"""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__(	__A       ):
						lowerCAmelCase__     :  List[str]  							=						VOCAB_FILES_NAMES
						lowerCAmelCase__     :  str  							=						PRETRAINED_VOCAB_FILES_MAP
						lowerCAmelCase__     :  List[Any]  							=						PRETRAINED_LYRIC_TOKENS_SIZES
						lowerCAmelCase__     :  int  							=						['input_ids', 'attention_mask']





						def __init__(				self						,__UpperCAmelCase						,__UpperCAmelCase						,__UpperCAmelCase						,__UpperCAmelCase=["v3", "v2", "v2"]						,__UpperCAmelCase=5_12						,__UpperCAmelCase=5						,__UpperCAmelCase="<|endoftext|>"						,**__UpperCAmelCase						,)    -> List[Any]:
													A__		   =							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						,)
													A__		   =							version
													A__		   =							max_n_lyric_tokens
													A__		   =							n_genres

													with open(__UpperCAmelCase						,encoding='utf-8'   ) as vocab_handle:
																				A__		   =							json.load(__UpperCAmelCase   )

													with open(__UpperCAmelCase						,encoding='utf-8'   ) as vocab_handle:
																				A__		   =							json.load(__UpperCAmelCase   )

													with open(__UpperCAmelCase						,encoding='utf-8'   ) as vocab_handle:
																				A__		   =							json.load(__UpperCAmelCase   )

													A__		   =							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__		   =							oov.replace(R'\-\''						,R'\-+\''   )

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





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





						def  snake_case__		(				self   )    -> Tuple:
													return dict(self.artists_encoder						,self.genres_encoder						,self.lyrics_encoder   )





						def  snake_case__		(				self						,__UpperCAmelCase						,__UpperCAmelCase						,__UpperCAmelCase   )    -> Optional[int]:
													A__		   =							[self.artists_encoder.get(__UpperCAmelCase						,0   ) for artist in list_artists]
													for genres in range(len(__UpperCAmelCase   )   ):
																				A__		   =							[self.genres_encoder.get(__UpperCAmelCase						,0   ) for genre in list_genres[genres]]
																				A__		   =							list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]   ))

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





						def  snake_case__		(				self						,__UpperCAmelCase   )    -> List[str]:
													return list(__UpperCAmelCase   )





						def  snake_case__		(				self						,__UpperCAmelCase						,__UpperCAmelCase						,__UpperCAmelCase						,**__UpperCAmelCase   )    -> Optional[int]:
													A__   ,     A__   ,     A__		   =							self.prepare_for_tokenization(__UpperCAmelCase						,__UpperCAmelCase						,__UpperCAmelCase   )
													A__		   =							self._tokenize(__UpperCAmelCase   )
													return artist, genre, lyrics





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

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

													A__		   =							self._run_strip_accents(__UpperCAmelCase   )
													A__		   =							lyrics.replace('\\'						,'\n'   )
													A__		   =							self.out_of_vocab.sub(''						,__UpperCAmelCase   ), [], []
													return artists, genres, lyrics





						def  snake_case__		(				self						,__UpperCAmelCase   )    -> str:
													A__		   =							unicodedata.normalize('NFD'						,__UpperCAmelCase   )
													A__		   =							[]
													for char in text:
																				A__		   =							unicodedata.category(__UpperCAmelCase   )
																				if cat == "Mn":
																											continue
																				output.append(__UpperCAmelCase   )
													return "".join(__UpperCAmelCase   )





						def  snake_case__		(				self						,__UpperCAmelCase   )    -> str:
													A__		   =							(
													    [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   )]
													    + ['.']
													)
													A__		   =							frozenset(__UpperCAmelCase   )
													A__		   =							re.compile(R'_+'   )
													A__		   =							''.join([c if c in accepted else '_' for c in text.lower()]   )
													A__		   =							pattern.sub('_'						,__UpperCAmelCase   ).strip('_'   )
													return text





						def  snake_case__		(				self						,__UpperCAmelCase   )    -> str:
													return " ".join(__UpperCAmelCase   )





						def  snake_case__		(				self						,__UpperCAmelCase						,__UpperCAmelCase = None						,__UpperCAmelCase = False   )    -> Tuple:
													# Convert to TensorType
													if not isinstance(__UpperCAmelCase						,__UpperCAmelCase   ):
																				A__		   =							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

																				A__		   =							tf.constant
																				A__		   =							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__		   =							torch.tensor
																				A__		   =							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__		   =							jnp.array
																				A__		   =							_is_jax
													else:
																				A__		   =							np.asarray
																				A__		   =							_is_numpy

													# Do the tensor conversion in batch

													try:
																				if prepend_batch_axis:
																											A__		   =							[inputs]

																				if not is_tensor(__UpperCAmelCase   ):
																											A__		   =							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						,__UpperCAmelCase						,__UpperCAmelCase						,__UpperCAmelCase=""						,__UpperCAmelCase="pt"   )    -> BatchEncoding:
													A__		   =							[0, 0, 0]
													A__		   =							[artist] * len(self.version   )
													A__		   =							[genres] * len(self.version   )

													A__   ,     A__   ,     A__		   =							self.tokenize(__UpperCAmelCase						,__UpperCAmelCase						,__UpperCAmelCase   )
													A__   ,     A__   ,     A__		   =							self._convert_token_to_id(__UpperCAmelCase						,__UpperCAmelCase						,__UpperCAmelCase   )

													A__		   =							[-INFINITY] * len(full_tokens[-1]   )
													A__		   =							[
													    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  snake_case__		(				self						,__UpperCAmelCase						,__UpperCAmelCase = None   )    -> Tuple[str]:
													if not os.path.isdir(__UpperCAmelCase   ):
																				logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''   )
																				return

													A__		   =							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   )   )

													A__		   =							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   )   )

													A__		   =							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  snake_case__		(				self						,__UpperCAmelCase						,__UpperCAmelCase						,__UpperCAmelCase   )    -> Optional[int]:
													A__		   =							self.artists_decoder.get(__UpperCAmelCase   )
													A__		   =							[self.genres_decoder.get(__UpperCAmelCase   ) for genre in genres_index]
													A__		   =							[self.lyrics_decoder.get(__UpperCAmelCase   ) for character in lyric_index]
													return artist, genres, lyrics






"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCamelCase							 =     {
    "configuration_chinese_clip": [
        "CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "ChineseCLIPConfig",
        "ChineseCLIPOnnxConfig",
        "ChineseCLIPTextConfig",
        "ChineseCLIPVisionConfig",
    ],
    "processing_chinese_clip": ["ChineseCLIPProcessor"],
}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCamelCase							 =     ["ChineseCLIPFeatureExtractor"]
				__lowerCamelCase							 =     ["ChineseCLIPImageProcessor"]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCamelCase							 =     [
				    "CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "ChineseCLIPModel",
				    "ChineseCLIPPreTrainedModel",
				    "ChineseCLIPTextModel",
				    "ChineseCLIPVisionModel",
				]

if TYPE_CHECKING:
				from .configuration_chinese_clip import (
				    CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    ChineseCLIPConfig,
				    ChineseCLIPOnnxConfig,
				    ChineseCLIPTextConfig,
				    ChineseCLIPVisionConfig,
				)
				from .processing_chinese_clip import ChineseCLIPProcessor

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_chinese_clip import (
								    CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
								    ChineseCLIPModel,
								    ChineseCLIPPreTrainedModel,
								    ChineseCLIPTextModel,
								    ChineseCLIPVisionModel,
								)

else:
				import sys

				__lowerCamelCase							 =     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





