





import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union

import numpy as np
import regex

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_flax_available, is_tf_available, is_torch_available, logging
from ...utils.generic import _is_jax, _is_numpy


_SCREAMING_SNAKE_CASE      	=		logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE      	=		{
    """artists_file""": """artists.json""",
    """lyrics_file""": """lyrics.json""",
    """genres_file""": """genres.json""",
}

_SCREAMING_SNAKE_CASE      	=		{
    """artists_file""": {
        """jukebox""": """https://huggingface.co/ArthurZ/jukebox/blob/main/artists.json""",
    },
    """genres_file""": {
        """jukebox""": """https://huggingface.co/ArthurZ/jukebox/blob/main/genres.json""",
    },
    """lyrics_file""": {
        """jukebox""": """https://huggingface.co/ArthurZ/jukebox/blob/main/lyrics.json""",
    },
}

_SCREAMING_SNAKE_CASE      	=		{
    """jukebox""": 5_12,
}
class SCREAMING_SNAKE_CASE_						(					snake_case_					):
						__magic_name__:			Dict       =       VOCAB_FILES_NAMES
						__magic_name__:			Optional[Any]       =       PRETRAINED_VOCAB_FILES_MAP
						__magic_name__:			Any       =       PRETRAINED_LYRIC_TOKENS_SIZES
						__magic_name__:			List[str]       =       ["input_ids", "attention_mask"]






						def __init__(      self      :      Tuple		,   _A      :      List[str]		,   _A      :      int		,   _A      :      Dict		,   _A      :      Dict=["v3", "v2", "v2"]		,   _A      :      Tuple=512		,   _A      :      Any=5		,   _A      :      int="<|endoftext|>"		,   **_A      :      Union[str, Any]		,   )							->    Optional[Any]:







							"""simple docstring"""


							snake_case_		:			int											=	AddedToken(_A		,   lstrip=_A		,   rstrip=_A	) if isinstance(_A		,   _A	) else unk_token
							super().__init__(
							    unk_token=_A		,   n_genres=_A		,   version=_A		,   max_n_lyric_tokens=_A		,   **_A		,   )
							snake_case_		:			int											=	version
							snake_case_		:			Union[str, Any]											=	max_n_lyric_tokens
							snake_case_		:			List[Any]											=	n_genres

							with open(_A		,   encoding='utf-8'	) as vocab_handle:
								snake_case_		:			List[Any]											=	json.load(_A	)

							with open(_A		,   encoding='utf-8'	) as vocab_handle:
								snake_case_		:			Any											=	json.load(_A	)

							with open(_A		,   encoding='utf-8'	) as vocab_handle:
								snake_case_		:			List[str]											=	json.load(_A	)

							snake_case_		:			int											=	R'[^A-Za-z0-9.,:;!?\-\'\"()\[\] \t\n]+'
							# In v2, we had a n_vocab=80 and in v3 we missed + and so n_vocab=79 of characters.
							if len(self.lyrics_encoder	) == 79:
								snake_case_		:			List[Any]											=	oov.replace(R'\-\''		,   R'\-+\''	)

							snake_case_		:			List[Any]											=	regex.compile(_A	)
							snake_case_		:			Any											=	{v: k for k, v in self.artists_encoder.items()}
							snake_case_		:			Union[str, Any]											=	{v: k for k, v in self.genres_encoder.items()}
							snake_case_		:			str											=	{v: k for k, v in self.lyrics_encoder.items()}






						@property
						def UpperCAmelCase_				(      self      :      Optional[int]	)							->    List[Any]:







							"""simple docstring"""


							return len(self.artists_encoder	) + len(self.genres_encoder	) + len(self.lyrics_encoder	)






						def UpperCAmelCase_				(      self      :      List[str]	)							->    List[Any]:







							"""simple docstring"""


							return dict(self.artists_encoder		,   self.genres_encoder		,   self.lyrics_encoder	)






						def UpperCAmelCase_				(      self      :      Optional[int]		,   _A      :      str		,   _A      :      Union[str, Any]		,   _A      :      Optional[int]	)							->    Tuple:







							"""simple docstring"""


							snake_case_		:			str											=	[self.artists_encoder.get(_A		,   0	) for artist in list_artists]
							for genres in range(len(_A	)	):
								snake_case_		:			Optional[int]											=	[self.genres_encoder.get(_A		,   0	) for genre in list_genres[genres]]
								snake_case_		:			List[Any]											=	list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]	))

							snake_case_		:			Union[str, Any]											=	[[self.lyrics_encoder.get(_A		,   0	) for character in list_lyrics[0]], [], []]
							return artists_id, list_genres, lyric_ids






						def UpperCAmelCase_				(      self      :      List[Any]		,   _A      :      Tuple	)							->    int:







