
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           =  logging.get_logger(__name__)

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

__SCREAMING_SNAKE_CASE           =  {
    '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           =  {
    'jukebox': 512,
}

class 	lowerCamelCase_    ( __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      :			int	,	__lowerCamelCase      :			Union[str, Any]	,	__lowerCamelCase      :			Union[str, Any]	,	__lowerCamelCase      :			List[str]	,	__lowerCamelCase      :			Optional[Any]=["v3", "v2", "v2"]	,	__lowerCamelCase      :			Any=5_12	,	__lowerCamelCase      :			str=5	,	__lowerCamelCase      :			Tuple="<|endoftext|>"	,	**__lowerCamelCase      :			Optional[int]	,	)      ->				Any:
									A							:					Any              =						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							:					Optional[int]              =						version
									A							:					int              =						max_n_lyric_tokens
									A							:					Optional[int]              =						n_genres

									with open(__lowerCamelCase	,	encoding="utf-8" ) as vocab_handle:
												A							:					List[str]              =						json.load(__lowerCamelCase )

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

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

									A							:					Tuple              =						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							:					Optional[Any]              =						oov.replace(r"\-'"	,	r"\-+'" )

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







						@property
						def 			SCREAMING_SNAKE_CASE__		(	self      :			Optional[int] )      ->				Optional[Any]:
									return len(self.artists_encoder ) + len(self.genres_encoder ) + len(self.lyrics_encoder )







						def 			SCREAMING_SNAKE_CASE__		(	self      :			List[Any] )      ->				str:
									return dict(self.artists_encoder	,	self.genres_encoder	,	self.lyrics_encoder )







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

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







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Union[str, Any]	,	__lowerCamelCase      :			Union[str, Any] )      ->				Tuple:
									return list(__lowerCamelCase )







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Tuple	,	__lowerCamelCase      :			List[str]	,	__lowerCamelCase      :			Any	,	__lowerCamelCase      :			Dict	,	**__lowerCamelCase      :			List[str] )      ->				List[str]:
									A							:					List[str]              =						self.prepare_for_tokenization(__lowerCamelCase	,	__lowerCamelCase	,	__lowerCamelCase )
									A							:					List[Any]              =						self._tokenize(__lowerCamelCase )
									return artist, genre, lyrics







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Union[str, Any]	,	__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							:					int              =						artists[idx].lower()
															A							:					str              =						[genres[idx].lower()]
												else:
															A							:					List[Any]              =						self._normalize(artists[idx] ) + ".v2"
															A							:					List[str]              =						[
															    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							:					Union[str, Any]              =						regex.compile(r"[^A-Za-z0-9.,:;!?\-'\"()\[\] \t\n]+" )
												A							:					int              =						"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789.,:;!?-+'\"()[] \t\n"
												A							:					List[Any]              =						{vocab[index]: index + 1 for index in range(len(__lowerCamelCase ) )}
												A							:					List[str]              =						0
												A							:					Optional[int]              =						len(__lowerCamelCase ) + 1
												A							:					int              =						self.vocab
												A							:					List[Any]              =						{v: k for k, v in self.vocab.items()}
												A							:					int              =						""
									else:
												A							:					Optional[Any]              =						regex.compile(r"[^A-Za-z0-9.,:;!?\-+'\"()\[\] \t\n]+" )

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







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Optional[Any]	,	__lowerCamelCase      :			List[str] )      ->				Union[str, Any]:
									A							:					Any              =						unicodedata.normalize("NFD"	,	__lowerCamelCase )
									A							:					List[str]              =						[]
									for char in text:
												A							:					List[str]              =						unicodedata.category(__lowerCamelCase )
												if cat == "Mn":
															continue
												output.append(__lowerCamelCase )
									return "".join(__lowerCamelCase )







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Any	,	__lowerCamelCase      :			str )      ->				str:
									A							:					Any              =						(
									    [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							:					Tuple              =						frozenset(__lowerCamelCase )
									A							:					Dict              =						re.compile(r"_+" )
									A							:					Optional[int]              =						"".join([c if c in accepted else "_" for c in text.lower()] )
									A							:					Tuple              =						pattern.sub("_"	,	__lowerCamelCase ).strip("_" )
									return text







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Dict	,	__lowerCamelCase      :			List[str] )      ->				str:
									return " ".join(__lowerCamelCase )







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Optional[int]	,	__lowerCamelCase      :			int	,	__lowerCamelCase      :			Optional[Union[str, TensorType]] = None	,	__lowerCamelCase      :			bool = False )      ->				Dict:
									# Convert to TensorType
									if not isinstance(__lowerCamelCase	,	__lowerCamelCase ):
												A							:					Dict              =						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							:					int              =						tf.constant
												A							:					Optional[int]              =						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							:					Optional[int]              =						torch.tensor
												A							:					int              =						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							:					Dict              =						jnp.array
												A							:					Dict              =						_is_jax
									else:
												A							:					Union[str, Any]              =						np.asarray
												A							:					Union[str, Any]              =						_is_numpy

									# Do the tensor conversion in batch

									try:
												if prepend_batch_axis:
															A							:					List[str]              =						[inputs]

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

									A							:					Optional[Any]              =						self.tokenize(__lowerCamelCase	,	__lowerCamelCase	,	__lowerCamelCase )
									A							:					List[str]              =						self._convert_token_to_id(__lowerCamelCase	,	__lowerCamelCase	,	__lowerCamelCase )

									A							:					Union[str, Any]              =						[-INFINITY] * len(full_tokens[-1] )
									A							:					Dict              =						[
									    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 			SCREAMING_SNAKE_CASE__		(	self      :			str	,	__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							:					Union[str, Any]              =						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							:					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 ) )

									A							:					Tuple              =						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 			SCREAMING_SNAKE_CASE__		(	self      :			Tuple	,	__lowerCamelCase      :			Dict	,	__lowerCamelCase      :			int	,	__lowerCamelCase      :			Optional[int] )      ->				Union[str, Any]:
									A							:					Tuple              =						self.artists_decoder.get(__lowerCamelCase )
									A							:					Dict              =						[self.genres_decoder.get(__lowerCamelCase ) for genre in genres_index]
									A							:					str              =						[self.lyrics_decoder.get(__lowerCamelCase ) for character in lyric_index]
									return artist, genres, lyrics




from collections.abc import Sequence




def 	UpperCAmelCase   (						_lowerCamelCase = None    ):
			if nums is None or not nums:
						raise ValueError("Input sequence should not be empty"    )

			A							:					Dict              =						nums[0]
			for i in range(1 ,    len(_lowerCamelCase    )    ):
						A							:					Tuple              =						nums[i]
						A							:					List[Any]              =						max(_lowerCamelCase ,    ans + num ,    _lowerCamelCase    )

			return ans


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							# Try on a sample input from the user
							__SCREAMING_SNAKE_CASE           =  int(input("""Enter number of elements : """).strip())
							__SCREAMING_SNAKE_CASE           =  list(map(int, input("""\nEnter the numbers : """).strip().split()))[:n]
							print(max_subsequence_sum(array))