






"""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


lowercase__          = logging.get_logger(__name__)

lowercase__          = {
    """artists_file""": """artists.json""",
    """lyrics_file""": """lyrics.json""",
    """genres_file""": """genres.json""",
}

lowercase__          = {
    """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__          = {
    """jukebox""": 512,
}


class 		__lowerCamelCase				( A__			):





		'''simple docstring'''






		a_	:				Any            =							VOCAB_FILES_NAMES
		a_	:				Tuple            =							PRETRAINED_VOCAB_FILES_MAP
		a_	:				Union[str, Any]            =							PRETRAINED_LYRIC_TOKENS_SIZES
		a_	:				List[str]            =							["""input_ids""", """attention_mask"""]





		def __init__(   self							:	Union[str, Any]						,			a_							:	List[str]						,			a_							:	str						,			a_							:	Union[str, Any]						,			a_							:	Union[str, Any]=["v3", "v2", "v2"]						,			a_							:	Optional[Any]=5_12						,			a_							:	Union[str, Any]=5						,			a_							:	List[str]="<|endoftext|>"						,			**a_							:	Tuple						,			):
				lowerCAmelCase_   :							Optional[int]									=			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_						,			)
				lowerCAmelCase_   :							str									=			version
				lowerCAmelCase_   :							int									=			max_n_lyric_tokens
				lowerCAmelCase_   :							Optional[Any]									=			n_genres

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

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

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

				lowerCAmelCase_   :							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:
						lowerCAmelCase_   :							Union[str, Any]									=			oov.replace(R"\-'"						,			R"\-+'"	)

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





		@property
		def    lowerCamelCase       (   self							:	str	):
				return len(self.artists_encoder	) + len(self.genres_encoder	) + len(self.lyrics_encoder	)





		def    lowerCamelCase       (   self							:	Dict	):
				return dict(self.artists_encoder						,			self.genres_encoder						,			self.lyrics_encoder	)





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

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





		def    lowerCamelCase       (   self							:	List[Any]						,			a_							:	Dict	):
				return list(a_	)





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





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

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

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





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





		def    lowerCamelCase       (   self							:	Tuple						,			a_							:	str	):
				lowerCAmelCase_   :							int									=			(
				    [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	)]
				    + ["."]
				)
				lowerCAmelCase_   :							Optional[int]									=			frozenset(a_	)
				lowerCAmelCase_   :							int									=			re.compile(R"_+"	)
				lowerCAmelCase_   :							int									=			"".join([c if c in accepted else "_" for c in text.lower()]	)
				lowerCAmelCase_   :							Optional[Any]									=			pattern.sub("_"						,			a_	).strip("_"	)
				return text





		def    lowerCamelCase       (   self							:	List[str]						,			a_							:	List[str]	):
				return " ".join(a_	)





		def    lowerCamelCase       (   self							:	Optional[int]						,			a_							:	Dict						,			a_							:	Optional[Union[str, TensorType]] = None						,			a_							:	bool = False	):
				# Convert to TensorType
				if not isinstance(a_						,			a_	):
						lowerCAmelCase_   :							Optional[int]									=			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

						lowerCAmelCase_   :							Optional[int]									=			tf.constant
						lowerCAmelCase_   :							Dict									=			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

						lowerCAmelCase_   :							Any									=			torch.tensor
						lowerCAmelCase_   :							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

						lowerCAmelCase_   :							Optional[Any]									=			jnp.array
						lowerCAmelCase_   :							int									=			_is_jax
				else:
						lowerCAmelCase_   :							str									=			np.asarray
						lowerCAmelCase_   :							int									=			_is_numpy

				# Do the tensor conversion in batch

				try:
						if prepend_batch_axis:
								lowerCAmelCase_   :							Optional[Any]									=			[inputs]

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

				lowerCAmelCase_				,	lowerCAmelCase_				,	lowerCAmelCase_   :							Tuple									=			self.tokenize(a_						,			a_						,			a_	)
				lowerCAmelCase_				,	lowerCAmelCase_				,	lowerCAmelCase_   :							Optional[Any]									=			self._convert_token_to_id(a_						,			a_						,			a_	)

				lowerCAmelCase_   :							List[str]									=			[-INFINITY] * len(full_tokens[-1]	)
				lowerCAmelCase_   :							Tuple									=			[
				    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							:	Tuple						,			a_							:	str						,			a_							:	Optional[str] = None	):
				if not os.path.isdir(a_	):
						logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''	)
						return

				lowerCAmelCase_   :							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_	)	)

				lowerCAmelCase_   :							List[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_	)	)

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








"""simple docstring"""

# Copyright 2023 The HuggingFace 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.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__          = {
    """configuration_mgp_str""": ["""MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MgpstrConfig"""],
    """processing_mgp_str""": ["""MgpstrProcessor"""],
    """tokenization_mgp_str""": ["""MgpstrTokenizer"""],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase__          = [
					    """MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """MgpstrModel""",
					    """MgpstrPreTrainedModel""",
					    """MgpstrForSceneTextRecognition""",
					]

if TYPE_CHECKING:
					from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
					from .processing_mgp_str import MgpstrProcessor
					from .tokenization_mgp_str import MgpstrTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_mgp_str import (
										    MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MgpstrForSceneTextRecognition,
										    MgpstrModel,
										    MgpstrPreTrainedModel,
										)
else:
					import sys

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