



'''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


_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''': 512,
}



class _A     (			__A			):
		_SCREAMING_SNAKE_CASE    :			List[str]  					=	VOCAB_FILES_NAMES
		_SCREAMING_SNAKE_CASE    :			str  					=	PRETRAINED_VOCAB_FILES_MAP
		_SCREAMING_SNAKE_CASE    :			List[Any]  					=	PRETRAINED_LYRIC_TOKENS_SIZES
		_SCREAMING_SNAKE_CASE    :			int  					=	['input_ids', 'attention_mask']





		def __init__(   self       ,				__UpperCAmelCase       ,				__UpperCAmelCase       ,				__UpperCAmelCase       ,				__UpperCAmelCase=["v3", "v2", "v2"]       ,				__UpperCAmelCase=512       ,				__UpperCAmelCase=5       ,				__UpperCAmelCase="<|endoftext|>"       ,				**__UpperCAmelCase       ,				)				->   List[Any]:

					'''simple docstring'''
					__UpperCAmelCase      :					Dict   =   AddedToken(__UpperCAmelCase       ,				lstrip=__UpperCAmelCase       ,				rstrip=__UpperCAmelCase ) if isinstance(__UpperCAmelCase       ,				__UpperCAmelCase ) else unk_token
					super().__init__(
					    unk_token=__UpperCAmelCase       ,				n_genres=__UpperCAmelCase       ,				version=__UpperCAmelCase       ,				max_n_lyric_tokens=__UpperCAmelCase       ,				**__UpperCAmelCase       ,				)
					__UpperCAmelCase      :					List[Any]   =   version
					__UpperCAmelCase      :					Tuple   =   max_n_lyric_tokens
					__UpperCAmelCase      :					Any   =   n_genres

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

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

					with open(__UpperCAmelCase       ,				encoding="""utf-8""" ) as vocab_handle:
								__UpperCAmelCase      :					Union[str, Any]   =   json.load(__UpperCAmelCase )

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

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





		@property
		def 							__A				(   self )				->   Optional[int]:

					'''simple docstring'''
					return len(self.artists_encoder ) + len(self.genres_encoder ) + len(self.lyrics_encoder )





		def 							__A				(   self )				->   Tuple:

					'''simple docstring'''
					return dict(self.artists_encoder       ,				self.genres_encoder       ,				self.lyrics_encoder )





		def 							__A				(   self       ,				__UpperCAmelCase       ,				__UpperCAmelCase       ,				__UpperCAmelCase )				->   Optional[int]:

					'''simple docstring'''
					__UpperCAmelCase      :					str   =   [self.artists_encoder.get(__UpperCAmelCase       ,				0 ) for artist in list_artists]
					for genres in range(len(__UpperCAmelCase ) ):
								__UpperCAmelCase      :					Any   =   [self.genres_encoder.get(__UpperCAmelCase       ,				0 ) for genre in list_genres[genres]]
								__UpperCAmelCase      :					Union[str, Any]   =   list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres] ))

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





		def 							__A				(   self       ,				__UpperCAmelCase )				->   List[str]:

					'''simple docstring'''
					return list(__UpperCAmelCase )





		def 							__A				(   self       ,				__UpperCAmelCase       ,				__UpperCAmelCase       ,				__UpperCAmelCase       ,				**__UpperCAmelCase )				->   Optional[int]:

					'''simple docstring'''
					__UpperCAmelCase ,     __UpperCAmelCase ,     __UpperCAmelCase      :					str   =   self.prepare_for_tokenization(__UpperCAmelCase       ,				__UpperCAmelCase       ,				__UpperCAmelCase )
					__UpperCAmelCase      :					List[Any]   =   self._tokenize(__UpperCAmelCase )
					return artist, genre, lyrics





		def 							__A				(   self       ,				__UpperCAmelCase       ,				__UpperCAmelCase       ,				__UpperCAmelCase       ,				__UpperCAmelCase = False )				->   Tuple[str, str, str, Dict[str, Any]]:

					'''simple docstring'''
					for idx in range(len(self.version ) ):
								if self.version[idx] == "v3":
											__UpperCAmelCase      :					Dict   =   artists[idx].lower()
											__UpperCAmelCase      :					Union[str, Any]   =   [genres[idx].lower()]
								else:
											__UpperCAmelCase      :					Union[str, Any]   =   self._normalize(artists[idx] ) + """.v2"""
											__UpperCAmelCase      :					Dict   =   [
											    self._normalize(__UpperCAmelCase ) + """.v2""" for genre in genres[idx].split("""_""" )
											]  # split is for the full dictionary with combined genres

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

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





		def 							__A				(   self       ,				__UpperCAmelCase )				->   str:

					'''simple docstring'''
					__UpperCAmelCase      :					Tuple   =   unicodedata.normalize("""NFD"""       ,				__UpperCAmelCase )
					__UpperCAmelCase      :					Dict   =   []
					for char in text:
								__UpperCAmelCase      :					int   =   unicodedata.category(__UpperCAmelCase )
								if cat == "Mn":
											continue
								output.append(__UpperCAmelCase )
					return "".join(__UpperCAmelCase )





		def 							__A				(   self       ,				__UpperCAmelCase )				->   str:

					'''simple docstring'''
					__UpperCAmelCase      :					Dict   =   (
					    [chr(__UpperCAmelCase ) for i in range(ord("""a""" )       ,				ord("""z""" ) + 1 )]
					    + [chr(__UpperCAmelCase ) for i in range(ord("""A""" )       ,				ord("""Z""" ) + 1 )]
					    + [chr(__UpperCAmelCase ) for i in range(ord("""0""" )       ,				ord("""9""" ) + 1 )]
					    + ["""."""]
					)
					__UpperCAmelCase      :					Any   =   frozenset(__UpperCAmelCase )
					__UpperCAmelCase      :					Any   =   re.compile(r"""_+""" )
					__UpperCAmelCase      :					List[Any]   =   """""".join([c if c in accepted else """_""" for c in text.lower()] )
					__UpperCAmelCase      :					int   =   pattern.sub("""_"""       ,				__UpperCAmelCase ).strip("""_""" )
					return text





		def 							__A				(   self       ,				__UpperCAmelCase )				->   str:

					'''simple docstring'''
					return " ".join(__UpperCAmelCase )





		def 							__A				(   self       ,				__UpperCAmelCase       ,				__UpperCAmelCase = None       ,				__UpperCAmelCase = False )				->   Tuple:

					'''simple docstring'''
					# Convert to TensorType
					if not isinstance(__UpperCAmelCase       ,				__UpperCAmelCase ):
								__UpperCAmelCase      :					Union[str, Any]   =   TensorType(__UpperCAmelCase )

					# 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

								__UpperCAmelCase      :					Union[str, Any]   =   tf.constant
								__UpperCAmelCase      :					List[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

								__UpperCAmelCase      :					Tuple   =   torch.tensor
								__UpperCAmelCase      :					List[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

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

					# Do the tensor conversion in batch

					try:
								if prepend_batch_axis:
											__UpperCAmelCase      :					List[Any]   =   [inputs]

								if not is_tensor(__UpperCAmelCase ):
											__UpperCAmelCase      :					Dict   =   as_tensor(__UpperCAmelCase )
					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       ,				__UpperCAmelCase       ,				__UpperCAmelCase       ,				__UpperCAmelCase=""       ,				__UpperCAmelCase="pt" )				->   BatchEncoding:

					'''simple docstring'''
					__UpperCAmelCase      :					Any   =   [0, 0, 0]
					__UpperCAmelCase      :					str   =   [artist] * len(self.version )
					__UpperCAmelCase      :					List[str]   =   [genres] * len(self.version )

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

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





		def 							__A				(   self       ,				__UpperCAmelCase       ,				__UpperCAmelCase = None )				->   Tuple[str]:

					'''simple docstring'''
					if not os.path.isdir(__UpperCAmelCase ):
								logger.error(f'Vocabulary path ({save_directory}) should be a directory' )
								return

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

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

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

					return (artists_file, genres_file, lyrics_file)





		def 							__A				(   self       ,				__UpperCAmelCase       ,				__UpperCAmelCase       ,				__UpperCAmelCase )				->   Optional[int]:

					'''simple docstring'''
					__UpperCAmelCase      :					str   =   self.artists_decoder.get(__UpperCAmelCase )
					__UpperCAmelCase      :					List[str]   =   [self.genres_decoder.get(__UpperCAmelCase ) for genre in genres_index]
					__UpperCAmelCase      :					Optional[Any]   =   [self.lyrics_decoder.get(__UpperCAmelCase ) for character in lyric_index]
					return artist, genres, lyrics





"""simple docstring"""




from __future__ import annotations

from typing import Generic, TypeVar

__lowerCamelCase							 =     TypeVar("T")
class 			UpperCamelCase__(	Generic[T]       ):





						def __init__(				self						,__UpperCAmelCase   )    -> None:
													A__		   =							data
													A__		   =							self
													A__		   =							0






class 			UpperCamelCase__(	Generic[T]       ):





						def __init__(				self   )    -> None:
													# map from node name to the node object
													A__		   =							{}





						def  snake_case__		(				self						,__UpperCAmelCase   )    -> None:
													# create a new set with x as its member
													A__		   =							DisjointSetTreeNode(__UpperCAmelCase   )





						def  snake_case__		(				self						,__UpperCAmelCase   )    -> DisjointSetTreeNode[T]:
													# find the set x belongs to (with path-compression)
													A__		   =							self.map[data]
													if elem_ref != elem_ref.parent:
																				A__		   =							self.find_set(elem_ref.parent.data   )
													return elem_ref.parent





						def  snake_case__		(				self						,__UpperCAmelCase						,__UpperCAmelCase   )    -> None:
													# helper function for union operation
													if nodea.rank > nodea.rank:
																				A__		   =							nodea
													else:
																				A__		   =							nodea
																				if nodea.rank == nodea.rank:
																											nodea.rank += 1





						def  snake_case__		(				self						,__UpperCAmelCase						,__UpperCAmelCase   )    -> None:
													# merge 2 disjoint sets
													self.link(self.find_set(__UpperCAmelCase   )						,self.find_set(__UpperCAmelCase   )   )






class 			UpperCamelCase__(	Generic[T]       ):





						def __init__(				self   )    -> None:
													# connections: map from the node to the neighbouring nodes (with weights)
													A__		   =							{}





						def  snake_case__		(				self						,__UpperCAmelCase   )    -> None:
													# add a node ONLY if its not present in the graph
													if node not in self.connections:
																				A__		   =							{}





						def  snake_case__		(				self						,__UpperCAmelCase						,__UpperCAmelCase						,__UpperCAmelCase   )    -> None:
													# add an edge with the given weight
													self.add_node(__UpperCAmelCase   )
													self.add_node(__UpperCAmelCase   )
													A__		   =							weight
													A__		   =							weight





						def  snake_case__		(				self   )    -> GraphUndirectedWeighted[T]:
													A__		   =							[]
													A__		   =							set()
													for start in self.connections:
																				for end in self.connections[start]:
																											if (start, end) not in seen:
																																		seen.add((end, start)   )
																																		edges.append((start, end, self.connections[start][end])   )
													edges.sort(key=lambda __UpperCAmelCase   : x[2]   )

													# creating the disjoint set
													A__		   =							DisjointSetTree[T]()
													for node in self.connections:
																				disjoint_set.make_set(__UpperCAmelCase   )

													# MST generation
													A__		   =							0
													A__		   =							0
													A__		   =							GraphUndirectedWeighted[T]()
													while num_edges < len(self.connections   ) - 1:
																				A__   ,     A__   ,     A__		   =							edges[index]
																				index += 1
																				A__		   =							disjoint_set.find_set(__UpperCAmelCase   )
																				A__		   =							disjoint_set.find_set(__UpperCAmelCase   )
																				if parent_u != parent_v:
																											num_edges += 1
																											graph.add_edge(__UpperCAmelCase						,__UpperCAmelCase						,__UpperCAmelCase   )
																											disjoint_set.union(__UpperCAmelCase						,__UpperCAmelCase   )
													return graph





