

import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch

class     a__  (    unittest.TestCase	):
			"""simple docstring"""







			__lowerCamelCase       				=				JukeboxTokenizer
			__lowerCamelCase       				=				{
			    'artist': 'Zac Brown Band',
			    'genres': 'Country',
			    'lyrics': 'I met a traveller from an antique land,\n        Who said "Two vast and trunkless legs of stone\n        Stand in the desert. . . . Near them, on the sand,\n        Half sunk a shattered visage lies, whose frown,\n        And wrinkled lip, and sneer of cold command,\n        Tell that its sculptor well those passions read\n        Which yet survive, stamped on these lifeless things,\n        The hand that mocked them, and the heart that fed;\n        And on the pedestal, these words appear:\n        My name is Ozymandias, King of Kings;\n        Look on my Works, ye Mighty, and despair!\n        Nothing beside remains. Round the decay\n        Of that colossal Wreck, boundless and bare\n        The lone and level sands stretch far away\n        ',
			}


			@require_torch
			def    UpperCamelCase						(			self				)     ->  Optional[int]:
							'''simple docstring'''






							import torch

							A__						=	JukeboxTokenizer.from_pretrained("openai/jukebox-1b-lyrics"				)
							A__						=	tokenizer(**self.metas				)["input_ids"]
							# fmt: off
							A__						=	[
							    torch.tensor([[
							        0, 0, 0, 7169, 507, 9, 76, 39, 31, 46, 76, 27,
							        76, 46, 44, 27, 48, 31, 38, 38, 31, 44, 76, 32,
							        44, 41, 39, 76, 27, 40, 76, 27, 40, 46, 35, 43,
							        47, 31, 76, 38, 27, 40, 30, 64, 78, 76, 76, 76,
							        76, 76, 76, 76, 76, 23, 34, 41, 76, 45, 27, 35,
							        30, 76, 71, 20, 49, 41, 76, 48, 27, 45, 46, 76,
							        27, 40, 30, 76, 46, 44, 47, 40, 37, 38, 31, 45,
							        45, 76, 38, 31, 33, 45, 76, 41, 32, 76, 45, 46,
							        41, 40, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
							        19, 46, 27, 40, 30, 76, 35, 40, 76, 46, 34, 31,
							        76, 30, 31, 45, 31, 44, 46, 63, 76, 63, 76, 63,
							        76, 63, 76, 14, 31, 27, 44, 76, 46, 34, 31, 39,
							        64, 76, 41, 40, 76, 46, 34, 31, 76, 45, 27, 40,
							        30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76, 8,
							        27, 38, 32, 76, 45, 47, 40, 37, 76, 27, 76, 45,
							        34, 27, 46, 46, 31, 44, 31, 30, 76, 48, 35, 45,
							        27, 33, 31, 76, 38, 35, 31, 45, 64, 76, 49, 34,
							        41, 45, 31, 76, 32, 44, 41, 49, 40, 64, 78, 76,
							        76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76, 49,
							        44, 35, 40, 37, 38, 31, 30, 76, 38, 35, 42, 64,
							        76, 27, 40, 30, 76, 45, 40, 31, 31, 44, 76, 41,
							        32, 76, 29, 41, 38, 30, 76, 29, 41, 39, 39, 27,
							        40, 30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76,
