

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


__A			:					List[Any]						=			logging.get_logger(__name__)

__A			:					int						=			{
    'artists_file': 'artists.json',
    'lyrics_file': 'lyrics.json',
    'genres_file': 'genres.json',
}

__A			:					List[str]						=			{
    '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',
    },
}

__A			:					Optional[Any]						=			{
    'jukebox': 5_1_2,
}





class 			_SCREAMING_SNAKE_CASE (   __snake_case		):







   '''simple docstring'''




   lowerCamelCase__				=      VOCAB_FILES_NAMES
   lowerCamelCase__				=      PRETRAINED_VOCAB_FILES_MAP
   lowerCamelCase__				=      PRETRAINED_LYRIC_TOKENS_SIZES
   lowerCamelCase__				=      ["input_ids", "attention_mask"]





   def __init__(       self					:			List[Any]     , __lowerCamelCase					:			Tuple     , __lowerCamelCase					:			Union[str, Any]     , __lowerCamelCase					:			Optional[int]     , __lowerCamelCase					:			Optional[int]=["v3", "v2", "v2"]     , __lowerCamelCase					:			str=512     , __lowerCamelCase					:			str=5     , __lowerCamelCase					:			List[str]="<|endoftext|>"     , **__lowerCamelCase					:			Tuple     , ):
       SCREAMING_SNAKE_CASE										=   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     , )
       SCREAMING_SNAKE_CASE										=   version
       SCREAMING_SNAKE_CASE										=   max_n_lyric_tokens
       SCREAMING_SNAKE_CASE										=   n_genres

       with open(__lowerCamelCase     , encoding="utf-8"			) as vocab_handle:
           SCREAMING_SNAKE_CASE										=   json.load(__lowerCamelCase			)

       with open(__lowerCamelCase     , encoding="utf-8"			) as vocab_handle:
           SCREAMING_SNAKE_CASE										=   json.load(__lowerCamelCase			)

       with open(__lowerCamelCase     , encoding="utf-8"			) as vocab_handle:
           SCREAMING_SNAKE_CASE										=   json.load(__lowerCamelCase			)

       SCREAMING_SNAKE_CASE										=   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:
           SCREAMING_SNAKE_CASE										=   oov.replace(r"\-'"     , r"\-+'"			)

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





   @property
   def      _snake_case		(       self					:			str			):
       return len(self.artists_encoder			) + len(self.genres_encoder			) + len(self.lyrics_encoder			)





   def      _snake_case		(       self					:			Dict			):
       return dict(self.artists_encoder     , self.genres_encoder     , self.lyrics_encoder			)





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

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





   def      _snake_case		(       self					:			List[Any]     , __lowerCamelCase					:			Any			):
       return list(__lowerCamelCase			)





   def      _snake_case		(       self					:			int     , __lowerCamelCase					:			Optional[int]     , __lowerCamelCase					:			Union[str, Any]     , __lowerCamelCase					:			Dict     , **__lowerCamelCase					:			Any			):
       SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE										=   self.prepare_for_tokenization(__lowerCamelCase     , __lowerCamelCase     , __lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   self._tokenize(__lowerCamelCase			)
       return artist, genre, lyrics





   def      _snake_case		(       self					:			int     , __lowerCamelCase					:			str     , __lowerCamelCase					:			str     , __lowerCamelCase					:			str     , __lowerCamelCase					:			bool = False			):
       for idx in range(len(self.version			)			):
           if self.version[idx] == "v3":
               SCREAMING_SNAKE_CASE										=   artists[idx].lower()
               SCREAMING_SNAKE_CASE										=   [genres[idx].lower()]
           else:
               SCREAMING_SNAKE_CASE										=   self._normalize(artists[idx]			) + ".v2"
               SCREAMING_SNAKE_CASE										=   [
                   self._normalize(__lowerCamelCase			) + ".v2" for genre in genres[idx].split("_"			)
               ]  # split is for the full dictionary with combined genres

