import torch

from diffusers import DiffusionPipeline

class 					_lowercase    (     UpperCAmelCase__			):






    '''simple docstring'''




    def __init__(    self       ,						lowerCamelCase__       ,						lowerCamelCase__ ):
       super().__init__()

       self.register_modules(unet=lowerCamelCase__       ,						scheduler=lowerCamelCase__ )




    def __call__(    self ):
       lowerCAmelCase_:							Tuple       =	torch.randn(
           (1, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)       ,						)
       lowerCAmelCase_:							int       =	1

       lowerCAmelCase_:							Tuple       =	self.unet(lowerCamelCase__       ,						lowerCamelCase__ ).sample
       lowerCAmelCase_:							List[str]       =	self.scheduler.step(lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ ).prev_sample

       lowerCAmelCase_:							Tuple       =	scheduler_output - scheduler_output + torch.ones_like(lowerCamelCase__ )

       return result
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  :      Optional[Any]            =    {
    """artists_file""": """artists.json""",
    """lyrics_file""": """lyrics.json""",
    """genres_file""": """genres.json""",
}

a  :      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  :      Any            =    {
    """jukebox""": 5_1_2,
}

class 					_lowercase    (     UpperCAmelCase__			):






    '''simple docstring'''
    SCREAMING_SNAKE_CASE:				Optional[int]          =    VOCAB_FILES_NAMES
    SCREAMING_SNAKE_CASE:				Optional[Any]          =    PRETRAINED_VOCAB_FILES_MAP
    SCREAMING_SNAKE_CASE:				List[Any]          =    PRETRAINED_LYRIC_TOKENS_SIZES
    SCREAMING_SNAKE_CASE:				Dict          =    ['input_ids', 'attention_mask']




    def __init__(    self       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__=["v3", "v2", "v2"]       ,						lowerCamelCase__=512       ,						lowerCamelCase__=5       ,						lowerCamelCase__="<|endoftext|>"       ,						**lowerCamelCase__       ,						):
       lowerCAmelCase_:							List[str]       =	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__       ,						)
       lowerCAmelCase_:							Any       =	version
       lowerCAmelCase_:							str       =	max_n_lyric_tokens
       lowerCAmelCase_:							Optional[Any]       =	n_genres

       with open(lowerCamelCase__       ,						encoding="utf-8" ) as vocab_handle:
          lowerCAmelCase_:							List[Any]       =	json.load(lowerCamelCase__ )

       with open(lowerCamelCase__       ,						encoding="utf-8" ) as vocab_handle:
          lowerCAmelCase_:							Tuple       =	json.load(lowerCamelCase__ )

       with open(lowerCamelCase__       ,						encoding="utf-8" ) as vocab_handle:
          lowerCAmelCase_:							Tuple       =	json.load(lowerCamelCase__ )

       lowerCAmelCase_:							List[str]       =	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:
          lowerCAmelCase_:							List[Any]       =	oov.replace(R"\-'"       ,						R"\-+'" )

       lowerCAmelCase_:							List[Any]       =	regex.compile(lowerCamelCase__ )
       lowerCAmelCase_:							Dict       =	{v: k for k, v in self.artists_encoder.items()}
       lowerCAmelCase_:							List[str]       =	{v: k for k, v in self.genres_encoder.items()}
       lowerCAmelCase_:							int       =	{v: k for k, v in self.lyrics_encoder.items()}




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




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




    def      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ ):
       lowerCAmelCase_:							Union[str, Any]       =	[self.artists_encoder.get(lowerCamelCase__       ,						0 ) for artist in list_artists]
       for genres in range(len(lowerCamelCase__ ) ):
          lowerCAmelCase_:							Tuple       =	[self.genres_encoder.get(lowerCamelCase__       ,						0 ) for genre in list_genres[genres]]
          lowerCAmelCase_:							Any       =	list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres] ))

       lowerCAmelCase_:							Optional[Any]       =	[[self.lyrics_encoder.get(lowerCamelCase__       ,						0 ) for character in list_lyrics[0]], [], []]
       return artists_id, list_genres, lyric_ids




    def      _a    (    self       ,						lowerCamelCase__ ):
       return list(lowerCamelCase__ )




    def      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						**lowerCamelCase__ ):
       lowerCAmelCase_  ,	lowerCAmelCase_  ,	lowerCAmelCase_:							Union[str, Any]       =	self.prepare_for_tokenization(lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ )
       lowerCAmelCase_:							Any       =	self._tokenize(lowerCamelCase__ )
       return artist, genre, lyrics




    def      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ = False ):
       for idx in range(len(self.version ) ):
          if self.version[idx] == "v3":
             lowerCAmelCase_:							List[Any]       =	artists[idx].lower()
             lowerCAmelCase_:							Tuple       =	[genres[idx].lower()]
          else:
             lowerCAmelCase_:							Optional[Any]       =	self._normalize(artists[idx] ) + ".v2"
             lowerCAmelCase_:							int       =	[
                 self._normalize(lowerCamelCase__ ) + ".v2" for genre in genres[idx].split("_" )
             ]  # split is for the full dictionary with combined genres