							        20, 31, 38, 38, 76, 46, 34, 27, 46, 76, 35, 46,
							        45, 76, 45, 29, 47, 38, 42, 46, 41, 44, 76, 49,
							        31, 38, 38, 76, 46, 34, 41, 45, 31, 76, 42, 27,
							        45, 45, 35, 41, 40, 45, 76, 44, 31, 27, 30, 78,
							        76, 76, 76, 76, 76, 76, 76, 76, 23, 34, 35, 29,
							        34, 76, 51, 31, 46, 76, 45, 47, 44, 48, 35, 48,
							        31, 64, 76, 45, 46, 27, 39, 42, 31, 30, 76, 41,
							        40, 76, 46, 34, 31, 45, 31, 76, 38, 35, 32, 31,
							        38, 31, 45, 45, 76, 46, 34, 35, 40, 33, 45, 64,
							        78, 76, 76, 76, 76, 76, 76, 76, 76, 20, 34, 31,
							        76, 34, 27, 40, 30, 76, 46, 34, 27, 46, 76, 39,
							        41, 29, 37, 31, 30, 76, 46, 34, 31, 39, 64, 76,
							        27, 40, 30, 76, 46, 34, 31, 76, 34, 31, 27, 44,
							        46, 76, 46, 34, 27, 46, 76, 32, 31, 30, 66, 78,
							        76, 76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76,
							        41, 40, 76, 46, 34, 31, 76, 42, 31, 30, 31, 45,
							        46, 27, 38, 64, 76, 46, 34, 31, 45, 31, 76, 49,
							        41, 44, 30, 45, 76, 27, 42, 42, 31, 27, 44, 65,
							        78, 76, 76, 76, 76, 76, 76, 76, 76, 13, 51, 76,
							        40, 27, 39, 31, 76, 35, 45, 76, 15, 52, 51, 39,
							        27, 40, 30, 35, 27, 45, 64, 76, 11, 35, 40, 33,
							        76, 41, 32, 76, 11, 35, 40, 33, 45, 66, 78, 76,
							        76, 76, 76, 76, 76, 76, 76, 12, 41, 41, 37, 76,
							        41, 40, 76, 39, 51, 76, 23, 41, 44, 37, 45, 64,
							        76, 51, 31, 76, 13, 35, 33, 34, 46, 51, 64, 76,
							        27, 40, 30, 76, 30, 31, 45, 42, 27, 35, 44, 67,
							        78, 76, 76, 76, 76, 76, 76, 76, 76, 14, 41, 46,
							        34, 35, 40, 33, 76, 28, 31, 45, 35, 30, 31, 76,
							        44, 31, 39, 27, 35, 40, 45, 63, 76, 18, 41, 47,
							        40, 30, 76, 46, 34, 31, 76, 30, 31, 29, 27, 51,
							        78, 76, 76, 76, 76, 76, 76, 76, 76, 15, 32, 76,
							        46, 34, 27, 46, 76, 29, 41, 38, 41, 45, 45, 27,
							        38, 76, 23, 44, 31, 29, 37, 64, 76, 28, 41, 47,
							        40, 30, 38, 31, 45, 45, 76, 27, 40, 30, 76, 28,
							        27, 44, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
							        20, 34, 31, 76, 38, 41, 40, 31, 76, 27, 40, 30,
							        76, 38, 31, 48, 31, 38, 76, 45, 27, 40, 30, 45,
							        76, 45, 46, 44, 31, 46, 29, 34, 76, 32, 27, 44,
							        76, 27, 49, 27, 51, 78, 76, 76, 76, 76, 76, 76,
							        76, 76]]				),
							    torch.tensor([[0, 0, 0, 1069, 11]]				),
							    torch.tensor([[0, 0, 0, 1069, 11]]				),
							]
							# fmt: on
							self.assertTrue(torch.allclose(tokens[0]					,					EXPECTED_OUTPUT[0]				)				)
							self.assertTrue(torch.allclose(tokens[1]					,					EXPECTED_OUTPUT[1]				)				)
							self.assertTrue(torch.allclose(tokens[2]					,					EXPECTED_OUTPUT[2]				)				)