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

       SCREAMING_SNAKE_CASE										=   self._run_strip_accents(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   lyrics.replace("\\"     , "\n"			)
       SCREAMING_SNAKE_CASE										=   self.out_of_vocab.sub(""     , __lowerCamelCase			), [], []
       return artists, genres, lyrics





   def      _snake_case		(       self					:			Any     , __lowerCamelCase					:			Union[str, Any]			):
       SCREAMING_SNAKE_CASE										=   unicodedata.normalize("NFD"     , __lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   []
       for char in text:
           SCREAMING_SNAKE_CASE										=   unicodedata.category(__lowerCamelCase			)
           if cat == "Mn":
               continue
           output.append(__lowerCamelCase			)
       return "".join(__lowerCamelCase			)





   def      _snake_case		(       self					:			Any     , __lowerCamelCase					:			str			):
       SCREAMING_SNAKE_CASE										=   (
           [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			)]
           + ["."]
       )
       SCREAMING_SNAKE_CASE										=   frozenset(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   re.compile(r"_+"			)
       SCREAMING_SNAKE_CASE										=   "".join([c if c in accepted else "_" for c in text.lower()]			)
       SCREAMING_SNAKE_CASE										=   pattern.sub("_"     , __lowerCamelCase			).strip("_"			)
       return text





   def      _snake_case		(       self					:			Tuple     , __lowerCamelCase					:			List[str]			):
       return " ".join(__lowerCamelCase			)





   def      _snake_case		(       self					:			Dict     , __lowerCamelCase					:			Union[str, Any]     , __lowerCamelCase					:			Optional[Union[str, TensorType]] = None     , __lowerCamelCase					:			bool = False			):
       # Convert to TensorType
       if not isinstance(__lowerCamelCase     , __lowerCamelCase			):
           SCREAMING_SNAKE_CASE										=   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

           SCREAMING_SNAKE_CASE										=   tf.constant
           SCREAMING_SNAKE_CASE										=   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

           SCREAMING_SNAKE_CASE										=   torch.tensor
           SCREAMING_SNAKE_CASE										=   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

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

       # Do the tensor conversion in batch

       try:
           if prepend_batch_axis:
               SCREAMING_SNAKE_CASE										=   [inputs]

           if not is_tensor(__lowerCamelCase			):
               SCREAMING_SNAKE_CASE										=   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					:			int     , __lowerCamelCase					:			Optional[Any]     , __lowerCamelCase					:			str     , __lowerCamelCase					:			str=""     , __lowerCamelCase					:			Union[str, Any]="pt"			):
       SCREAMING_SNAKE_CASE										=   [0, 0, 0]
       SCREAMING_SNAKE_CASE										=   [artist] * len(self.version			)
       SCREAMING_SNAKE_CASE										=   [genres] * len(self.version			)

       SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE										=   self.tokenize(__lowerCamelCase     , __lowerCamelCase     , __lowerCamelCase			)
       SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE										=   self._convert_token_to_id(__lowerCamelCase     , __lowerCamelCase     , __lowerCamelCase			)

       SCREAMING_SNAKE_CASE										=   [-INFINITY] * len(full_tokens[-1]			)
       SCREAMING_SNAKE_CASE										=   [
           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			):
       if not os.path.isdir(__lowerCamelCase			):
           logger.error(f"Vocabulary path ({save_directory}) should be a directory"			)
           return

       SCREAMING_SNAKE_CASE										=   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			)			)

       SCREAMING_SNAKE_CASE										=   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			)			)

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


from collections.abc import Callable

import numpy as np





def 	__a     (      A__			:  Callable			,  A__			:  float			,  A__			:  float			,  A__			:  float			,  A__			:  float       ):
    SCREAMING_SNAKE_CASE										=   int(np.ceil((x_end - xa) / step_size       )       )
    SCREAMING_SNAKE_CASE										=   np.zeros((n + 1,)       )
    SCREAMING_SNAKE_CASE										=   ya
    SCREAMING_SNAKE_CASE										=   xa

    for k in range(A__       ):
        SCREAMING_SNAKE_CASE										=   y[k] + step_size * ode_func(A__			,  y[k]       )
        SCREAMING_SNAKE_CASE										=   y[k] + (
            (step_size / 2) * (ode_func(A__			,  y[k]       ) + ode_func(x + step_size			,  A__       ))
        )
        x += step_size

    return y


if __name__ == "__main__":
    import doctest

    doctest.testmod()