






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

lowerCamelCase_				: List[str]			=							{
    '''artists_file''': '''artists.json''',
    '''lyrics_file''': '''lyrics.json''',
    '''genres_file''': '''genres.json''',
}

lowerCamelCase_				: Optional[Any]			=							{
    '''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_				: Any			=							{
    '''jukebox''': 512,
}
class    _SCREAMING_SNAKE_CASE							(		SCREAMING_SNAKE_CASE	):


			'''simple docstring'''





			__a							:							Tuple					     =					VOCAB_FILES_NAMES
			__a							:							Tuple					     =					PRETRAINED_VOCAB_FILES_MAP
			__a							:							Any					     =					PRETRAINED_LYRIC_TOKENS_SIZES
			__a							:							Optional[int]					     =					["input_ids", "attention_mask"]






			def __init__(   self							:						int ,      lowercase							:						Tuple ,      lowercase							:						Optional[Any] ,      lowercase							:						Union[str, Any] ,      lowercase							:						str=["v3", "v2", "v2"] ,      lowercase							:						List[str]=5_1_2 ,      lowercase							:						Union[str, Any]=5 ,      lowercase							:						List[Any]="<|endoftext|>" ,      **lowercase							:						Optional[int] ,      )							->    Union[str, Any]:

									'''simple docstring'''







									UpperCamelCase__         = AddedToken(lowercase ,      lstrip=lowercase ,      rstrip=lowercase			) if isinstance(lowercase ,      lowercase			) else unk_token
									super().__init__(
									    unk_token=lowercase ,      n_genres=lowercase ,      version=lowercase ,      max_n_lyric_tokens=lowercase ,      **lowercase ,      )
									UpperCamelCase__         = version
									UpperCamelCase__         = max_n_lyric_tokens
									UpperCamelCase__         = n_genres

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

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

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

									UpperCamelCase__         = 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__         = oov.replace(r"""\-'""" ,      r"""\-+'"""			)

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






			@property
			def 				A      (   self							:						Union[str, Any]			)							->    List[Any]:

									'''simple docstring'''







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






			def 				A      (   self							:						Union[str, Any]			)							->    Union[str, Any]:

									'''simple docstring'''







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






			def 				A      (   self							:						int ,      lowercase							:						Optional[int] ,      lowercase							:						Union[str, Any] ,      lowercase							:						List[str]			)							->    Any:

									'''simple docstring'''







									UpperCamelCase__         = [self.artists_encoder.get(lowercase ,      0			) for artist in list_artists]
									for genres in range(len(lowercase			)			):
															UpperCamelCase__         = [self.genres_encoder.get(lowercase ,      0			) for genre in list_genres[genres]]
															UpperCamelCase__         = list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]			))

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






			def 				A      (   self							:						Optional[int] ,      lowercase							:						Any			)							->    Optional[Any]:

									'''simple docstring'''







									return list(lowercase			)






			def 				A      (   self							:						str ,      lowercase							:						List[str] ,      lowercase							:						int ,      lowercase							:						str ,      **lowercase							:						Any			)							->    int:

									'''simple docstring'''







									UpperCamelCase__    ,   UpperCamelCase__    ,   UpperCamelCase__         = self.prepare_for_tokenization(lowercase ,      lowercase ,      lowercase			)
									UpperCamelCase__         = self._tokenize(lowercase			)
									return artist, genre, lyrics






			def 				A      (   self							:						Dict ,      lowercase							:						str ,      lowercase							:						str ,      lowercase							:						str ,      lowercase							:						bool = False			)							->    Tuple[str, str, str, Dict[str, Any]]:

									'''simple docstring'''







									for idx in range(len(self.version			)			):
															if self.version[idx] == "v3":
																					UpperCamelCase__         = artists[idx].lower()
																					UpperCamelCase__         = [genres[idx].lower()]
															else:
																					UpperCamelCase__         = self._normalize(artists[idx]			) + """.v2"""
																					UpperCamelCase__         = [
																					    self._normalize(lowercase			) + """.v2""" for genre in genres[idx].split("""_"""			)
																					]  # split is for the full dictionary with combined genres

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

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






			def 				A      (   self							:						Union[str, Any] ,      lowercase							:						List[str]			)							->    Union[str, Any]:

									'''simple docstring'''







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






			def 				A      (   self							:						Any ,      lowercase							:						str			)							->    str:

									'''simple docstring'''







									UpperCamelCase__         = (
									    [chr(lowercase			) for i in range(ord("""a"""			) ,      ord("""z"""			) + 1			)]
									    + [chr(lowercase			) for i in range(ord("""A"""			) ,      ord("""Z"""			) + 1			)]
									    + [chr(lowercase			) for i in range(ord("""0"""			) ,      ord("""9"""			) + 1			)]
									    + ["""."""]
									)
									UpperCamelCase__         = frozenset(lowercase			)
									UpperCamelCase__         = re.compile(r"""_+"""			)
									UpperCamelCase__         = """""".join([c if c in accepted else """_""" for c in text.lower()]			)
									UpperCamelCase__         = pattern.sub("""_""" ,      lowercase			).strip("""_"""			)
									return text






			def 				A      (   self							:						Union[str, Any] ,      lowercase							:						List[str]			)							->    str:

