


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''': 512,
}


class   a__	(						lowerCAmelCase_    ):
       lowerCamelCase__:     Optional[Any]							    =     VOCAB_FILES_NAMES
       lowerCamelCase__:     List[str]							    =     PRETRAINED_VOCAB_FILES_MAP
       lowerCamelCase__:     List[Any]							    =     PRETRAINED_LYRIC_TOKENS_SIZES
       lowerCamelCase__:     List[str]							    =     ["""input_ids""", """attention_mask"""]

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

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

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

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

            a_    :     Dict										=    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:
                 a_    :     int										=    oov.replace(R"""\-'"""      ,							R"""\-+'"""    )

            a_    :     List[Any]										=    regex.compile(lowerCamelCase_    )
            a_    :     int										=    {v: k for k, v in self.artists_encoder.items()}
            a_    :     Tuple										=    {v: k for k, v in self.genres_encoder.items()}
            a_    :     int										=    {v: k for k, v in self.lyrics_encoder.items()}

       @property
       def 						UpperCAmelCase(   self      :     Dict    ):
            return len(self.artists_encoder    ) + len(self.genres_encoder    ) + len(self.lyrics_encoder    )

       def 						UpperCAmelCase(   self      :     int    ):
            return dict(self.artists_encoder      ,							self.genres_encoder      ,							self.lyrics_encoder    )

       def 						UpperCAmelCase(   self      :     Optional[int]      ,							lowerCamelCase_      :     Any      ,							lowerCamelCase_      :     int      ,							lowerCamelCase_      :     Tuple    ):
            a_    :     List[Any]										=    [self.artists_encoder.get(lowerCamelCase_      ,							0    ) for artist in list_artists]
            for genres in range(len(lowerCamelCase_    )    ):
                 a_    :     Any										=    [self.genres_encoder.get(lowerCamelCase_      ,							0    ) for genre in list_genres[genres]]
                 a_    :     int										=    list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]    ))

            a_    :     Dict										=    [[self.lyrics_encoder.get(lowerCamelCase_      ,							0    ) for character in list_lyrics[0]], [], []]
            return artists_id, list_genres, lyric_ids

       def 						UpperCAmelCase(   self      :     Union[str, Any]      ,							lowerCamelCase_      :     List[str]    ):
            return list(lowerCamelCase_    )

       def 						UpperCAmelCase(   self      :     Any      ,							lowerCamelCase_      :     str      ,							lowerCamelCase_      :     int      ,							lowerCamelCase_      :     int      ,							**lowerCamelCase_      :     Union[str, Any]    ):
            a_			,			a_			,			a_    :     str										=    self.prepare_for_tokenization(lowerCamelCase_      ,							lowerCamelCase_      ,							lowerCamelCase_    )
            a_    :     Tuple										=    self._tokenize(lowerCamelCase_    )
            return artist, genre, lyrics

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

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

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

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

       def 						UpperCAmelCase(   self      :     List[str]      ,							lowerCamelCase_      :     str    ):
            a_    :     List[str]										=    (
                [chr(lowerCamelCase_    ) for i in range(ord("""a"""    )      ,							ord("""z"""    ) + 1    )]
                + [chr(lowerCamelCase_    ) for i in range(ord("""A"""    )      ,							ord("""Z"""    ) + 1    )]
                + [chr(lowerCamelCase_    ) for i in range(ord("""0"""    )      ,							ord("""9"""    ) + 1    )]
                + ["""."""]
            )
            a_    :     Optional[Any]										=    frozenset(lowerCamelCase_    )
            a_    :     Optional[Any]										=    re.compile(R"""_+"""    )
            a_    :     List[Any]										=    """""".join([c if c in accepted else """_""" for c in text.lower()]    )
            a_    :     Union[str, Any]										=    pattern.sub("""_"""      ,							lowerCamelCase_    ).strip("""_"""    )
            return text

       def 						UpperCAmelCase(   self      :     str      ,							lowerCamelCase_      :     List[str]    ):
            return " ".join(lowerCamelCase_    )

       def 						UpperCAmelCase(   self      :     Any      ,							lowerCamelCase_      :     Union[str, Any]      ,							lowerCamelCase_      :     Optional[Union[str, TensorType]] = None      ,							lowerCamelCase_      :     bool = False    ):
            # Convert to TensorType
            if not isinstance(lowerCamelCase_      ,							lowerCamelCase_    ):
                 a_    :     Union[str, Any]										=    TensorType(lowerCamelCase_    )

