F'Hemisphere: {vol_hemisphere(2 ) = }' )  # ~= 16.75
   print(F'Circular Cylinder: {vol_circular_cylinder(2     ,		2 ) = }' )  # ~= 25.1
   print(F'Torus: {vol_torus(2     ,		2 ) = }' )  # ~= 157.9
   print(F'Conical Frustum: {vol_conical_frustum(2     ,		2     ,		4 ) = }' )  # ~= 58.6
   print(F'Spherical cap: {vol_spherical_cap(1     ,		2 ) = }' )  # ~= 5.24
   print(F'Spheres intersetion: {vol_spheres_intersect(2     ,		2     ,		1 ) = }' )  # ~= 21.21
   print(F'Spheres union: {vol_spheres_union(2     ,		2     ,		1 ) = }' )  # ~= 45.81
   print(
       F'Hollow Circular Cylinder: {vol_hollow_circular_cylinder(1     ,		2     ,		3 ) = }' )  # ~= 28.3


if __name__ == "__main__":
       main()




import json
import os
import shutil
import tempfile
import unittest

from transformers import is_speech_available, is_torch_available
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_torch
from transformers.utils import FEATURE_EXTRACTOR_NAME


if is_speech_available() and is_torch_available():
	from transformers import SpeechTaFeatureExtractor, SpeechTaProcessor

	from .test_feature_extraction_speechta import floats_list


A__       =			get_tests_dir("""fixtures/test_sentencepiece_bpe_char.model""")





@require_torch
class    __lowerCAmelCase					(	unittest.TestCase			):




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       tempfile.mkdtemp()

									_lowerCAmelCase         =       SpeechTaTokenizer(_snake_case						)
									tokenizer.save_pretrained(self.tmpdirname						)

									_lowerCAmelCase         =       {
									    """feature_size""": 1,
									    """padding_value""": 0.0,
									    """sampling_rate""": 16000,
									    """do_normalize""": False,
									    """num_mel_bins""": 80,
									    """hop_length""": 16,
									    """win_length""": 64,
									    """win_function""": """hann_window""",
									    """fmin""": 80,
									    """fmax""": 7600,
									    """mel_floor""": 1e-10,
									    """reduction_factor""": 2,
									    """return_attention_mask""": True,
									}

									_lowerCAmelCase         =       os.path.join(self.tmpdirname		,							_snake_case						)
									with open(self.feature_extraction_file		,							"""w"""		,							encoding="""utf-8"""						) as fp:
														fp.write(json.dumps(_snake_case						) + """\n"""						)




				def 				snake_case  (				self		,							**_snake_case						):



									"""simple docstring"""





									return SpeechTaTokenizer.from_pretrained(self.tmpdirname		,							**_snake_case						)




				def 				snake_case  (				self		,							**_snake_case						):



									"""simple docstring"""





									return SpeechTaFeatureExtractor.from_pretrained(self.tmpdirname		,							**_snake_case						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									shutil.rmtree(self.tmpdirname						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       self.get_tokenizer()
									_lowerCAmelCase         =       self.get_feature_extractor()

									_lowerCAmelCase         =       SpeechTaProcessor(tokenizer=_snake_case		,							feature_extractor=_snake_case						)

									processor.save_pretrained(self.tmpdirname						)
									_lowerCAmelCase         =       SpeechTaProcessor.from_pretrained(self.tmpdirname						)

									self.assertEqual(processor.tokenizer.get_vocab()		,							tokenizer.get_vocab()						)
									self.assertIsInstance(processor.tokenizer		,							_snake_case						)

									self.assertEqual(processor.feature_extractor.to_json_string()		,							feature_extractor.to_json_string()						)
									self.assertIsInstance(processor.feature_extractor		,							_snake_case						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       SpeechTaProcessor(tokenizer=self.get_tokenizer()		,							feature_extractor=self.get_feature_extractor()						)
									processor.save_pretrained(self.tmpdirname						)

									_lowerCAmelCase         =       self.get_tokenizer(bos_token="""(BOS)"""		,							eos_token="""(EOS)"""						)
									_lowerCAmelCase         =       self.get_feature_extractor(do_normalize=_snake_case		,							padding_value=1.0						)