									'''simple docstring'''







									return " ".join(lowercase			)






			def 				A      (   self							:						Optional[int] ,      lowercase							:						Any ,      lowercase							:						Optional[Union[str, TensorType]] = None ,      lowercase							:						bool = False			)							->    Optional[int]:

									'''simple docstring'''







									if not isinstance(lowercase ,      lowercase			):
															UpperCamelCase__         = TensorType(lowercase			)

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

									# Do the tensor conversion in batch

									try:
															if prepend_batch_axis:
																					UpperCamelCase__         = [inputs]

															if not is_tensor(lowercase			):
																					UpperCamelCase__         = as_tensor(lowercase			)
									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] ,      lowercase							:						Optional[Any] ,      lowercase							:						int ,      lowercase							:						List[str]="" ,      lowercase							:						str="pt"			)							->    BatchEncoding:

									'''simple docstring'''







									UpperCamelCase__         = [0, 0, 0]
									UpperCamelCase__         = [artist] * len(self.version			)
									UpperCamelCase__         = [genres] * len(self.version			)

									UpperCamelCase__    ,   UpperCamelCase__    ,   UpperCamelCase__         = self.tokenize(lowercase ,      lowercase ,      lowercase			)
									UpperCamelCase__    ,   UpperCamelCase__    ,   UpperCamelCase__         = self._convert_token_to_id(lowercase ,      lowercase ,      lowercase			)

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






			def 				A      (   self							:						str ,      lowercase							:						str ,      lowercase							:						Optional[str] = None			)							->    Tuple[str]:

									'''simple docstring'''







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

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

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

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

									return (artists_file, genres_file, lyrics_file)







			def 				A      (   self							:						Tuple ,      lowercase							:						Tuple ,      lowercase							:						Tuple ,      lowercase							:						str			)							->    Any:

									'''simple docstring'''







									UpperCamelCase__         = self.artists_decoder.get(lowercase			)
									UpperCamelCase__         = [self.genres_decoder.get(lowercase			) for genre in genres_index]
									UpperCamelCase__         = [self.lyrics_decoder.get(lowercase			) for character in lyric_index]
									return artist, genres, lyrics








'''simple docstring'''


# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import torch

from ..models.speechta import SpeechTaForTextToSpeech, SpeechTaHifiGan, SpeechTaProcessor
from ..utils import is_datasets_available
from .base import PipelineTool


if is_datasets_available():
					from datasets import load_dataset
class    _SCREAMING_SNAKE_CASE							(		SCREAMING_SNAKE_CASE	):


			'''simple docstring'''





			__a							:							int					     =					"microsoft/speecht5_tts"
			__a							:							int					     =					(
			    "This is a tool that reads an English text out loud. It takes an input named `text` which should contain the "
			    "text to read (in English) and returns a waveform object containing the sound."
			)
			__a							:							Optional[Any]					     =					"text_reader"
			__a							:							Tuple					     =					SpeechTaProcessor
			__a							:							int					     =					SpeechTaForTextToSpeech
			__a							:							int					     =					SpeechTaHifiGan

			__a							:							Optional[int]					     =					["text"]
			__a							:							Union[str, Any]					     =					["audio"]






			def 				A      (   self							:						str			)							->    Optional[int]:

									'''simple docstring'''







									if self.post_processor is None:
															UpperCamelCase__         = """microsoft/speecht5_hifigan"""
									super().setup()






			def 				A      (   self							:						List[Any] ,      lowercase							:						Any ,      lowercase							:						Union[str, Any]=None			)							->    Tuple:

									'''simple docstring'''







									UpperCamelCase__         = self.pre_processor(text=lowercase ,      return_tensors="""pt""" ,      truncation=lowercase			)

									if speaker_embeddings is None:
															if not is_datasets_available():
																					raise ImportError("""Datasets needs to be installed if not passing speaker embeddings."""			)

															UpperCamelCase__         = load_dataset("""Matthijs/cmu-arctic-xvectors""" ,      split="""validation"""			)
															UpperCamelCase__         = torch.tensor(embeddings_dataset[7_3_0_5]["""xvector"""]			).unsqueeze(0			)

									return {"input_ids": inputs["input_ids"], "speaker_embeddings": speaker_embeddings}






			def 				A      (   self							:						Union[str, Any] ,      lowercase							:						Optional[int]			)							->    int:

									'''simple docstring'''







									with torch.no_grad():
															return self.model.generate_speech(**lowercase			)







			def 				A      (   self							:						str ,      lowercase							:						Union[str, Any]			)							->    Tuple:

									'''simple docstring'''







									with torch.no_grad():
															return self.post_processor(lowercase			).cpu().detach()
