



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


UpperCAmelCase_		 =					logging.get_logger(__name__)

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

UpperCAmelCase_		 =					{
    """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""",
    },
}

UpperCAmelCase_		 =					{
    """jukebox""": 5_1_2,
}


class 	lowerCamelCase__	(       _A):



 """simple docstring"""

 a__					: Any =  VOCAB_FILES_NAMES
 a__					: str =  PRETRAINED_VOCAB_FILES_MAP
 a__					: Any =  PRETRAINED_LYRIC_TOKENS_SIZES
 a__					: str =  ["input_ids", "attention_mask"]

 def __init__(    self					:					int			,						__lowerCAmelCase					:					Optional[Any]			,						__lowerCAmelCase					:					Any			,						__lowerCAmelCase					:					Tuple			,						__lowerCAmelCase					:					int=["v3", "v2", "v2"]			,						__lowerCAmelCase					:					str=5_12			,						__lowerCAmelCase					:					Tuple=5			,						__lowerCAmelCase					:					str="<|endoftext|>"			,						**__lowerCAmelCase					:					Tuple			,						)   ->	Union[str, Any]:
    _A      =       AddedToken(__lowerCAmelCase			,						lstrip=__lowerCAmelCase			,						rstrip=__lowerCAmelCase      ) if isinstance(__lowerCAmelCase			,						__lowerCAmelCase      ) else unk_token
    super().__init__(
        unk_token=__lowerCAmelCase			,						n_genres=__lowerCAmelCase			,						version=__lowerCAmelCase			,						max_n_lyric_tokens=__lowerCAmelCase			,						**__lowerCAmelCase			,						)
    _A      =       version
    _A      =       max_n_lyric_tokens
    _A      =       n_genres

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

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

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

    _A      =       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:
       _A      =       oov.replace(R'''\-\''''			,						R'''\-+\''''      )

    _A      =       regex.compile(__lowerCAmelCase      )
    _A      =       {v: k for k, v in self.artists_encoder.items()}
    _A      =       {v: k for k, v in self.genres_encoder.items()}
    _A      =       {v: k for k, v in self.lyrics_encoder.items()}

 @property
 def     snake_case_      (    self					:					str      )   ->	Tuple:
    return len(self.artists_encoder      ) + len(self.genres_encoder      ) + len(self.lyrics_encoder      )

 def     snake_case_      (    self					:					Dict      )   ->	str:
    return dict(self.artists_encoder			,						self.genres_encoder			,						self.lyrics_encoder      )

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

    _A      =       [[self.lyrics_encoder.get(__lowerCAmelCase			,						0      ) for character in list_lyrics[0]], [], []]
    return artists_id, list_genres, lyric_ids

 def     snake_case_      (    self					:					int			,						__lowerCAmelCase					:					Tuple      )   ->	Optional[int]:
    return list(__lowerCAmelCase      )

 def     snake_case_      (    self					:					List[str]			,						__lowerCAmelCase					:					Optional[Any]			,						__lowerCAmelCase					:					Optional[Any]			,						__lowerCAmelCase					:					Tuple			,						**__lowerCAmelCase					:					int      )   ->	Union[str, Any]:
    _A  ,    _A  ,    _A      =       self.prepare_for_tokenization(__lowerCAmelCase			,						__lowerCAmelCase			,						__lowerCAmelCase      )
    _A      =       self._tokenize(__lowerCAmelCase      )
    return artist, genre, lyrics

 def     snake_case_      (    self					:					str			,						__lowerCAmelCase					:					str			,						__lowerCAmelCase					:					str			,						__lowerCAmelCase					:					str			,						__lowerCAmelCase					:					bool = False      )   ->	Tuple[str, str, str, Dict[str, Any]]:
    for idx in range(len(self.version      )      ):
       if self.version[idx] == "v3":
          _A      =       artists[idx].lower()
          _A      =       [genres[idx].lower()]
       else:
          _A      =       self._normalize(artists[idx]      ) + '''.v2'''
          _A      =       [
              self._normalize(__lowerCAmelCase      ) + '''.v2''' for genre in genres[idx].split('''_'''      )
          ]  # split is for the full dictionary with combined genres

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

    _A      =       self._run_strip_accents(__lowerCAmelCase      )
    _A      =       lyrics.replace('''\\'''			,						'''\n'''      )
    _A      =       self.out_of_vocab.sub(''''''			,						__lowerCAmelCase      ), [], []
    return artists, genres, lyrics

 def     snake_case_      (    self					:					str			,						__lowerCAmelCase					:					Tuple      )   ->	Union[str, Any]:
    _A      =       unicodedata.normalize('''NFD'''			,						__lowerCAmelCase      )
    _A      =       []
    for char in text:
       _A      =       unicodedata.category(__lowerCAmelCase      )
       if cat == "Mn":
          continue
       output.append(__lowerCAmelCase      )
    return "".join(__lowerCAmelCase      )

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

 def     snake_case_      (    self					:					Any			,						__lowerCAmelCase					:					List[str]      )   ->	str:
    return " ".join(__lowerCAmelCase      )

 def     snake_case_      (    self					:					List[Any]			,						__lowerCAmelCase					:					Any			,						__lowerCAmelCase					:					Optional[Union[str, TensorType]] = None			,						__lowerCAmelCase					:					bool = False      )   ->	Any:
    # Convert to TensorType
    if not isinstance(__lowerCAmelCase			,						__lowerCAmelCase      ):
       _A      =       TensorType(__lowerCAmelCase      )

    # 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

       _A      =       tf.constant
       _A      =       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

