'''simple docstring'''




import unittest

from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__lowercase        =    get_tests_dir('''fixtures/test_sentencepiece.model''')






@require_sentencepiece
class 							a__(   __snake_case					,		unittest.TestCase      ):


			'''simple docstring'''






			UpperCAmelCase_     :	Optional[Any]						=			XLMProphetNetTokenizer
			UpperCAmelCase_     :	Optional[int]						=			False
			UpperCAmelCase_     :	Optional[int]						=			True



			def 				a_			(  self):




					"""simple docstring"""


					super().setUp()

					# We have a SentencePiece fixture for testing
					lowerCAmelCase     =    XLMProphetNetTokenizer(__lowerCAmelCase			,       keep_accents=__lowerCAmelCase)
					tokenizer.save_pretrained(self.tmpdirname)



			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    """[PAD]"""
					lowerCAmelCase     =    0

					self.assertEqual(self.get_tokenizer()._convert_token_to_id(__lowerCAmelCase)			,       __lowerCAmelCase)
					self.assertEqual(self.get_tokenizer()._convert_id_to_token(__lowerCAmelCase)			,       __lowerCAmelCase)



			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    list(self.get_tokenizer().get_vocab().keys())

					self.assertEqual(vocab_keys[0]			,       """[PAD]""")
					self.assertEqual(vocab_keys[1]			,       """[CLS]""")
					self.assertEqual(vocab_keys[-1]			,       """j""")
					self.assertEqual(len(__lowerCAmelCase)			,       1012)



			def 				a_			(  self):




					"""simple docstring"""


					self.assertEqual(self.get_tokenizer().vocab_size			,       1012)



			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    XLMProphetNetTokenizer(__lowerCAmelCase			,       keep_accents=__lowerCAmelCase)

					lowerCAmelCase     =    tokenizer.tokenize("""This is a test""")
					self.assertListEqual(__lowerCAmelCase			,       ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""])

					self.assertListEqual(
					    tokenizer.convert_tokens_to_ids(__lowerCAmelCase)			,       [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]			,       )

					lowerCAmelCase     =    tokenizer.tokenize("""I was born in 92000, and this is falsé.""")
					self.assertListEqual(
					    __lowerCAmelCase			,       [
					        SPIECE_UNDERLINE + """I""",
					        SPIECE_UNDERLINE + """was""",
					        SPIECE_UNDERLINE + """b""",
					        """or""",
					        """n""",
					        SPIECE_UNDERLINE + """in""",
					        SPIECE_UNDERLINE + """""",
					        """9""",
					        """2""",
					        """0""",
					        """0""",
					        """0""",
					        """,""",
					        SPIECE_UNDERLINE + """and""",
					        SPIECE_UNDERLINE + """this""",
					        SPIECE_UNDERLINE + """is""",
					        SPIECE_UNDERLINE + """f""",
					        """al""",
					        """s""",
					        """é""",
					        """.""",
					    ]			,       )
					lowerCAmelCase     =    tokenizer.convert_tokens_to_ids(__lowerCAmelCase)
					self.assertListEqual(
					    __lowerCAmelCase			,       [
					        value + tokenizer.fairseq_offset
					        for value in [8, 21, 84, 55, 24, 19, 7, -9, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, -9, 4]
					    ]			,       )

					lowerCAmelCase     =    tokenizer.convert_ids_to_tokens(__lowerCAmelCase)
					self.assertListEqual(
					    __lowerCAmelCase			,       [
					        SPIECE_UNDERLINE + """I""",
					        SPIECE_UNDERLINE + """was""",
					        SPIECE_UNDERLINE + """b""",
					        """or""",
					        """n""",
					        SPIECE_UNDERLINE + """in""",
					        SPIECE_UNDERLINE + """""",
					        """[UNK]""",
					        """2""",
					        """0""",
					        """0""",
					        """0""",
					        """,""",
					        SPIECE_UNDERLINE + """and""",
					        SPIECE_UNDERLINE + """this""",
					        SPIECE_UNDERLINE + """is""",
					        SPIECE_UNDERLINE + """f""",
					        """al""",
					        """s""",
					        """[UNK]""",
					        """.""",
					    ]			,       )



			@cached_property
			def 				a_			(  self):




					"""simple docstring"""


					return XLMProphetNetTokenizer.from_pretrained("""microsoft/xprophetnet-large-wiki100-cased""")



			@slow
			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    """Hello World!"""
					lowerCAmelCase     =    [35389, 6672, 49, 2]
					self.assertListEqual(__lowerCAmelCase			,       self.big_tokenizer.encode(__lowerCAmelCase))







