

'''simple docstring'''

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							:				Any     	=			logging.get_logger(__name__)

SCREAMING_SNAKE_CASE							:				List[Any]     	=			{
    "artists_file": "artists.json",
    "lyrics_file": "lyrics.json",
    "genres_file": "genres.json",
}

SCREAMING_SNAKE_CASE							:				Any     	=			{
    "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							:				Dict     	=			{
    "jukebox": 512,
}






class    snake_case     (      lowercase_		):






				"""simple docstring"""
				_a    	=     VOCAB_FILES_NAMES
				_a    	=     PRETRAINED_VOCAB_FILES_MAP
				_a    	=     PRETRAINED_LYRIC_TOKENS_SIZES
				_a    	=     ["""input_ids""", """attention_mask"""]



				def __init__(    self,     _lowercase,     _lowercase,     _lowercase,     _lowercase=["v3", "v2", "v2"],     _lowercase=512,     _lowercase=5,     _lowercase="<|endoftext|>",     **_lowercase,     )     ->							Union[str, Any]:
											SCREAMING_SNAKE_CASE_				=				AddedToken(_lowercase,     lstrip=_lowercase,     rstrip=_lowercase       ) if isinstance(_lowercase,     _lowercase       ) else unk_token
											super().__init__(
											    unk_token=_lowercase,     n_genres=_lowercase,     version=_lowercase,     max_n_lyric_tokens=_lowercase,     **_lowercase,     )
											SCREAMING_SNAKE_CASE_				=				version
											SCREAMING_SNAKE_CASE_				=				max_n_lyric_tokens
											SCREAMING_SNAKE_CASE_				=				n_genres

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

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

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

											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(_lowercase       )
											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   a__					(    self       )     ->							List[Any]:
											return len(self.artists_encoder       ) + len(self.genres_encoder       ) + len(self.lyrics_encoder       )



				def   a__					(    self       )     ->							Tuple:
											return dict(self.artists_encoder,     self.genres_encoder,     self.lyrics_encoder       )



				def   a__					(    self,     _lowercase,     _lowercase,     _lowercase       )     ->							Dict:
											SCREAMING_SNAKE_CASE_				=				[self.artists_encoder.get(_lowercase,     0       ) for artist in list_artists]
											for genres in range(len(_lowercase       )       ):
																		SCREAMING_SNAKE_CASE_				=				[self.genres_encoder.get(_lowercase,     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(_lowercase,     0       ) for character in list_lyrics[0]], [], []]
											return artists_id, list_genres, lyric_ids



				def   a__					(    self,     _lowercase       )     ->							List[str]:
											return list(_lowercase       )



				def   a__					(    self,     _lowercase,     _lowercase,     _lowercase,     **_lowercase       )     ->							Union[str, Any]:
											SCREAMING_SNAKE_CASE_				,    SCREAMING_SNAKE_CASE_				,    SCREAMING_SNAKE_CASE_				=				self.prepare_for_tokenization(_lowercase,     _lowercase,     _lowercase       )
											SCREAMING_SNAKE_CASE_				=				self._tokenize(_lowercase       )
											return artist, genre, lyrics



				def   a__					(    self,     _lowercase,     _lowercase,     _lowercase,     _lowercase = False       )     ->							Tuple[str, str, str, Dict[str, Any]]:
											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(_lowercase       ) + '.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(_lowercase       )       )}
																		SCREAMING_SNAKE_CASE_				=				0
																		SCREAMING_SNAKE_CASE_				=				len(_lowercase       ) + 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(_lowercase       )
											SCREAMING_SNAKE_CASE_				=				lyrics.replace('\\',     '\n'       )
											SCREAMING_SNAKE_CASE_				=				self.out_of_vocab.sub('',     _lowercase       ), [], []
											return artists, genres, lyrics



				def   a__					(    self,     _lowercase       )     ->							Any:
											SCREAMING_SNAKE_CASE_				=				unicodedata.normalize('NFD',     _lowercase       )
											SCREAMING_SNAKE_CASE_				=				[]
											for char in text:
																		SCREAMING_SNAKE_CASE_				=				unicodedata.category(_lowercase       )
																		if cat == "Mn":
																									continue
																		output.append(_lowercase       )
											return "".join(_lowercase       )