       _A      =       torch.tensor
       _A      =       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

       _A      =       jnp.array
       _A      =       _is_jax
    else:
       _A      =       np.asarray
       _A      =       _is_numpy

    # Do the tensor conversion in batch

    try:
       if prepend_batch_axis:
          _A      =       [inputs]

       if not is_tensor(__lowerCAmelCase      ):
          _A      =       as_tensor(__lowerCAmelCase      )
    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					:					Optional[Any]			,						__lowerCAmelCase					:					List[str]			,						__lowerCAmelCase					:					Dict			,						__lowerCAmelCase					:					List[str]=""			,						__lowerCAmelCase					:					Any="pt"      )   ->	BatchEncoding:
    _A      =       [0, 0, 0]
    _A      =       [artist] * len(self.version      )
    _A      =       [genres] * len(self.version      )

    _A  ,    _A  ,    _A      =       self.tokenize(__lowerCAmelCase			,						__lowerCAmelCase			,						__lowerCAmelCase      )
    _A  ,    _A  ,    _A      =       self._convert_token_to_id(__lowerCAmelCase			,						__lowerCAmelCase			,						__lowerCAmelCase      )

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

 def     snake_case_      (    self					:					Optional[int]			,						__lowerCAmelCase					:					str			,						__lowerCAmelCase					:					Optional[str] = None      )   ->	Tuple[str]:
    if not os.path.isdir(__lowerCAmelCase      ):
       logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''      )
       return

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

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

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

    return (artists_file, genres_file, lyrics_file)

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








"""simple docstring"""







import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a_							=    logging.get_logger(__name__)


a_							=    """▁"""

a_							=    {"""vocab_file""": """spiece.model"""}

a_							=    {
    """vocab_file""": {
        """google/reformer-crime-and-punishment""": (
            """https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"""
        )
    }
}

a_							=    {
    """google/reformer-crime-and-punishment""": 52_42_88,
}







class 					A_(SCREAMING_SNAKE_CASE_      ):







			"""simple docstring"""



			a_       :			Optional[int]												=			VOCAB_FILES_NAMES
			a_       :			int												=			PRETRAINED_VOCAB_FILES_MAP
			a_       :			str												=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			a_       :			Optional[Any]												=			["""input_ids""", """attention_mask"""]
			def __init__(	self				,   A				,   A="</s>"				,   A="<unk>"				,   A=[]				,   A = None				,   **A				,   ):
						_lowerCamelCase					:					Any	       =    {} if sp_model_kwargs is None else sp_model_kwargs

						super().__init__(
						    eos_token=A				,   unk_token=A				,   additional_special_tokens=A				,   sp_model_kwargs=self.sp_model_kwargs				,   **A				,   )

						_lowerCamelCase					:					Dict	       =    vocab_file
						_lowerCamelCase					:					List[Any]	       =    spm.SentencePieceProcessor(**self.sp_model_kwargs							)
						self.sp_model.Load(A							)
			@property
			def    _lowerCAmelCase		(	self							):
						return self.sp_model.get_piece_size()
			def    _lowerCAmelCase		(	self							):
						_lowerCamelCase					:					int	       =    {self.convert_ids_to_tokens(A							): i for i in range(self.vocab_size							)}
						vocab.update(self.added_tokens_encoder							)
						return vocab
			def __getstate__(	self							):
						_lowerCamelCase					:					Optional[int]	       =    self.__dict__.copy()
						_lowerCamelCase					:					Union[str, Any]	       =    None
						return state
			def __setstate__(	self				,   A							):
						_lowerCamelCase					:					int	       =    d

						# for backward compatibility
						if not hasattr(self				,   'sp_model_kwargs'							):
									_lowerCamelCase					:					Union[str, Any]	       =    {}

						_lowerCamelCase					:					Dict	       =    spm.SentencePieceProcessor(**self.sp_model_kwargs							)
						self.sp_model.Load(self.vocab_file							)
			def    _lowerCAmelCase		(	self				,   A							):
						return self.sp_model.encode(A				,   out_type=A							)
			def    _lowerCAmelCase		(	self				,   A							):
						return self.sp_model.piece_to_id(A							)
			def    _lowerCAmelCase		(	self				,   A							):
						if index < self.sp_model.get_piece_size():
									_lowerCamelCase					:					Dict	       =    self.sp_model.IdToPiece(A							)
						return token
			def    _lowerCAmelCase		(	self				,   A							):
						_lowerCamelCase					:					Tuple	       =    []
						_lowerCamelCase					:					Optional[int]	       =    ''
						for token in tokens:
									# make sure that special tokens are not decoded using sentencepiece model
									if token in self.all_special_tokens:
												out_string += self.sp_model.decode(A							) + token
												_lowerCamelCase					:					Dict	       =    []
									else:
												current_sub_tokens.append(A							)
						out_string += self.sp_model.decode(A							)
						return out_string.strip()

			def    _lowerCAmelCase		(	self				,   A				,   A = None							):
						if not os.path.isdir(A							):
									logger.error(F"Vocabulary path ({save_directory}) should be a directory"							)
									return
						_lowerCamelCase					:					Any	       =    os.path.join(
						    A				,   (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']							)

						if os.path.abspath(self.vocab_file							) != os.path.abspath(A							) and os.path.isfile(self.vocab_file							):
									copyfile(self.vocab_file				,   A							)
						elif not os.path.isfile(self.vocab_file							):
									with open(A				,   'wb'							) as fi:
												_lowerCamelCase					:					List[str]	       =    self.sp_model.serialized_model_proto()
												fi.write(A							)

						return (out_vocab_file,)