			@slow
			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    {"""input_ids""": [[11073, 82783, 18, 26, 82783, 549, 51540, 248, 17209, 1301, 217, 20, 215186, 1325, 147, 17209, 1301, 217, 20, 56370, 53, 122020, 20, 16477, 27, 87355, 4548, 20, 4728, 78392, 17, 159969, 18, 26, 24491, 629, 15, 538, 22704, 5439, 15, 2788, 24491, 9885, 15, 43534, 605, 15, 814, 18403, 33200, 29, 15, 43534, 24458, 12410, 111, 24966, 83669, 9637, 144068, 26, 850, 22346, 27, 147, 24966, 83669, 83490, 26, 39113, 735, 27, 689, 656, 2800, 1339, 4600, 53, 122020, 115785, 34, 816, 1339, 46887, 18, 147, 53905, 1951, 42238, 41170, 17732, 834, 436, 15, 27523, 98733, 217, 147, 5542, 4981, 930, 17347, 16, 2], [20091, 629, 94, 82786, 58, 490, 20, 1528, 84, 53905, 344, 80592, 110128, 18822, 5267, 1306, 62, 152537, 308, 7997, 401, 124427, 549, 35442, 225, 109, 15055, 25748, 147, 7119, 43712, 34, 767, 135366, 18, 16, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [592, 63784, 119466, 17, 147808, 88214, 18, 656, 81, 32, 3296, 10280, 16, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
					# fmt: on

					self.tokenizer_integration_test_util(
					    expected_encoding=__lowerCAmelCase			,       model_name="""microsoft/xprophetnet-large-wiki100-cased"""			,       revision="""1acad1643ddd54a44df6a1b797ada8373685d90e"""			,       )












"""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


_lowerCAmelCase            =	logging.get_logger(__name__)

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

_lowerCAmelCase            =	{
    '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',
    },
}

_lowerCAmelCase            =	{
    'jukebox': 5_12,
}


class      UpperCamelCase		(__snake_case     ):
						_SCREAMING_SNAKE_CASE  : Optional[int]												=		VOCAB_FILES_NAMES
						_SCREAMING_SNAKE_CASE  : Tuple												=		PRETRAINED_VOCAB_FILES_MAP
						_SCREAMING_SNAKE_CASE  : int												=		PRETRAINED_LYRIC_TOKENS_SIZES
						_SCREAMING_SNAKE_CASE  : Optional[int]												=		["""input_ids""", """attention_mask"""]






						def __init__(		self  :Tuple			, __magic_name__  :Dict			, __magic_name__  :int			, __magic_name__  :str			, __magic_name__  :List[Any]=["v3", "v2", "v2"]			, __magic_name__  :List[Any]=512			, __magic_name__  :Optional[Any]=5			, __magic_name__  :Tuple="<|endoftext|>"			, **__magic_name__  :Tuple			, )      ->Union[str, Any]:
										lowercase    :      Any       = AddedToken(__magic_name__			, lstrip=__magic_name__			, rstrip=__magic_name__				) if isinstance(__magic_name__			, __magic_name__				) else unk_token
										super().__init__(
										    unk_token=__magic_name__			, n_genres=__magic_name__			, version=__magic_name__			, max_n_lyric_tokens=__magic_name__			, **__magic_name__			, )
										lowercase    :      Optional[int]       = version
										lowercase    :      Optional[int]       = max_n_lyric_tokens
										lowercase    :      Optional[int]       = n_genres

										with open(__magic_name__			, encoding="""utf-8"""				) as vocab_handle:
														lowercase    :      Optional[int]       = json.load(__magic_name__				)

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

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

										lowercase    :      str       = 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:
														lowercase    :      Dict       = oov.replace(r"""\-'"""			, r"""\-+'"""				)

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






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






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






						def      __snake_case      (		self  :str			, __magic_name__  :Optional[int]			, __magic_name__  :Dict			, __magic_name__  :Optional[Any]				)      ->List[str]:
										lowercase    :      Optional[int]       = [self.artists_encoder.get(__magic_name__			, 0				) for artist in list_artists]
										for genres in range(len(__magic_name__				)				):
														lowercase    :      int       = [self.genres_encoder.get(__magic_name__			, 0				) for genre in list_genres[genres]]
														lowercase    :      Optional[Any]       = list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]				))