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

       lowerCAmelCase_:							int       =	self._run_strip_accents(lowerCamelCase__ )
       lowerCAmelCase_:							Optional[Any]       =	lyrics.replace("\\"       ,						"\n" )
       lowerCAmelCase_:							List[str]       =	self.out_of_vocab.sub(""       ,						lowerCamelCase__ ), [], []
       return artists, genres, lyrics




    def      _a    (    self       ,						lowerCamelCase__ ):
       lowerCAmelCase_:							int       =	unicodedata.normalize("NFD"       ,						lowerCamelCase__ )
       lowerCAmelCase_:							Any       =	[]
       for char in text:
          lowerCAmelCase_:							Optional[Any]       =	unicodedata.category(lowerCamelCase__ )
          if cat == "Mn":
             continue
          output.append(lowerCamelCase__ )
       return "".join(lowerCamelCase__ )




    def      _a    (    self       ,						lowerCamelCase__ ):
       lowerCAmelCase_:							Tuple       =	(
           [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 )]
           + ["."]
       )
       lowerCAmelCase_:							List[str]       =	frozenset(lowerCamelCase__ )
       lowerCAmelCase_:							Any       =	re.compile(R"_+" )
       lowerCAmelCase_:							List[Any]       =	"".join([c if c in accepted else "_" for c in text.lower()] )
       lowerCAmelCase_:							Union[str, Any]       =	pattern.sub("_"       ,						lowerCamelCase__ ).strip("_" )
       return text




    def      _a    (    self       ,						lowerCamelCase__ ):
       return " ".join(lowerCamelCase__ )




    def      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__ = None       ,						lowerCamelCase__ = False ):
       # Convert to TensorType
       if not isinstance(lowerCamelCase__       ,						lowerCamelCase__ ):
          lowerCAmelCase_:							str       =	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

          lowerCAmelCase_:							Optional[int]       =	tf.constant
          lowerCAmelCase_:							str       =	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

          lowerCAmelCase_:							Optional[Any]       =	torch.tensor
          lowerCAmelCase_:							Optional[Any]       =	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

          lowerCAmelCase_:							Optional[Any]       =	jnp.array
          lowerCAmelCase_:							List[str]       =	_is_jax
       else:
          lowerCAmelCase_:							Optional[int]       =	np.asarray
          lowerCAmelCase_:							int       =	_is_numpy

       # Do the tensor conversion in batch

       try:
          if prepend_batch_axis:
             lowerCAmelCase_:							Any       =	[inputs]

          if not is_tensor(lowerCamelCase__ ):
             lowerCAmelCase_:							Optional[int]       =	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       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__=""       ,						lowerCamelCase__="pt" ):
       lowerCAmelCase_:							Any       =	[0, 0, 0]
       lowerCAmelCase_:							Dict       =	[artist] * len(self.version )
       lowerCAmelCase_:							int       =	[genres] * len(self.version )

       lowerCAmelCase_  ,	lowerCAmelCase_  ,	lowerCAmelCase_:							List[str]       =	self.tokenize(lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ )
       lowerCAmelCase_  ,	lowerCAmelCase_  ,	lowerCAmelCase_:							str       =	self._convert_token_to_id(lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ )

       lowerCAmelCase_:							List[Any]       =	[-INFINITY] * len(full_tokens[-1] )
       lowerCAmelCase_:							Optional[Any]       =	[
           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      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__ = None ):
       if not os.path.isdir(lowerCamelCase__ ):
          logger.error(F'''Vocabulary path ({save_directory}) should be a directory''' )
          return

       lowerCAmelCase_:							Dict       =	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__ ) )

       lowerCAmelCase_:							Optional[Any]       =	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__ ) )

       lowerCAmelCase_:							Dict       =	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      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ ):
       lowerCAmelCase_:							str       =	self.artists_decoder.get(lowerCamelCase__ )
       lowerCAmelCase_:							Optional[int]       =	[self.genres_decoder.get(lowerCamelCase__ ) for genre in genres_index]
       lowerCAmelCase_:							Optional[int]       =	[self.lyrics_decoder.get(lowerCamelCase__ ) for character in lyric_index]
       return artist, genres, lyrics