							"""simple docstring"""


							return list(_A	)






						def UpperCAmelCase_				(      self      :      Dict		,   _A      :      List[str]		,   _A      :      List[str]		,   _A      :      Any		,   **_A      :      Tuple	)							->    str:







							"""simple docstring"""


							snake_case_						,snake_case_						,snake_case_		:			Tuple											=	self.prepare_for_tokenization(_A		,   _A		,   _A	)
							snake_case_		:			List[Any]											=	self._tokenize(_A	)
							return artist, genre, lyrics






						def UpperCAmelCase_				(      self      :      int		,   _A      :      str		,   _A      :      str		,   _A      :      str		,   _A      :      bool = False	)							->    Tuple[str, str, str, Dict[str, Any]]:







							"""simple docstring"""


							for idx in range(len(self.version	)	):
								if self.version[idx] == "v3":
									snake_case_		:			List[str]											=	artists[idx].lower()
									snake_case_		:			Optional[int]											=	[genres[idx].lower()]
								else:
									snake_case_		:			Optional[Any]											=	self._normalize(artists[idx]	) + '.v2'
									snake_case_		:			str											=	[
									    self._normalize(_A	) + '.v2' for genre in genres[idx].split('_'	)
									]  # split is for the full dictionary with combined genres

							if self.version[0] == "v2":
								snake_case_		:			Optional[int]											=	regex.compile(R'[^A-Za-z0-9.,:;!?\-\'\"()\[\] \t\n]+'	)
								snake_case_		:			List[str]											=	'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789.,:;!?-+\'\"()[] \t\n'
								snake_case_		:			str											=	{vocab[index]: index + 1 for index in range(len(_A	)	)}
								snake_case_		:			Optional[int]											=	0
								snake_case_		:			Optional[Any]											=	len(_A	) + 1
								snake_case_		:			Dict											=	self.vocab
								snake_case_		:			int											=	{v: k for k, v in self.vocab.items()}
								snake_case_		:			Tuple											=	''
							else:
								snake_case_		:			Any											=	regex.compile(R'[^A-Za-z0-9.,:;!?\-+\'\"()\[\] \t\n]+'	)

							snake_case_		:			Optional[Any]											=	self._run_strip_accents(_A	)
							snake_case_		:			List[Any]											=	lyrics.replace('\\'		,   '\n'	)
							snake_case_		:			Any											=	self.out_of_vocab.sub(''		,   _A	), [], []
							return artists, genres, lyrics






						def UpperCAmelCase_				(      self      :      Any		,   _A      :      List[str]	)							->    Optional[Any]:







							"""simple docstring"""


							snake_case_		:			Dict											=	unicodedata.normalize('NFD'		,   _A	)
							snake_case_		:			List[str]											=	[]
							for char in text:
								snake_case_		:			Union[str, Any]											=	unicodedata.category(_A	)
								if cat == "Mn":
									continue
								output.append(_A	)
							return "".join(_A	)






						def UpperCAmelCase_				(      self      :      int		,   _A      :      str	)							->    str:







							"""simple docstring"""


							snake_case_		:			Any											=	(
							    [chr(_A	) for i in range(ord('a'	)		,   ord('z'	) + 1	)]
							    + [chr(_A	) for i in range(ord('A'	)		,   ord('Z'	) + 1	)]
							    + [chr(_A	) for i in range(ord('0'	)		,   ord('9'	) + 1	)]
							    + ['.']
							)
							snake_case_		:			Any											=	frozenset(_A	)
							snake_case_		:			List[str]											=	re.compile(R'_+'	)
							snake_case_		:			Optional[Any]											=	''.join([c if c in accepted else '_' for c in text.lower()]	)
							snake_case_		:			List[str]											=	pattern.sub('_'		,   _A	).strip('_'	)
							return text






						def UpperCAmelCase_				(      self      :      List[Any]		,   _A      :      List[str]	)							->    str:







							"""simple docstring"""


							return " ".join(_A	)






						def UpperCAmelCase_				(      self      :      Union[str, Any]		,   _A      :      int		,   _A      :      Optional[Union[str, TensorType]] = None		,   _A      :      bool = False	)							->    List[str]:







							"""simple docstring"""


							if not isinstance(_A		,   _A	):
								snake_case_		:			Tuple											=	TensorType(_A	)

							# Get a function reference for the correct framework
							if tensor_type == TensorType.TENSORFLOW:
								if not is_tf_available():
									raise ImportError(
									    'Unable to convert output to TensorFlow tensors format, TensorFlow is not installed.'	)
								import tensorflow as tf

								snake_case_		:			List[Any]											=	tf.constant
								snake_case_		:			Optional[Any]											=	tf.is_tensor
							elif tensor_type == TensorType.PYTORCH:
								if not is_torch_available():
									raise ImportError('Unable to convert output to PyTorch tensors format, PyTorch is not installed.'	)
								import torch

								snake_case_		:			Dict											=	torch.tensor
								snake_case_		:			str											=	torch.is_tensor
							elif tensor_type == TensorType.JAX:
								if not is_flax_available():
									raise ImportError('Unable to convert output to JAX tensors format, JAX is not installed.'	)
								import jax.numpy as jnp  # noqa: F811

								snake_case_		:			Any											=	jnp.array
								snake_case_		:			str											=	_is_jax
							else:
								snake_case_		:			Union[str, Any]											=	np.asarray
								snake_case_		:			str											=	_is_numpy

							# Do the tensor conversion in batch

							try:
								if prepend_batch_axis:
									snake_case_		:			Union[str, Any]											=	[inputs]

								if not is_tensor(_A	):
									snake_case_		:			str											=	as_tensor(_A	)
							except:  # noqa E722
								raise ValueError(
								    'Unable to create tensor, you should probably activate truncation and/or padding '
								    'with \'padding=True\' \'truncation=True\' to have batched tensors with the same length.'	)

							return inputs






						def __call__(      self      :      Tuple		,   _A      :      Any		,   _A      :      Union[str, Any]		,   _A      :      Any=""		,   _A      :      Any="pt"	)							->    BatchEncoding:







							"""simple docstring"""


							snake_case_		:			Tuple											=	[0, 0, 0]
							snake_case_		:			Any											=	[artist] * len(self.version	)
							snake_case_		:			List[Any]											=	[genres] * len(self.version	)

							snake_case_						,snake_case_						,snake_case_		:			List[str]											=	self.tokenize(_A		,   _A		,   _A	)
							snake_case_						,snake_case_						,snake_case_		:			int											=	self._convert_token_to_id(_A		,   _A		,   _A	)

							snake_case_		:			Optional[int]											=	[-INFINITY] * len(full_tokens[-1]	)
							snake_case_		:			Dict											=	[
							    self.convert_to_tensors(
							        [input_ids + [artists_id[i]] + genres_ids[i] + full_tokens[i]]		,   tensor_type=_A	)
							    for i in range(len(self.version	)	)
							]
							return BatchEncoding({'input_ids': input_ids, 'attention_masks': attention_masks}	)






						def UpperCAmelCase_				(      self      :      List[str]		,   _A      :      str		,   _A      :      Optional[str] = None	)							->    Tuple[str]:







							"""simple docstring"""


							if not os.path.isdir(_A	):
								logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""	)
								return

							snake_case_		:			Tuple											=	os.path.join(
							    _A		,   (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['artists_file']	)
							with open(_A		,   'w'		,   encoding='utf-8'	) as f:
								f.write(json.dumps(self.artists_encoder		,   ensure_ascii=_A	)	)

							snake_case_		:			Dict											=	os.path.join(
							    _A		,   (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['genres_file']	)
							with open(_A		,   'w'		,   encoding='utf-8'	) as f:
								f.write(json.dumps(self.genres_encoder		,   ensure_ascii=_A	)	)

							snake_case_		:			Any											=	os.path.join(
							    _A		,   (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['lyrics_file']	)
							with open(_A		,   'w'		,   encoding='utf-8'	) as f:
								f.write(json.dumps(self.lyrics_encoder		,   ensure_ascii=_A	)	)

							return (artists_file, genres_file, lyrics_file)






						def UpperCAmelCase_				(      self      :      Any		,   _A      :      str		,   _A      :      List[str]		,   _A      :      Optional[Any]	)							->    Optional[int]:







							"""simple docstring"""


							snake_case_		:			int											=	self.artists_decoder.get(_A	)
							snake_case_		:			Any											=	[self.genres_decoder.get(_A	) for genre in genres_index]
							snake_case_		:			Union[str, Any]											=	[self.lyrics_decoder.get(_A	) for character in lyric_index]
							return artist, genres, lyrics








from __future__ import annotations


def 							SCREAMING_SNAKE_CASE__						(    __a   , __a = None   , __a = None   , __a = False   , ):
	snake_case_		:			int											=	cipher_alphabet or [chr(__a   ) for i in range(97   , 1_23   )]

	# If the argument is None or the user provided an empty dictionary
	if not frequencies_dict:
		# Frequencies of letters in the english language (how much they show up)
		snake_case_		:			Dict											=	{
		    'a': 0.08497,
		    'b': 0.01492,
		    'c': 0.02202,
		    'd': 0.04253,
		    'e': 0.11162,
		    'f': 0.02228,
		    'g': 0.02015,
		    'h': 0.06094,
		    'i': 0.07546,
		    'j': 0.00153,
		    'k': 0.01292,
		    'l': 0.04025,
		    'm': 0.02406,
		    'n': 0.06749,
		    'o': 0.07507,
		    'p': 0.01929,
		    'q': 0.00095,
		    'r': 0.07587,
		    's': 0.06327,
		    't': 0.09356,
		    'u': 0.02758,
		    'v': 0.00978,
		    'w': 0.02560,
		    'x': 0.00150,
		    'y': 0.01994,
		    'z': 0.00077,
		}
	else:
		# Custom frequencies dictionary
		snake_case_		:			int											=	frequencies_dict

	if not case_sensitive:
		snake_case_		:			Optional[Any]											=	ciphertext.lower()

	# Chi squared statistic values
	snake_case_		:			dict[int, tuple[float, str]]											=	{}

	# cycle through all of the shifts
	for shift in range(len(__a   )   ):
		snake_case_		:			int											=	''

		# decrypt the message with the shift
		for letter in ciphertext:
			try:
				# Try to index the letter in the alphabet
				snake_case_		:			List[Any]											=	(alphabet_letters.index(letter.lower()   ) - shift) % len(
				    __a   )
				decrypted_with_shift += (
				    alphabet_letters[new_key].upper()
				    if case_sensitive and letter.isupper()
				    else alphabet_letters[new_key]
				)
			except ValueError:
				# Append the character if it isn't in the alphabet
				decrypted_with_shift += letter

		snake_case_		:			Union[str, Any]											=	0.0

		# Loop through each letter in the decoded message with the shift
		for letter in decrypted_with_shift:
			if case_sensitive:
				snake_case_		:			List[Any]											=	letter.lower()
				if letter in frequencies:
					# Get the amount of times the letter occurs in the message
					snake_case_		:			Optional[Any]											=	decrypted_with_shift.lower().count(__a   )

					# Get the excepcted amount of times the letter should appear based
					# on letter frequencies
					snake_case_		:			Tuple											=	frequencies[letter] * occurrences

					# Complete the chi squared statistic formula
					snake_case_		:			Optional[int]											=	((occurrences - expected) ** 2) / expected

					# Add the margin of error to the total chi squared statistic
					chi_squared_statistic += chi_letter_value
			else:
				if letter.lower() in frequencies:
					# Get the amount of times the letter occurs in the message
					snake_case_		:			Any											=	decrypted_with_shift.count(__a   )

					# Get the excepcted amount of times the letter should appear based
					# on letter frequencies
					snake_case_		:			List[str]											=	frequencies[letter] * occurrences

					# Complete the chi squared statistic formula
					snake_case_		:			Optional[Any]											=	((occurrences - expected) ** 2) / expected

					# Add the margin of error to the total chi squared statistic
					chi_squared_statistic += chi_letter_value

        # Add the data to the chi_squared_statistic_values dictionary
		snake_case_		:			Any											=	(
		    chi_squared_statistic,
		    decrypted_with_shift,
		)

	# Get the most likely cipher by finding the cipher with the smallest chi squared
	# statistic
	def chi_squared_statistic_values_sorting_key(__a   ) -> tuple[float, str]:
		return chi_squared_statistic_values[key]

	snake_case_		:			int											=	min(
	    __a   , key=__a   , )

	# Get all the data from the most likely cipher (key, decoded message)
	(
	    (
	    snake_case_
	)						,(
	    snake_case_
	)						,
	)		:			str											=	chi_squared_statistic_values[most_likely_cipher]

	# Return the data on the most likely shift
	return (
	    most_likely_cipher,
	    most_likely_cipher_chi_squared_value,
	    decoded_most_likely_cipher,
	)