				def   a__					(    self,     _lowercase       )     ->							str:
											SCREAMING_SNAKE_CASE_				=				(
											    [chr(_lowercase       ) for i in range(ord('a'       ),     ord('z'       ) + 1       )]
											    + [chr(_lowercase       ) for i in range(ord('A'       ),     ord('Z'       ) + 1       )]
											    + [chr(_lowercase       ) for i in range(ord('0'       ),     ord('9'       ) + 1       )]
											    + ['.']
											)
											SCREAMING_SNAKE_CASE_				=				frozenset(_lowercase       )
											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('_',     _lowercase       ).strip('_'       )
											return text



				def   a__					(    self,     _lowercase       )     ->							str:
											return " ".join(_lowercase       )



				def   a__					(    self,     _lowercase,     _lowercase = None,     _lowercase = False       )     ->							List[Any]:
											# Convert to TensorType
											if not isinstance(_lowercase,     _lowercase       ):
																		SCREAMING_SNAKE_CASE_				=				TensorType(_lowercase       )

											# 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(_lowercase       ):
																									SCREAMING_SNAKE_CASE_				=				as_tensor(_lowercase       )
											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,     _lowercase,     _lowercase,     _lowercase="",     _lowercase="pt"       )     ->							BatchEncoding:
											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(_lowercase,     _lowercase,     _lowercase       )
											SCREAMING_SNAKE_CASE_				,    SCREAMING_SNAKE_CASE_				,    SCREAMING_SNAKE_CASE_				=				self._convert_token_to_id(_lowercase,     _lowercase,     _lowercase       )

											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=_lowercase       )
											    for i in range(len(self.version       )       )
											]
											return BatchEncoding({'input_ids': input_ids, 'attention_masks': attention_masks}       )



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

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

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

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

											return (artists_file, genres_file, lyrics_file)





				def   a__					(    self,     _lowercase,     _lowercase,     _lowercase       )     ->							int:
											SCREAMING_SNAKE_CASE_				=				self.artists_decoder.get(_lowercase       )
											SCREAMING_SNAKE_CASE_				=				[self.genres_decoder.get(_lowercase       ) for genre in genres_index]
											SCREAMING_SNAKE_CASE_				=				[self.lyrics_decoder.get(_lowercase       ) for character in lyric_index]
											return artist, genres, lyrics








'''simple docstring'''

import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class    snake_case     (      lowercase_		):






				"""simple docstring"""
				_a    	=     ["""image_processor""", """tokenizer"""]
				_a    	=     """CLIPImageProcessor"""
				_a    	=     ("""XLMRobertaTokenizer""", """XLMRobertaTokenizerFast""")



				def __init__(    self,     _lowercase=None,     _lowercase=None,     **_lowercase       )     ->							int:
											SCREAMING_SNAKE_CASE_				=				None
											if "feature_extractor" in kwargs:
																		warnings.warn(
																		    'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
																		    ' instead.',     _lowercase,     )
																		SCREAMING_SNAKE_CASE_				=				kwargs.pop('feature_extractor'       )

											SCREAMING_SNAKE_CASE_				=				image_processor if image_processor is not None else feature_extractor
											if image_processor is None:
																		raise ValueError('You need to specify an `image_processor`.'       )
											if tokenizer is None:
																		raise ValueError('You need to specify a `tokenizer`.'       )

											super().__init__(_lowercase,     _lowercase       )



				def __call__(    self,     _lowercase=None,     _lowercase=None,     _lowercase=None,     **_lowercase       )     ->							str:

											if text is None and images is None:
																		raise ValueError('You have to specify either text or images. Both cannot be none.'       )

											if text is not None:
																		SCREAMING_SNAKE_CASE_				=				self.tokenizer(_lowercase,     return_tensors=_lowercase,     **_lowercase       )

											if images is not None:
																		SCREAMING_SNAKE_CASE_				=				self.image_processor(_lowercase,     return_tensors=_lowercase,     **_lowercase       )

											if text is not None and images is not None:
																		SCREAMING_SNAKE_CASE_				=				image_features.pixel_values
																		return encoding
											elif text is not None:
																		return encoding
											else:
																		return BatchEncoding(data=dict(**_lowercase       ),     tensor_type=_lowercase       )



				def   a__					(    self,     *_lowercase,     **_lowercase       )     ->							Optional[int]:
											return self.tokenizer.batch_decode(*_lowercase,     **_lowercase       )



				def   a__					(    self,     *_lowercase,     **_lowercase       )     ->							Optional[Any]:
											return self.tokenizer.decode(*_lowercase,     **_lowercase       )





				@property
				def   a__					(    self       )     ->							Optional[int]:
											SCREAMING_SNAKE_CASE_				=				self.tokenizer.model_input_names
											SCREAMING_SNAKE_CASE_				=				self.image_processor.model_input_names
											return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names       )       )





