
"""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_												= 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 				a ( _SCREAMING_SNAKE_CASE							):





       """simple docstring"""







       A__       :							Tuple    				=				VOCAB_FILES_NAMES
       A__       :							Optional[Any]    				=				PRETRAINED_VOCAB_FILES_MAP
       A__       :							List[str]    				=				PRETRAINED_LYRIC_TOKENS_SIZES
       A__       :							Optional[Any]    				=				["input_ids", "attention_mask"]






       def __init__(			self							,	snake_case_							,	snake_case_							,	snake_case_							,	snake_case_=["v3", "v2", "v2"]							,	snake_case_=512							,	snake_case_=5							,	snake_case_="<|endoftext|>"							,	**snake_case_							,	)    ->				Any:
          _UpperCAmelCase         =      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         =      version
          _UpperCAmelCase         =      max_n_lyric_tokens
          _UpperCAmelCase         =      n_genres

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

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

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

          _UpperCAmelCase         =      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         =      oov.replace(R"\-'"							,	R"\-+'"			)

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






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






       def 				__A						(			self			)    ->				Optional[int]:
          return dict(self.artists_encoder							,	self.genres_encoder							,	self.lyrics_encoder			)






       def 				__A						(			self							,	snake_case_							,	snake_case_							,	snake_case_			)    ->				str:
          _UpperCAmelCase         =      [self.artists_encoder.get(__UpperCamelCase							,	0			) for artist in list_artists]
          for genres in range(len(__UpperCamelCase			)			):
             _UpperCAmelCase         =      [self.genres_encoder.get(__UpperCamelCase							,	0			) for genre in list_genres[genres]]
             _UpperCAmelCase         =      list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]			))

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






       def 				__A						(			self							,	snake_case_			)    ->				str:
          return list(__UpperCamelCase			)






       def 				__A						(			self							,	snake_case_							,	snake_case_							,	snake_case_							,	**snake_case_			)    ->				List[Any]:
          _UpperCAmelCase       ,     _UpperCAmelCase       ,     _UpperCAmelCase         =      self.prepare_for_tokenization(__UpperCamelCase							,	__UpperCamelCase							,	__UpperCamelCase			)
          _UpperCAmelCase         =      self._tokenize(__UpperCamelCase			)
          return artist, genre, lyrics






       def 				__A						(			self							,	snake_case_							,	snake_case_							,	snake_case_							,	snake_case_ = False			)    ->				Optional[Any]:
          for idx in range(len(self.version			)			):
             if self.version[idx] == "v3":
                _UpperCAmelCase         =      artists[idx].lower()
                _UpperCAmelCase         =      [genres[idx].lower()]
             else:
                _UpperCAmelCase         =      self._normalize(artists[idx]			) + ".v2"
                _UpperCAmelCase         =      [
                    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         =      regex.compile(R"[^A-Za-z0-9.,:;!?\-'\"()\[\] \t\n]+"			)
             _UpperCAmelCase         =      "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789.,:;!?-+'\"()[] \t\n"
             _UpperCAmelCase         =      {vocab[index]: index + 1 for index in range(len(__UpperCamelCase			)			)}
             _UpperCAmelCase         =      0
             _UpperCAmelCase         =      len(__UpperCamelCase			) + 1
             _UpperCAmelCase         =      self.vocab
             _UpperCAmelCase         =      {v: k for k, v in self.vocab.items()}
             _UpperCAmelCase         =      ""
          else:
             _UpperCAmelCase         =      regex.compile(R"[^A-Za-z0-9.,:;!?\-+'\"()\[\] \t\n]+"			)

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






       def 				__A						(			self							,	snake_case_			)    ->				Union[str, Any]:
          _UpperCAmelCase         =      unicodedata.normalize("NFD"							,	__UpperCamelCase			)
          _UpperCAmelCase         =      []
          for char in text:
             _UpperCAmelCase         =      unicodedata.category(__UpperCamelCase			)
             if cat == "Mn":
                continue
             output.append(__UpperCamelCase			)
          return "".join(__UpperCamelCase			)






       def 				__A						(			self							,	snake_case_			)    ->				str:
          _UpperCAmelCase         =      (
              [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         =      frozenset(__UpperCamelCase			)
          _UpperCAmelCase         =      re.compile(R"_+"			)
          _UpperCAmelCase         =      "".join([c if c in accepted else "_" for c in text.lower()]			)
          _UpperCAmelCase         =      pattern.sub("_"							,	__UpperCamelCase			).strip("_"			)
          return text






       def 				__A						(			self							,	snake_case_			)    ->				Optional[Any]:
          return " ".join(__UpperCamelCase			)






       def 				__A						(			self							,	snake_case_							,	snake_case_ = None							,	snake_case_ = False			)    ->				int:
          # Convert to TensorType
          if not isinstance(__UpperCamelCase							,	__UpperCamelCase			):
             _UpperCAmelCase         =      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         =      tf.constant
             _UpperCAmelCase         =      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         =      torch.tensor
             _UpperCAmelCase         =      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         =      jnp.array
             _UpperCAmelCase         =      _is_jax
          else:
             _UpperCAmelCase         =      np.asarray
             _UpperCAmelCase         =      _is_numpy