            # 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_    :     Optional[int]										=    tf.constant
                 a_    :     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

                 a_    :     int										=    torch.tensor
                 a_    :     Dict										=    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_    :     str										=    jnp.array
                 a_    :     Optional[Any]										=    _is_jax
            else:
                 a_    :     str										=    np.asarray
                 a_    :     List[str]										=    _is_numpy

            # Do the tensor conversion in batch

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

                 if not is_tensor(lowerCamelCase_    ):
                      a_    :     str										=    as_tensor(lowerCamelCase_    )
            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      :     Any      ,							lowerCamelCase_      :     Tuple      ,							lowerCamelCase_      :     Optional[int]      ,							lowerCamelCase_      :     List[Any]=""      ,							lowerCamelCase_      :     int="pt"    ):
            a_    :     Any										=    [0, 0, 0]
            a_    :     int										=    [artist] * len(self.version    )
            a_    :     str										=    [genres] * len(self.version    )

            a_			,			a_			,			a_    :     Any										=    self.tokenize(lowerCamelCase_      ,							lowerCamelCase_      ,							lowerCamelCase_    )
            a_			,			a_			,			a_    :     Optional[int]										=    self._convert_token_to_id(lowerCamelCase_      ,							lowerCamelCase_      ,							lowerCamelCase_    )

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

       def 						UpperCAmelCase(   self      :     Optional[Any]      ,							lowerCamelCase_      :     str      ,							lowerCamelCase_      :     Optional[str] = None    ):
            if not os.path.isdir(lowerCamelCase_    ):
                 logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''    )
                 return

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

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

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

            return (artists_file, genres_file, lyrics_file)

       def 						UpperCAmelCase(   self      :     Dict      ,							lowerCamelCase_      :     Optional[int]      ,							lowerCamelCase_      :     int      ,							lowerCamelCase_      :     Tuple    ):
            a_    :     Optional[int]										=    self.artists_decoder.get(lowerCamelCase_    )
            a_    :     Tuple										=    [self.genres_decoder.get(lowerCamelCase_    ) for genre in genres_index]
            a_    :     Optional[Any]										=    [self.lyrics_decoder.get(lowerCamelCase_    ) for character in lyric_index]
            return artist, genres, lyrics







from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


__lowerCamelCase        =     logging.get_logger(__name__)

__lowerCamelCase        =     {
    '''facebook/convnextv2-tiny-1k-224''': '''https://huggingface.co/facebook/convnextv2-tiny-1k-224/resolve/main/config.json''',
}


class   a__	(						lowerCAmelCase_						,       lowerCAmelCase_    ):
       lowerCamelCase__:     str							    =     """convnextv2"""

       def __init__(   self      :     Tuple      ,							lowerCamelCase_      :     str=3      ,							lowerCamelCase_      :     Tuple=4      ,							lowerCamelCase_      :     Any=4      ,							lowerCamelCase_      :     Optional[int]=None      ,							lowerCamelCase_      :     Optional[int]=None      ,							lowerCamelCase_      :     Optional[int]="gelu"      ,							lowerCamelCase_      :     Optional[Any]=0.0_2      ,							lowerCamelCase_      :     str=1E-12      ,							lowerCamelCase_      :     Dict=0.0      ,							lowerCamelCase_      :     Union[str, Any]=2_2_4      ,							lowerCamelCase_      :     Dict=None      ,							lowerCamelCase_      :     Optional[Any]=None      ,							**lowerCamelCase_      :     List[Any]      ,							):
            super().__init__(**lowerCamelCase_    )

            a_    :     Dict										=    num_channels
            a_    :     Optional[int]										=    patch_size
            a_    :     int										=    num_stages
            a_    :     Any										=    [9_6, 1_9_2, 3_8_4, 7_6_8] if hidden_sizes is None else hidden_sizes
            a_    :     Any										=    [3, 3, 9, 3] if depths is None else depths
            a_    :     Any										=    hidden_act
            a_    :     Dict										=    initializer_range
            a_    :     Optional[Any]										=    layer_norm_eps
            a_    :     int										=    drop_path_rate
            a_    :     Optional[Any]										=    image_size
            a_    :     Dict										=    ["""stem"""] + [F'''stage{idx}''' for idx in range(1      ,							len(self.depths    ) + 1    )]
            a_			,			a_    :     int										=    get_aligned_output_features_output_indices(
                out_features=lowerCamelCase_      ,							out_indices=lowerCamelCase_      ,							stage_names=self.stage_names    )



