

"""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					:Union[str, Any]    = logging.get_logger(__name__)

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

a					:List[str]    = {
    "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					:List[str]    = {
    "jukebox": 512,
}

class      __a				(_UpperCamelCase):






     '''simple docstring'''
     _SCREAMING_SNAKE_CASE						:Optional[Any]       = VOCAB_FILES_NAMES
     _SCREAMING_SNAKE_CASE						:List[str]       = PRETRAINED_VOCAB_FILES_MAP
     _SCREAMING_SNAKE_CASE						:int       = PRETRAINED_LYRIC_TOKENS_SIZES
     _SCREAMING_SNAKE_CASE						:List[str]       = ["""input_ids""", """attention_mask"""]

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


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      int      		=	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	,    )
           SCREAMING_SNAKE_CASE__   :      Dict      		=	version
           SCREAMING_SNAKE_CASE__   :      Dict      		=	max_n_lyric_tokens
           SCREAMING_SNAKE_CASE__   :      Dict      		=	n_genres

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

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

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

           SCREAMING_SNAKE_CASE__   :      int      		=	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__   :      Any      		=	oov.replace(r"""\-\'"""	,    r"""\-+\'"""  )

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

     @property
     def 					_a			(						self  )  ->      int:


           """simple docstring"""


           return len(self.artists_encoder  ) + len(self.genres_encoder  ) + len(self.lyrics_encoder  )

     def 					_a			(						self  )  ->      List[Any]:


           """simple docstring"""


           return dict(self.artists_encoder	,    self.genres_encoder	,    self.lyrics_encoder  )

     def 					_a			(						self	,    _a	,    _a	,    _a  )  ->      Dict:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      List[str]      		=	[self.artists_encoder.get(_UpperCAmelCase	,    0  ) for artist in list_artists]
           for genres in range(len(_UpperCAmelCase  )  ):
                 SCREAMING_SNAKE_CASE__   :      int      		=	[self.genres_encoder.get(_UpperCAmelCase	,    0  ) for genre in list_genres[genres]]
                 SCREAMING_SNAKE_CASE__   :      List[Any]      		=	list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]  ))

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

     def 					_a			(						self	,    _a  )  ->      Tuple:


           """simple docstring"""


           return list(_UpperCAmelCase  )

     def 					_a			(						self	,    _a	,    _a	,    _a	,    **_a  )  ->      int:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      str      		=	self.prepare_for_tokenization(_UpperCAmelCase	,    _UpperCAmelCase	,    _UpperCAmelCase  )
           SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	self._tokenize(_UpperCAmelCase  )
           return artist, genre, lyrics

     def 					_a			(						self	,    _a	,    _a	,    _a	,    _a = False  )  ->      Optional[int]:


           """simple docstring"""


           for idx in range(len(self.version  )  ):
                 if self.version[idx] == "v3":
                       SCREAMING_SNAKE_CASE__   :      Any      		=	artists[idx].lower()
                       SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	[genres[idx].lower()]
                 else:
                       SCREAMING_SNAKE_CASE__   :      int      		=	self._normalize(artists[idx]  ) + '''.v2'''
                       SCREAMING_SNAKE_CASE__   :      Tuple      		=	[
                           self._normalize(_UpperCAmelCase  ) + '''.v2''' for genre in genres[idx].split("""_"""  )
                       ]  # split is for the full dictionary with combined genres

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

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

     def 					_a			(						self	,    _a  )  ->      List[Any]:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      str      		=	unicodedata.normalize("""NFD"""	,    _UpperCAmelCase  )
           SCREAMING_SNAKE_CASE__   :      Dict      		=	[]
           for char in text:
                 SCREAMING_SNAKE_CASE__   :      Dict      		=	unicodedata.category(_UpperCAmelCase  )
                 if cat == "Mn":
                       continue
                 output.append(_UpperCAmelCase  )
           return "".join(_UpperCAmelCase  )

     def 					_a			(						self	,    _a  )  ->      Tuple:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      List[str]      		=	(
               [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  )]
               + ['''.''']
           )
           SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	frozenset(_UpperCAmelCase  )
           SCREAMING_SNAKE_CASE__   :      Any      		=	re.compile(r"""_+"""  )
           SCREAMING_SNAKE_CASE__   :      Dict      		=	''''''.join([c if c in accepted else """_""" for c in text.lower()]  )
           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	pattern.sub("""_"""	,    _UpperCAmelCase  ).strip("""_"""  )
           return text

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


           """simple docstring"""


           return " ".join(_UpperCAmelCase  )

     def 					_a			(						self	,    _a	,    _a = None	,    _a = False  )  ->      Optional[Any]:


