

'''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


A_       						=							logging.get_logger(__name__)

A_       						=							{
    "artists_file": "artists.json",
    "lyrics_file": "lyrics.json",
    "genres_file": "genres.json",
}

A_       						=							{
    "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_       						=							{
    "jukebox": 5_12,
}





class 							_snake_case (       _a						):
   _A       :     Tuple       =					VOCAB_FILES_NAMES
   _A       :     Optional[int]       =					PRETRAINED_VOCAB_FILES_MAP
   _A       :     List[str]       =					PRETRAINED_LYRIC_TOKENS_SIZES
   _A       :     Tuple       =					['''input_ids''', '''attention_mask''']
   def __init__( self			:      str     ,SCREAMING_SNAKE_CASE__			:      int     ,SCREAMING_SNAKE_CASE__			:      List[Any]     ,SCREAMING_SNAKE_CASE__			:      str     ,SCREAMING_SNAKE_CASE__			:      Tuple=["v3", "v2", "v2"]     ,SCREAMING_SNAKE_CASE__			:      Union[str, Any]=512     ,SCREAMING_SNAKE_CASE__			:      Dict=5     ,SCREAMING_SNAKE_CASE__			:      Optional[int]="<|endoftext|>"     ,**SCREAMING_SNAKE_CASE__			:      Dict     ,):
     SCREAMING_SNAKE_CASE:int						      =					AddedToken(SCREAMING_SNAKE_CASE__     ,lstrip=SCREAMING_SNAKE_CASE__     ,rstrip=SCREAMING_SNAKE_CASE__							) if isinstance(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							) else unk_token
     super().__init__(
         unk_token=SCREAMING_SNAKE_CASE__     ,n_genres=SCREAMING_SNAKE_CASE__     ,version=SCREAMING_SNAKE_CASE__     ,max_n_lyric_tokens=SCREAMING_SNAKE_CASE__     ,**SCREAMING_SNAKE_CASE__     ,)
     SCREAMING_SNAKE_CASE:Union[str, Any]						      =					version
     SCREAMING_SNAKE_CASE:Tuple						      =					max_n_lyric_tokens
     SCREAMING_SNAKE_CASE:Dict						      =					n_genres

     with open(SCREAMING_SNAKE_CASE__     ,encoding="utf-8"							) as vocab_handle:
       SCREAMING_SNAKE_CASE:Any						      =					json.load(SCREAMING_SNAKE_CASE__							)

     with open(SCREAMING_SNAKE_CASE__     ,encoding="utf-8"							) as vocab_handle:
       SCREAMING_SNAKE_CASE:Any						      =					json.load(SCREAMING_SNAKE_CASE__							)

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

     SCREAMING_SNAKE_CASE:Union[str, 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:
       SCREAMING_SNAKE_CASE:Dict						      =					oov.replace(R"\-'"     ,R"\-+'"							)

     SCREAMING_SNAKE_CASE:str						      =					regex.compile(SCREAMING_SNAKE_CASE__							)
     SCREAMING_SNAKE_CASE:List[str]						      =					{v: k for k, v in self.artists_encoder.items()}
     SCREAMING_SNAKE_CASE:Any						      =					{v: k for k, v in self.genres_encoder.items()}
     SCREAMING_SNAKE_CASE:Tuple						      =					{v: k for k, v in self.lyrics_encoder.items()}
   @property
   def     __UpperCamelCase						( self			:      Any							):
     return len(self.artists_encoder							) + len(self.genres_encoder							) + len(self.lyrics_encoder							)
   def     __UpperCamelCase						( self			:      Any							):
     return dict(self.artists_encoder     ,self.genres_encoder     ,self.lyrics_encoder							)
   def     __UpperCamelCase						( self			:      Any     ,SCREAMING_SNAKE_CASE__			:      int     ,SCREAMING_SNAKE_CASE__			:      List[str]     ,SCREAMING_SNAKE_CASE__			:      Optional[Any]							):
     SCREAMING_SNAKE_CASE:Optional[Any]						      =					[self.artists_encoder.get(SCREAMING_SNAKE_CASE__     ,0							) for artist in list_artists]
     for genres in range(len(SCREAMING_SNAKE_CASE__							)							):
       SCREAMING_SNAKE_CASE:Union[str, Any]						      =					[self.genres_encoder.get(SCREAMING_SNAKE_CASE__     ,0							) for genre in list_genres[genres]]
       SCREAMING_SNAKE_CASE:List[str]						      =					list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]							))