			@require_torch
			def    UpperCamelCase						(			self				)     ->  Union[str, Any]:
							'''simple docstring'''






							import torch

							A__						=	JukeboxTokenizer.from_pretrained("openai/jukebox-5b-lyrics"				)
							A__						=	tokenizer(**self.metas				)["input_ids"]
							# fmt: off
							A__						=	[
							    torch.tensor([[
							        0, 0, 0, 1069, 11, -1, -1, -1, -1, 9, 77, 39,
							        31, 46, 77, 27, 77, 46, 44, 27, 48, 31, 38, 38,
							        31, 44, 77, 32, 44, 41, 39, 77, 27, 40, 77, 27,
							        40, 46, 35, 43, 47, 31, 77, 38, 27, 40, 30, 64,
							        79, 77, 77, 77, 77, 77, 77, 77, 77, 23, 34, 41,
							        77, 45, 27, 35, 30, 77, 72, 20, 49, 41, 77, 48,
							        27, 45, 46, 77, 27, 40, 30, 77, 46, 44, 47, 40,
							        37, 38, 31, 45, 45, 77, 38, 31, 33, 45, 77, 41,
							        32, 77, 45, 46, 41, 40, 31, 79, 77, 77, 77, 77,
							        77, 77, 77, 77, 19, 46, 27, 40, 30, 77, 35, 40,
							        77, 46, 34, 31, 77, 30, 31, 45, 31, 44, 46, 63,
							        77, 63, 77, 63, 77, 63, 77, 14, 31, 27, 44, 77,
							        46, 34, 31, 39, 64, 77, 41, 40, 77, 46, 34, 31,
							        77, 45, 27, 40, 30, 64, 79, 77, 77, 77, 77, 77,
							        77, 77, 77, 8, 27, 38, 32, 77, 45, 47, 40, 37,
							        77, 27, 77, 45, 34, 27, 46, 46, 31, 44, 31, 30,
							        77, 48, 35, 45, 27, 33, 31, 77, 38, 35, 31, 45,
							        64, 77, 49, 34, 41, 45, 31, 77, 32, 44, 41, 49,
							        40, 64, 79, 77, 77, 77, 77, 77, 77, 77, 77, 1,
							        40, 30, 77, 49, 44, 35, 40, 37, 38, 31, 30, 77,
							        38, 35, 42, 64, 77, 27, 40, 30, 77, 45, 40, 31,
							        31, 44, 77, 41, 32, 77, 29, 41, 38, 30, 77, 29,
							        41, 39, 39, 27, 40, 30, 64, 79, 77, 77, 77, 77,
							        77, 77, 77, 77, 20, 31, 38, 38, 77, 46, 34, 27,
							        46, 77, 35, 46, 45, 77, 45, 29, 47, 38, 42, 46,
							        41, 44, 77, 49, 31, 38, 38, 77, 46, 34, 41, 45,
							        31, 77, 42, 27, 45, 45, 35, 41, 40, 45, 77, 44,
							        31, 27, 30, 79, 77, 77, 77, 77, 77, 77, 77, 77,
							        23, 34, 35, 29, 34, 77, 51, 31, 46, 77, 45, 47,
							        44, 48, 35, 48, 31, 64, 77, 45, 46, 27, 39, 42,
							        31, 30, 77, 41, 40, 77, 46, 34, 31, 45, 31, 77,
							        38, 35, 32, 31, 38, 31, 45, 45, 77, 46, 34, 35,
							        40, 33, 45, 64, 79, 77, 77, 77, 77, 77, 77, 77,
							        77, 20, 34, 31, 77, 34, 27, 40, 30, 77, 46, 34,
							        27, 46, 77, 39, 41, 29, 37, 31, 30, 77, 46, 34,
							        31, 39, 64, 77, 27, 40, 30, 77, 46, 34, 31, 77,
							        34, 31, 27, 44, 46, 77, 46, 34, 27, 46, 77, 32,
							        31, 30, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77,
							        1, 40, 30, 77, 41, 40, 77, 46, 34, 31, 77, 42,
							        31, 30, 31, 45, 46, 27, 38, 64, 77, 46, 34, 31,
							        45, 31, 77, 49, 41, 44, 30, 45, 77, 27, 42, 42,
							        31, 27, 44, 65, 79, 77, 77, 77, 77, 77, 77, 77,
							        77, 13, 51, 77, 40, 27, 39, 31, 77, 35, 45, 77,
							        15, 52, 51, 39, 27, 40, 30, 35, 27, 45, 64, 77,
							        11, 35, 40, 33, 77, 41, 32, 77, 11, 35, 40, 33,
							        45, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77, 12,
							        41, 41, 37, 77, 41, 40, 77, 39, 51, 77, 23, 41,
							        44, 37, 45, 64, 77, 51, 31, 77, 13, 35, 33, 34,
							        46, 51, 64, 77, 27, 40, 30, 77, 30, 31, 45, 42,
							        27, 35, 44, 67, 79, 77, 77, 77, 77, 77, 77, 77,
							        77, 14, 41, 46, 34, 35, 40, 33, 77, 28, 31, 45,
							        35, 30, 31, 77, 44, 31, 39, 27, 35, 40, 45, 63,
							        77, 18, 41, 47, 40, 30, 77, 46, 34, 31, 77, 30,
							        31, 29, 27, 51, 79, 77, 77, 77, 77, 77, 77, 77,
							        77, 15, 32, 77, 46, 34, 27, 46, 77, 29, 41, 38,
							        41, 45, 45, 27, 38, 77, 23, 44, 31, 29, 37, 64,
							        77, 28, 41, 47, 40, 30, 38, 31, 45, 45, 77, 27,
							        40, 30, 77, 28, 27, 44, 31, 79, 77, 77, 77, 77,
							        77, 77, 77, 77, 20, 34, 31, 77, 38, 41, 40, 31,
							        77, 27, 40, 30, 77, 38, 31, 48, 31, 38, 77, 45,
							        27, 40, 30, 45, 77, 45, 46, 44, 31, 46, 29, 34,
							        77, 32, 27, 44, 77, 27, 49, 27, 51, 79, 77, 77,
							        77, 77, 77, 77, 77, 77]]				),
							    torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]				),
							    torch.tensor([[0, 0, 0, 1069, 11, -1, -1, -1, -1]]				),
							]
							# fmt: on
							self.assertTrue(torch.allclose(tokens[0]					,					EXPECTED_OUTPUT[0]				)				)
							self.assertTrue(torch.allclose(tokens[1]					,					EXPECTED_OUTPUT[1]				)				)
							self.assertTrue(torch.allclose(tokens[2]					,					EXPECTED_OUTPUT[2]				)				)