          # Do the tensor conversion in batch

          try:
             if prepend_batch_axis:
                _UpperCAmelCase         =      [inputs]

             if not is_tensor(__UpperCamelCase			):
                _UpperCAmelCase         =      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							,	snake_case_							,	snake_case_							,	snake_case_=""							,	snake_case_="pt"			)    ->				str:
          _UpperCAmelCase         =      [0, 0, 0]
          _UpperCAmelCase         =      [artist] * len(self.version			)
          _UpperCAmelCase         =      [genres] * len(self.version			)

          _UpperCAmelCase       ,     _UpperCAmelCase       ,     _UpperCAmelCase         =      self.tokenize(__UpperCamelCase							,	__UpperCamelCase							,	__UpperCamelCase			)
          _UpperCAmelCase       ,     _UpperCAmelCase       ,     _UpperCAmelCase         =      self._convert_token_to_id(__UpperCamelCase							,	__UpperCamelCase							,	__UpperCamelCase			)

          _UpperCAmelCase         =      [-INFINITY] * len(full_tokens[-1]			)
          _UpperCAmelCase         =      [
              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							,	snake_case_							,	snake_case_ = None			)    ->				List[str]:
          if not os.path.isdir(__UpperCamelCase			):
             logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""			)
             return

          _UpperCAmelCase         =      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         =      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         =      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							,	snake_case_							,	snake_case_							,	snake_case_			)    ->				List[Any]:
          _UpperCAmelCase         =      self.artists_decoder.get(__UpperCamelCase			)
          _UpperCAmelCase         =      [self.genres_decoder.get(__UpperCamelCase			) for genre in genres_index]
          _UpperCAmelCase         =      [self.lyrics_decoder.get(__UpperCamelCase			) for character in lyric_index]
          return artist, genres, lyrics



from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase   =	logging.get_logger(__name__)

lowercase   =	{
    '''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json''',
}





class    __A(					UpperCAmelCase							):
					SCREAMING_SNAKE_CASE           =     '''gpt_neox_japanese'''

					def __init__(						self       :  Union[str, Any] ,       __UpperCamelCase       :  str=3_2_0_0_0 ,       __UpperCamelCase       :  List[Any]=2_5_6_0 ,       __UpperCamelCase       :  Any=3_2 ,       __UpperCamelCase       :  List[str]=3_2 ,       __UpperCamelCase       :  List[str]=4 ,       __UpperCamelCase       :  Dict="gelu" ,       __UpperCamelCase       :  List[Any]=1.00 ,       __UpperCamelCase       :  Any=1_0_0_0_0 ,       __UpperCamelCase       :  Optional[Any]=2_0_4_8 ,       __UpperCamelCase       :  Tuple=0.02 ,       __UpperCamelCase       :  List[str]=1E-5 ,       __UpperCamelCase       :  str=True ,       __UpperCamelCase       :  str=3_1_9_9_6 ,       __UpperCamelCase       :  int=3_1_9_9_9 ,       __UpperCamelCase       :  Optional[Any]=0.1 ,       __UpperCamelCase       :  Tuple=0.0 ,       **__UpperCamelCase       :  List[str] ,       ):
												super().__init__(bos_token_id=__UpperCamelCase ,       eos_token_id=__UpperCamelCase ,       **__UpperCamelCase )
												lowerCamelCase_					=       vocab_size
												lowerCamelCase_					=       max_position_embeddings
												lowerCamelCase_					=       hidden_size
												lowerCamelCase_					=       num_hidden_layers
												lowerCamelCase_					=       num_attention_heads
												lowerCamelCase_					=       intermediate_multiple_size
												lowerCamelCase_					=       hidden_act
												lowerCamelCase_					=       rotary_pct
												lowerCamelCase_					=       rotary_emb_base
												lowerCamelCase_					=       initializer_range
												lowerCamelCase_					=       layer_norm_eps
												lowerCamelCase_					=       use_cache
												lowerCamelCase_					=       attention_dropout
												lowerCamelCase_					=       hidden_dropout