           """simple docstring"""


           if not isinstance(_UpperCAmelCase	,    _UpperCAmelCase  ):
                 SCREAMING_SNAKE_CASE__   :      Dict      		=	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

                 SCREAMING_SNAKE_CASE__   :      int      		=	tf.constant
                 SCREAMING_SNAKE_CASE__   :      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

                 SCREAMING_SNAKE_CASE__   :      List[Any]      		=	torch.tensor
                 SCREAMING_SNAKE_CASE__   :      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

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

           # Do the tensor conversion in batch

           try:
                 if prepend_batch_axis:
                       SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	[inputs]

                 if not is_tensor(_UpperCAmelCase  ):
                       SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	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	,    _a	,    _a	,    _a=""	,    _a="pt"  )  ->      Any:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      List[Any]      		=	[0, 0, 0]
           SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	[artist] * len(self.version  )
           SCREAMING_SNAKE_CASE__   :      List[str]      		=	[genres] * len(self.version  )

           SCREAMING_SNAKE_CASE__   :      Any      		=	self.tokenize(_UpperCAmelCase	,    _UpperCAmelCase	,    _UpperCAmelCase  )
           SCREAMING_SNAKE_CASE__   :      int      		=	self._convert_token_to_id(_UpperCAmelCase	,    _UpperCAmelCase	,    _UpperCAmelCase  )

           SCREAMING_SNAKE_CASE__   :      List[Any]      		=	[-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=_UpperCAmelCase  )
               for i in range(len(self.version  )  )
           ]
           return BatchEncoding({"""input_ids""": input_ids, """attention_masks""": attention_masks}  )

     def 					_a			(						self	,    _a	,    _a = None  )  ->      Optional[int]:


           """simple docstring"""


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

           SCREAMING_SNAKE_CASE__   :      Any      		=	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  )  )

           SCREAMING_SNAKE_CASE__   :      int      		=	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  )  )

           SCREAMING_SNAKE_CASE__   :      List[Any]      		=	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	,    _a	,    _a	,    _a  )  ->      Union[str, Any]:


           """simple docstring"""


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







"""simple docstring"""


def  _lowercase					(    __lowerCAmelCase  ,					__lowerCAmelCase							)       ->				bool:
      SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	len(__lowerCAmelCase							) + 1
      SCREAMING_SNAKE_CASE__   :      int      		=	len(__lowerCAmelCase							) + 1

      # dp is a 2d matrix where dp[i][j] denotes whether prefix string of
      # length i of input_string matches with prefix string of length j of
      # given pattern.
      # "dp" stands for dynamic programming.
      SCREAMING_SNAKE_CASE__   :      Dict      		=	[[0 for i in range(__lowerCAmelCase							)] for j in range(__lowerCAmelCase							)]

      # since string of zero length match pattern of zero length
      SCREAMING_SNAKE_CASE__   :      Dict      		=	1

      # since pattern of zero length will never match with string of non-zero length
      for i in range(1  ,					__lowerCAmelCase							):
            SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	0

      # since string of zero length will match with pattern where there
      # is at least one * alternatively
      for j in range(1  ,					__lowerCAmelCase							):
            SCREAMING_SNAKE_CASE__   :      int      		=	dp[0][j - 2] if pattern[j - 1] == """*""" else 0

      # now using bottom-up approach to find for all remaining lengths
      for i in range(1  ,					__lowerCAmelCase							):
            for j in range(1  ,					__lowerCAmelCase							):
                  if input_string[i - 1] == pattern[j - 1] or pattern[j - 1] == ".":
                        SCREAMING_SNAKE_CASE__   :      Any      		=	dp[i - 1][j - 1]

                  elif pattern[j - 1] == "*":
                        if dp[i][j - 2] == 1:
                              SCREAMING_SNAKE_CASE__   :      List[str]      		=	1
                        elif pattern[j - 2] in (input_string[i - 1], "."):
                              SCREAMING_SNAKE_CASE__   :      List[Any]      		=	dp[i - 1][j]
                        else:
                              SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	0
                  else:
                        SCREAMING_SNAKE_CASE__   :      Dict      		=	0

      return bool(dp[-1][-1]							)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  # inputing the strings
  # input_string = input("input a string :")
  # pattern = input("input a pattern :")

  a					:Any    = "aab"
  a					:Optional[Any]    = "c*a*b"

  # using function to check whether given string matches the given pattern
  if match_pattern(input_string, pattern):
    print(f'{input_string} matches the given pattern {pattern}')
  else:
    print(f'{input_string} does not match with the given pattern {pattern}')