"""simple docstring"""





import mpmath  # for roots of unity
import numpy as np



class 						snake_case_:






     def __init__(		self     :    str    , UpperCamelCase_     :    int=None    , UpperCamelCase_     :    List[str]=None ):
           # Input as list
           lowerCAmelCase    :		str				=      list(poly_a or [0] )[:]
           lowerCAmelCase    :		Any				=      list(poly_b or [0] )[:]

           # Remove leading zero coefficients
           while self.polyA[-1] == 0:
                 self.polyA.pop()
           lowerCAmelCase    :		Optional[int]				=      len(self.polyA )

           while self.polyB[-1] == 0:
                 self.polyB.pop()
           lowerCAmelCase    :		Union[str, Any]				=      len(self.polyB )

           # Add 0 to make lengths equal a power of 2
           lowerCAmelCase    :		str				=      int(
               2 ** np.ceil(np.loga(len(self.polyA ) + len(self.polyB ) - 1 ) ) )

           while len(self.polyA ) < self.c_max_length:
                 self.polyA.append(0 )
           while len(self.polyB ) < self.c_max_length:
                 self.polyB.append(0 )
           # A complex root used for the fourier transform
           lowerCAmelCase    :		int				=      complex(mpmath.root(x=1    , n=self.c_max_length    , k=1 ) )

