
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


lowercase						:      Tuple									= logging.get_logger(__name__)

lowercase						:      Optional[int]									= {
    'artists_file': 'artists.json',
    'lyrics_file': 'lyrics.json',
    'genres_file': 'genres.json',
}

lowercase						:      int									= {
    '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',
    },
}

lowercase						:      List[str]									= {
    'jukebox': 512,
}




class 				lowerCamelCase__							(       __lowercase):




	'''simple docstring'''




	_A			=  VOCAB_FILES_NAMES
	_A			=  PRETRAINED_VOCAB_FILES_MAP
	_A			=  PRETRAINED_LYRIC_TOKENS_SIZES
	_A			=  ['input_ids', 'attention_mask']







	def __init__(      self	:int  ,     a	:Union[str, Any]  ,     a	:Union[str, Any]  ,     a	:List[str]  ,     a	:Optional[Any]=["v3", "v2", "v2"]  ,     a	:Any=5_1_2  ,     a	:str=5  ,     a	:Tuple="<|endoftext|>"  ,     **a	:Optional[int]  ,     )	->				Any:
								__UpperCamelCase			:     Any         =      AddedToken(a  ,     lstrip=a  ,     rstrip=a		) if isinstance(a  ,     a		) else unk_token
								super().__init__(
								    unk_token=a  ,     n_genres=a  ,     version=a  ,     max_n_lyric_tokens=a  ,     **a  ,     )
								__UpperCamelCase			:     Optional[int]         =      version
								__UpperCamelCase			:     int         =      max_n_lyric_tokens
								__UpperCamelCase			:     Optional[int]         =      n_genres

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

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

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

								__UpperCamelCase			:     Tuple         =      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		) == 7_9:
															__UpperCamelCase			:     Optional[Any]         =      oov.replace(r"\-'"  ,     r"\-+'"		)

								__UpperCamelCase			:     Optional[int]         =      regex.compile(a		)
								__UpperCamelCase			:     Optional[int]         =      {v: k for k, v in self.artists_encoder.items()}
								__UpperCamelCase			:     Union[str, Any]         =      {v: k for k, v in self.genres_encoder.items()}
								__UpperCamelCase			:     Any         =      {v: k for k, v in self.lyrics_encoder.items()}







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







	def      _lowerCamelCase       (      self	:List[Any]		)	->				str:
								return dict(self.artists_encoder  ,     self.genres_encoder  ,     self.lyrics_encoder		)







	def      _lowerCamelCase       (      self	:Dict  ,     a	:List[str]  ,     a	:Union[str, Any]  ,     a	:Tuple		)	->				Tuple:
								__UpperCamelCase			:     Union[str, Any]         =      [self.artists_encoder.get(a  ,     0		) for artist in list_artists]
								for genres in range(len(a		)		):
															__UpperCamelCase			:     List[Any]         =      [self.genres_encoder.get(a  ,     0		) for genre in list_genres[genres]]
															__UpperCamelCase			:     Optional[Any]         =      list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]		))

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







	def      _lowerCamelCase       (      self	:Union[str, Any]  ,     a	:Union[str, Any]		)	->				Tuple:
								return list(a		)







	def      _lowerCamelCase       (      self	:Tuple  ,     a	:List[str]  ,     a	:Any  ,     a	:Dict  ,     **a	:List[str]		)	->				List[str]:
								__UpperCamelCase     ,		__UpperCamelCase     ,		__UpperCamelCase			:     List[str]         =      self.prepare_for_tokenization(a  ,     a  ,     a		)
								__UpperCamelCase			:     List[Any]         =      self._tokenize(a		)
								return artist, genre, lyrics







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

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

								__UpperCamelCase			:     List[Any]         =      self._run_strip_accents(a		)
								__UpperCamelCase			:     str         =      lyrics.replace("\\"  ,     "\n"		)
								__UpperCamelCase			:     Optional[int]         =      self.out_of_vocab.sub(""  ,     a		), [], []
								return artists, genres, lyrics







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







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







	def      _lowerCamelCase       (      self	:Dict  ,     a	:List[str]		)	->				str:
								return " ".join(a		)







	def      _lowerCamelCase       (      self	:Optional[int]  ,     a	:int  ,     a	:Optional[Union[str, TensorType]] = None  ,     a	:bool = False		)	->				Dict:
								# Convert to TensorType
								if not isinstance(a  ,     a		):
															__UpperCamelCase			:     Dict         =      TensorType(a		)

								# 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			:     int         =      tf.constant
															__UpperCamelCase			:     Optional[int]         =      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			:     Optional[int]         =      torch.tensor
															__UpperCamelCase			:     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

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

								# Do the tensor conversion in batch

								try:
															if prepend_batch_axis:
																						__UpperCamelCase			:     List[str]         =      [inputs]

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

								__UpperCamelCase     ,		__UpperCamelCase     ,		__UpperCamelCase			:     Optional[Any]         =      self.tokenize(a  ,     a  ,     a		)
								__UpperCamelCase     ,		__UpperCamelCase     ,		__UpperCamelCase			:     List[str]         =      self._convert_token_to_id(a  ,     a  ,     a		)

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







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

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

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

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

								return (artists_file, genres_file, lyrics_file)







	def      _lowerCamelCase       (      self	:Tuple  ,     a	:Dict  ,     a	:int  ,     a	:Optional[int]		)	->				Union[str, Any]:
								__UpperCamelCase			:     Tuple         =      self.artists_decoder.get(a		)
								__UpperCamelCase			:     Dict         =      [self.genres_decoder.get(a		) for genre in genres_index]
								__UpperCamelCase			:     str         =      [self.lyrics_decoder.get(a		) for character in lyric_index]
								return artist, genres, lyrics

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase						:      Optional[Any]									= {
    'configuration_blip_2': [
        'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Blip2Config',
        'Blip2QFormerConfig',
        'Blip2VisionConfig',
    ],
    'processing_blip_2': ['Blip2Processor'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase						:      Tuple									= [
		    'BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'Blip2Model',
		    'Blip2QFormerModel',
		    'Blip2PreTrainedModel',
		    'Blip2ForConditionalGeneration',
		    'Blip2VisionModel',
		]

if TYPE_CHECKING:
		from .configuration_blip_a import (
		    BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    BlipaConfig,
		    BlipaQFormerConfig,
		    BlipaVisionConfig,
		)
		from .processing_blip_a import BlipaProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_blip_a import (
				    BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BlipaForConditionalGeneration,
				    BlipaModel,
				    BlipaPreTrainedModel,
				    BlipaQFormerModel,
				    BlipaVisionModel,
				)

else:
		import sys

		lowercase						:      Dict									= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)