     SCREAMING_SNAKE_CASE:Tuple						      =					[[self.lyrics_encoder.get(SCREAMING_SNAKE_CASE__     ,0							) for character in list_lyrics[0]], [], []]
     return artists_id, list_genres, lyric_ids
   def     __UpperCamelCase						( self			:      Any     ,SCREAMING_SNAKE_CASE__			:      Dict							):
     return list(SCREAMING_SNAKE_CASE__							)
   def     __UpperCamelCase						( self			:      Union[str, Any]     ,SCREAMING_SNAKE_CASE__			:      Optional[int]     ,SCREAMING_SNAKE_CASE__			:      Union[str, Any]     ,SCREAMING_SNAKE_CASE__			:      Optional[int]     ,**SCREAMING_SNAKE_CASE__			:      Union[str, Any]							):
     SCREAMING_SNAKE_CASE      ,    SCREAMING_SNAKE_CASE      ,    SCREAMING_SNAKE_CASE:Optional[int]						      =					self.prepare_for_tokenization(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)
     SCREAMING_SNAKE_CASE:Optional[int]						      =					self._tokenize(SCREAMING_SNAKE_CASE__							)
     return artist, genre, lyrics
   def     __UpperCamelCase						( self			:      Any     ,SCREAMING_SNAKE_CASE__			:      str     ,SCREAMING_SNAKE_CASE__			:      str     ,SCREAMING_SNAKE_CASE__			:      str     ,SCREAMING_SNAKE_CASE__			:      bool = False							):
     for idx in range(len(self.version							)							):
       if self.version[idx] == "v3":
         SCREAMING_SNAKE_CASE:Union[str, Any]						      =					artists[idx].lower()
         SCREAMING_SNAKE_CASE:Union[str, Any]						      =					[genres[idx].lower()]
       else:
         SCREAMING_SNAKE_CASE:Any						      =					self._normalize(artists[idx]							) + ".v2"
         SCREAMING_SNAKE_CASE:int						      =					[
             self._normalize(SCREAMING_SNAKE_CASE__							) + ".v2" for genre in genres[idx].split("_"							)
         ]  # split is for the full dictionary with combined genres

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

     SCREAMING_SNAKE_CASE:int						      =					self._run_strip_accents(SCREAMING_SNAKE_CASE__							)
     SCREAMING_SNAKE_CASE:Union[str, Any]						      =					lyrics.replace("\\"     ,"\n"							)
     SCREAMING_SNAKE_CASE:Optional[Any]						      =					self.out_of_vocab.sub(""     ,SCREAMING_SNAKE_CASE__							), [], []
     return artists, genres, lyrics
   def     __UpperCamelCase						( self			:      Optional[Any]     ,SCREAMING_SNAKE_CASE__			:      Union[str, Any]							):
     SCREAMING_SNAKE_CASE:Union[str, Any]						      =					unicodedata.normalize("NFD"     ,SCREAMING_SNAKE_CASE__							)
     SCREAMING_SNAKE_CASE:Optional[Any]						      =					[]
     for char in text:
       SCREAMING_SNAKE_CASE:Union[str, Any]						      =					unicodedata.category(SCREAMING_SNAKE_CASE__							)
       if cat == "Mn":
         continue
       output.append(SCREAMING_SNAKE_CASE__							)
     return "".join(SCREAMING_SNAKE_CASE__							)
   def     __UpperCamelCase						( self			:      Any     ,SCREAMING_SNAKE_CASE__			:      str							):
     SCREAMING_SNAKE_CASE:Optional[int]						      =					(
         [chr(SCREAMING_SNAKE_CASE__							) for i in range(ord("a"							)     ,ord("z"							) + 1							)]
         + [chr(SCREAMING_SNAKE_CASE__							) for i in range(ord("A"							)     ,ord("Z"							) + 1							)]
         + [chr(SCREAMING_SNAKE_CASE__							) for i in range(ord("0"							)     ,ord("9"							) + 1							)]
         + ["."]
     )
     SCREAMING_SNAKE_CASE:List[str]						      =					frozenset(SCREAMING_SNAKE_CASE__							)
     SCREAMING_SNAKE_CASE:Union[str, Any]						      =					re.compile(R"_+"							)
     SCREAMING_SNAKE_CASE:Tuple						      =					"".join([c if c in accepted else "_" for c in text.lower()]							)
     SCREAMING_SNAKE_CASE:Tuple						      =					pattern.sub("_"     ,SCREAMING_SNAKE_CASE__							).strip("_"							)
     return text
   def     __UpperCamelCase						( self			:      List[Any]     ,SCREAMING_SNAKE_CASE__			:      List[str]							):
     return " ".join(SCREAMING_SNAKE_CASE__							)
   def     __UpperCamelCase						( self			:      List[str]     ,SCREAMING_SNAKE_CASE__			:      Union[str, Any]     ,SCREAMING_SNAKE_CASE__			:      Optional[Union[str, TensorType]] = None     ,SCREAMING_SNAKE_CASE__			:      bool = False							):
     # Convert to TensorType
     if not isinstance(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							):
       SCREAMING_SNAKE_CASE:List[str]						      =					TensorType(SCREAMING_SNAKE_CASE__							)