									_lowerCAmelCase         =       SpeechTaProcessor.from_pretrained(
									    self.tmpdirname		,							bos_token="""(BOS)"""		,							eos_token="""(EOS)"""		,							do_normalize=_snake_case		,							padding_value=1.0						)

									self.assertEqual(processor.tokenizer.get_vocab()		,							tokenizer_add_kwargs.get_vocab()						)
									self.assertIsInstance(processor.tokenizer		,							_snake_case						)

									self.assertEqual(processor.feature_extractor.to_json_string()		,							feature_extractor_add_kwargs.to_json_string()						)
									self.assertIsInstance(processor.feature_extractor		,							_snake_case						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       self.get_feature_extractor()
									_lowerCAmelCase         =       self.get_tokenizer()

									_lowerCAmelCase         =       SpeechTaProcessor(tokenizer=_snake_case		,							feature_extractor=_snake_case						)

									_lowerCAmelCase         =       floats_list((3, 1000)						)

									_lowerCAmelCase         =       feature_extractor(audio=_snake_case		,							return_tensors="""np"""						)
									_lowerCAmelCase         =       processor(audio=_snake_case		,							return_tensors="""np"""						)

									for key in input_feat_extract.keys():
														self.assertAlmostEqual(input_feat_extract[key].sum()		,							input_processor[key].sum()		,							delta=1e-2						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       self.get_feature_extractor()
									_lowerCAmelCase         =       self.get_tokenizer()

									_lowerCAmelCase         =       SpeechTaProcessor(tokenizer=_snake_case		,							feature_extractor=_snake_case						)

									_lowerCAmelCase         =       floats_list((3, 1000)						)

									_lowerCAmelCase         =       feature_extractor(audio_target=_snake_case		,							return_tensors="""np"""						)
									_lowerCAmelCase         =       processor(audio_target=_snake_case		,							return_tensors="""np"""						)

									for key in input_feat_extract.keys():
														self.assertAlmostEqual(input_feat_extract[key].sum()		,							input_processor[key].sum()		,							delta=1e-2						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       self.get_feature_extractor()
									_lowerCAmelCase         =       self.get_tokenizer()

									_lowerCAmelCase         =       SpeechTaProcessor(tokenizer=_snake_case		,							feature_extractor=_snake_case						)

									_lowerCAmelCase         =       """This is a test string"""

									_lowerCAmelCase         =       processor(text=_snake_case						)
									_lowerCAmelCase         =       tokenizer(_snake_case						)

									for key in encoded_tok.keys():
														self.assertListEqual(encoded_tok[key]		,							encoded_processor[key]						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       self.get_feature_extractor()
									_lowerCAmelCase         =       self.get_tokenizer()

									_lowerCAmelCase         =       SpeechTaProcessor(tokenizer=_snake_case		,							feature_extractor=_snake_case						)

									_lowerCAmelCase         =       """This is a test string"""

									_lowerCAmelCase         =       processor(text_target=_snake_case						)
									_lowerCAmelCase         =       tokenizer(_snake_case						)

									for key in encoded_tok.keys():
														self.assertListEqual(encoded_tok[key]		,							encoded_processor[key]						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       self.get_feature_extractor()
									_lowerCAmelCase         =       self.get_tokenizer()

									_lowerCAmelCase         =       SpeechTaProcessor(tokenizer=_snake_case		,							feature_extractor=_snake_case						)

									_lowerCAmelCase         =       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

									_lowerCAmelCase         =       processor.batch_decode(_snake_case						)
									_lowerCAmelCase         =       tokenizer.batch_decode(_snake_case						)

									self.assertListEqual(_snake_case		,							_snake_case						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       self.get_feature_extractor()
									_lowerCAmelCase         =       self.get_tokenizer()

									_lowerCAmelCase         =       SpeechTaProcessor(tokenizer=_snake_case		,							feature_extractor=_snake_case						)

									self.assertListEqual(
									    processor.model_input_names		,							feature_extractor.model_input_names		,							msg="""`processor` and `feature_extractor` model input names do not match"""		,							)