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






						def      __snake_case      (		self  :Optional[int]			, __magic_name__  :Optional[Any]				)      ->List[str]:
										return list(__magic_name__				)






						def      __snake_case      (		self  :Tuple			, __magic_name__  :Tuple			, __magic_name__  :List[str]			, __magic_name__  :str			, **__magic_name__  :Union[str, Any]				)      ->Tuple:
										lowercase      ,      lowercase      ,      lowercase    :      List[str]       = self.prepare_for_tokenization(__magic_name__			, __magic_name__			, __magic_name__				)
										lowercase    :      List[str]       = self._tokenize(__magic_name__				)
										return artist, genre, lyrics






						def      __snake_case      (		self  :Optional[int]			, __magic_name__  :str			, __magic_name__  :str			, __magic_name__  :str			, __magic_name__  :bool = False				)      ->Tuple[str, str, str, Dict[str, Any]]:
										for idx in range(len(self.version				)				):
														if self.version[idx] == "v3":
																		lowercase    :      Tuple       = artists[idx].lower()
																		lowercase    :      Dict       = [genres[idx].lower()]
														else:
																		lowercase    :      str       = self._normalize(artists[idx]				) + """.v2"""
																		lowercase    :      str       = [
																		    self._normalize(__magic_name__				) + """.v2""" for genre in genres[idx].split("""_"""				)
																		]  # split is for the full dictionary with combined genres

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

										lowercase    :      str       = self._run_strip_accents(__magic_name__				)
										lowercase    :      str       = lyrics.replace("""\\"""			, """\n"""				)
										lowercase    :      int       = self.out_of_vocab.sub(""""""			, __magic_name__				), [], []
										return artists, genres, lyrics






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






						def      __snake_case      (		self  :Optional[int]			, __magic_name__  :str				)      ->str:
										lowercase    :      Tuple       = (
										    [chr(__magic_name__				) for i in range(ord("""a"""				)			, ord("""z"""				) + 1				)]
										    + [chr(__magic_name__				) for i in range(ord("""A"""				)			, ord("""Z"""				) + 1				)]
										    + [chr(__magic_name__				) for i in range(ord("""0"""				)			, ord("""9"""				) + 1				)]
										    + ["""."""]
										)
										lowercase    :      Dict       = frozenset(__magic_name__				)
										lowercase    :      Optional[int]       = re.compile(r"""_+"""				)
										lowercase    :      Optional[int]       = """""".join([c if c in accepted else """_""" for c in text.lower()]				)
										lowercase    :      Union[str, Any]       = pattern.sub("""_"""			, __magic_name__				).strip("""_"""				)
										return text






						def      __snake_case      (		self  :Optional[int]			, __magic_name__  :List[str]				)      ->str:
										return " ".join(__magic_name__				)






						def      __snake_case      (		self  :Tuple			, __magic_name__  :Optional[int]			, __magic_name__  :Optional[Union[str, TensorType]] = None			, __magic_name__  :bool = False				)      ->Tuple:
										# Convert to TensorType
										if not isinstance(__magic_name__			, __magic_name__				):
														lowercase    :      Optional[Any]       = TensorType(__magic_name__				)

										# 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

														lowercase    :      int       = tf.constant
														lowercase    :      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

														lowercase    :      List[Any]       = torch.tensor
														lowercase    :      List[str]       = 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

														lowercase    :      int       = jnp.array
														lowercase    :      Dict       = _is_jax
										else:
														lowercase    :      List[Any]       = np.asarray
														lowercase    :      Tuple       = _is_numpy

										# Do the tensor conversion in batch

										try:
														if prepend_batch_axis:
																		lowercase    :      Dict       = [inputs]

														if not is_tensor(__magic_name__				):
																		lowercase    :      str       = as_tensor(__magic_name__				)
										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  :Optional[int]			, __magic_name__  :Union[str, Any]			, __magic_name__  :str			, __magic_name__  :Optional[Any]=""			, __magic_name__  :Optional[int]="pt"				)      ->BatchEncoding:
										lowercase    :      Union[str, Any]       = [0, 0, 0]
										lowercase    :      Optional[int]       = [artist] * len(self.version				)
										lowercase    :      Dict       = [genres] * len(self.version				)

										lowercase      ,      lowercase      ,      lowercase    :      Dict       = self.tokenize(__magic_name__			, __magic_name__			, __magic_name__				)
										lowercase      ,      lowercase      ,      lowercase    :      Dict       = self._convert_token_to_id(__magic_name__			, __magic_name__			, __magic_name__				)

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






						def      __snake_case      (		self  :int			, __magic_name__  :str			, __magic_name__  :Optional[str] = None				)      ->Tuple[str]:
										if not os.path.isdir(__magic_name__				):
														logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
														return

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

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

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

										return (artists_file, genres_file, lyrics_file)






						def      __snake_case      (		self  :int			, __magic_name__  :int			, __magic_name__  :Dict			, __magic_name__  :Union[str, Any]				)      ->List[str]:
										lowercase    :      Union[str, Any]       = self.artists_decoder.get(__magic_name__				)
										lowercase    :      int       = [self.genres_decoder.get(__magic_name__				) for genre in genres_index]
										lowercase    :      Union[str, Any]       = [self.lyrics_decoder.get(__magic_name__				) for character in lyric_index]
										return artist, genres, lyrics