     # 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:List[str]						      =					tf.constant
       SCREAMING_SNAKE_CASE:List[Any]						      =					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:Dict						      =					torch.tensor
       SCREAMING_SNAKE_CASE:Optional[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

       SCREAMING_SNAKE_CASE:Any						      =					jnp.array
       SCREAMING_SNAKE_CASE:Dict						      =					_is_jax
     else:
       SCREAMING_SNAKE_CASE:List[Any]						      =					np.asarray
       SCREAMING_SNAKE_CASE:Union[str, Any]						      =					_is_numpy

     # Do the tensor conversion in batch

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

       if not is_tensor(SCREAMING_SNAKE_CASE__							):
         SCREAMING_SNAKE_CASE:int						      =					as_tensor(SCREAMING_SNAKE_CASE__							)
     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			:      int     ,SCREAMING_SNAKE_CASE__			:      str     ,SCREAMING_SNAKE_CASE__			:      Optional[int]     ,SCREAMING_SNAKE_CASE__			:      Optional[Any]=""     ,SCREAMING_SNAKE_CASE__			:      Optional[int]="pt"							):
     SCREAMING_SNAKE_CASE:Optional[int]						      =					[0, 0, 0]
     SCREAMING_SNAKE_CASE:Union[str, Any]						      =					[artist] * len(self.version							)
     SCREAMING_SNAKE_CASE:List[Any]						      =					[genres] * len(self.version							)

     SCREAMING_SNAKE_CASE      ,    SCREAMING_SNAKE_CASE      ,    SCREAMING_SNAKE_CASE:Tuple						      =					self.tokenize(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)
     SCREAMING_SNAKE_CASE      ,    SCREAMING_SNAKE_CASE      ,    SCREAMING_SNAKE_CASE:Optional[int]						      =					self._convert_token_to_id(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)

     SCREAMING_SNAKE_CASE:Tuple						      =					[-INFINITY] * len(full_tokens[-1]							)
     SCREAMING_SNAKE_CASE:str						      =					[
         self.convert_to_tensors(
             [input_ids + [artists_id[i]] + genres_ids[i] + full_tokens[i]]     ,tensor_type=SCREAMING_SNAKE_CASE__							)
         for i in range(len(self.version							)							)
     ]
     return BatchEncoding({"input_ids": input_ids, "attention_masks": attention_masks}							)
   def     __UpperCamelCase						( self			:      Dict     ,SCREAMING_SNAKE_CASE__			:      str     ,SCREAMING_SNAKE_CASE__			:      Optional[str] = None							):
     if not os.path.isdir(SCREAMING_SNAKE_CASE__							):
       logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''							)
       return

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

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

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

     return (artists_file, genres_file, lyrics_file)







   def     __UpperCamelCase						( self			:      Dict     ,SCREAMING_SNAKE_CASE__			:      Tuple     ,SCREAMING_SNAKE_CASE__			:      Optional[Any]     ,SCREAMING_SNAKE_CASE__			:      List[str]							):
     SCREAMING_SNAKE_CASE:Union[str, Any]						      =					self.artists_decoder.get(SCREAMING_SNAKE_CASE__							)
     SCREAMING_SNAKE_CASE:Union[str, Any]						      =					[self.genres_decoder.get(SCREAMING_SNAKE_CASE__							) for genre in genres_index]
     SCREAMING_SNAKE_CASE:Dict						      =					[self.lyrics_decoder.get(SCREAMING_SNAKE_CASE__							) for character in lyric_index]
     return artist, genres, lyrics









'''simple docstring'''

import argparse
import importlib
from pathlib import Path


# Test all the extensions added in the setup
A_       						=							[
    "kernels/rwkv/wkv_cuda.cu",
    "kernels/rwkv/wkv_op.cpp",
    "kernels/deformable_detr/ms_deform_attn.h",
    "kernels/deformable_detr/cuda/ms_deform_im2col_cuda.cuh",
    "models/graphormer/algos_graphormer.pyx",
]





def    A_  ( snake_case ):
  # Test all the extensions added in the setup
  for file in FILES_TO_FIND:
    if not (transformers_path / file).exists():
      return False
  return True


if __name__ == "__main__":
    A_       						=							argparse.ArgumentParser()
    parser.add_argument("--check_lib", action="store_true", help="Whether to check the build or the actual package.")
    A_       						=							parser.parse_args()
    if args.check_lib:
        A_       						=							importlib.import_module("transformers")
        A_       						=							Path(transformers_module.__file__).parent
    else:
        A_       						=							Path.cwd() / "build/lib/transformers"
    if not test_custom_files_are_present(transformers_path):
        raise ValueError("The built release does not contain the custom files. Fix this before going further!")