           # The product
           lowerCAmelCase    :		int				=      self.__multiply()






     def    lowerCamelCase__   (		self     :    List[str]    , UpperCamelCase_     :    str ):
           lowerCAmelCase    :		Optional[Any]				=      [[x] for x in self.polyA] if which == '''A''' else [[x] for x in self.polyB]
           # Corner case
           if len(UpperCamelCase_ ) <= 1:
                 return dft[0]
           #
           lowerCAmelCase    :		Tuple				=      self.c_max_length // 2
           while next_ncol > 0:
                 lowerCAmelCase    :		Dict				=      [[] for i in range(UpperCamelCase_ )]
                 lowerCAmelCase    :		List[Any]				=      self.root**next_ncol

                 # First half of next step
                 lowerCAmelCase    :		Dict				=      1
                 for j in range(self.c_max_length // (next_ncol * 2) ):
                       for i in range(UpperCamelCase_ ):
                             new_dft[i].append(dft[i][j] + current_root * dft[i + next_ncol][j] )
                       current_root *= root
                 # Second half of next step
                 lowerCAmelCase    :		int				=      1
                 for j in range(self.c_max_length // (next_ncol * 2) ):
                       for i in range(UpperCamelCase_ ):
                             new_dft[i].append(dft[i][j] - current_root * dft[i + next_ncol][j] )
                       current_root *= root
                 # Update
                 lowerCAmelCase    :		Optional[Any]				=      new_dft
                 lowerCAmelCase    :		Union[str, Any]				=      next_ncol // 2
           return dft[0]






     def    lowerCamelCase__   (		self     :    List[Any] ):
           lowerCAmelCase    :		Optional[Any]				=      self.__dft('''A''' )
           lowerCAmelCase    :		Optional[int]				=      self.__dft('''B''' )
           lowerCAmelCase    :		Any				=      [[dft_a[i] * dft_b[i] for i in range(self.c_max_length )]]
           del dft_a
           del dft_b

           # Corner Case
           if len(inverce_c[0] ) <= 1:
                 return inverce_c[0]
           # Inverse DFT
           lowerCAmelCase    :		str				=      2
           while next_ncol <= self.c_max_length:
                 lowerCAmelCase    :		Union[str, Any]				=      [[] for i in range(UpperCamelCase_ )]
                 lowerCAmelCase    :		Optional[Any]				=      self.root ** (next_ncol // 2)
                 lowerCAmelCase    :		Tuple				=      1
                 # First half of next step
                 for j in range(self.c_max_length // next_ncol ):
                       for i in range(next_ncol // 2 ):
                             # Even positions
                             new_inverse_c[i].append(
                                 (
                                     inverce_c[i][j]
                                     + inverce_c[i][j + self.c_max_length // next_ncol]
                                 )
                                 / 2 )
                             # Odd positions
                             new_inverse_c[i + next_ncol // 2].append(
                                 (
                                     inverce_c[i][j]
                                     - inverce_c[i][j + self.c_max_length // next_ncol]
                                 )
                                 / (2 * current_root) )
                       current_root *= root
                 # Update
                 lowerCAmelCase    :		Any				=      new_inverse_c
                 next_ncol *= 2
           # Unpack
           lowerCAmelCase    :		Optional[int]				=      [round(x[0].real    , 8 ) + round(x[0].imag    , 8 ) * 1j for x in inverce_c]

           # Remove leading 0's
           while inverce_c[-1] == 0:
                 inverce_c.pop()
           return inverce_c






     def __str__(		self     :    int ):
           lowerCAmelCase    :		int				=      '''A = ''' + ''' + '''.join(
               F'''{coef}*x^{i}''' for coef, i in enumerate(self.polyA[: self.len_A] ) )
           lowerCAmelCase    :		str				=      '''B = ''' + ''' + '''.join(
               F'''{coef}*x^{i}''' for coef, i in enumerate(self.polyB[: self.len_B] ) )
           lowerCAmelCase    :		int				=      '''A*B = ''' + ''' + '''.join(
               F'''{coef}*x^{i}''' for coef, i in enumerate(self.product ) )

           return F'''{a}\n{b}\n{c}'''


# Unit tests
if __name__ == "__main__":
 import doctest

 doctest.testmod()


