'''simple docstring'''

import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
from ..utils.py_utils import no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
  from .features import FeatureType


__a       ,      __a       ,      __a:			List[str]	       =       False, False, False



@dataclass
class       UpperCAmelCase  :





       '''simple docstring'''



       SCREAMING_SNAKE_CASE 		=   None
       SCREAMING_SNAKE_CASE 		=   True
       SCREAMING_SNAKE_CASE 		=   True
       SCREAMING_SNAKE_CASE 		=   None
       # Automatically constructed
       SCREAMING_SNAKE_CASE 		=   "dict"
       SCREAMING_SNAKE_CASE 		=   pa.struct({"bytes": pa.binary(), "path": pa.string()} )
       SCREAMING_SNAKE_CASE 		=   field(default="Audio"   ,						init=__SCREAMING_SNAKE_CASE   ,						repr=__SCREAMING_SNAKE_CASE )

       def __call__(						self			)  ->  str:
              return self.pa_type

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  List[Any]:
              try:
                     import soundfile as sf  # soundfile is a dependency of librosa, needed to decode audio files.
              except ImportError as err:
                     raise ImportError('''To support encoding audio data, please install \'soundfile\'.'''			) from err
              if isinstance(_snake_case     ,       _snake_case			):
                     return {"bytes": None, "path": value}
              elif isinstance(_snake_case     ,       _snake_case			):
                     return {"bytes": value, "path": None}
              elif "array" in value:
                     # convert the audio array to wav bytes
                     lowercase__    :   Optional[Any]						= BytesIO()
                     sf.write(_snake_case     ,       value['''array''']     ,       value['''sampling_rate''']     ,       format='''wav'''			)
                     return {"bytes": buffer.getvalue(), "path": None}
              elif value.get('''path'''			) is not None and os.path.isfile(value['''path''']			):
                     # we set "bytes": None to not duplicate the data if they're already available locally
                     if value["path"].endswith('''pcm'''			):
                            # "PCM" only has raw audio bytes
                            if value.get('''sampling_rate'''			) is None:
                                   # At least, If you want to convert "PCM-byte" to "WAV-byte", you have to know sampling rate
                                   raise KeyError('''To use PCM files, please specify a \'sampling_rate\' in Audio object'''			)
                            if value.get('''bytes'''			):
                                   # If we already had PCM-byte, we don`t have to make "read file, make bytes" (just use it!)
                                   lowercase__    :   Union[str, Any]						= np.frombuffer(value['''bytes''']     ,       dtype=np.intaa			).astype(np.floataa			) / 32767
                            else:
                                   lowercase__    :   int						= np.memmap(value['''path''']     ,       dtype='''h'''     ,       mode='''r'''			).astype(np.floataa			) / 32767

                            lowercase__    :   Dict						= BytesIO(bytes()			)
                            sf.write(_snake_case     ,       _snake_case     ,       value['''sampling_rate''']     ,       format='''wav'''			)
                            return {"bytes": buffer.getvalue(), "path": None}
                     else:
                            return {"bytes": None, "path": value.get('''path'''			)}
              elif value.get('''bytes'''			) is not None or value.get('''path'''			) is not None:
                     # store the audio bytes, and path is used to infer the audio format using the file extension
                     return {"bytes": value.get('''bytes'''			), "path": value.get('''path'''			)}
              else:
                     raise ValueError(
                         F"""An audio sample should have one of \'path\' or \'bytes\' but they are missing or None in {value}."""			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase = None			)  ->  Union[str, Any]:
              if not self.decode:
                     raise RuntimeError('''Decoding is disabled for this feature. Please use Audio(decode=True) instead.'''			)

              lowercase__    :   str						= (value["path"], BytesIO(value['''bytes''']			)) if value["bytes"] is not None else (value["path"], None)
              if path is None and file is None:
                     raise ValueError(F"""An audio sample should have one of \'path\' or \'bytes\' but both are None in {value}."""			)

              try:
                     import librosa
                     import soundfile as sf
              except ImportError as err:
                     raise ImportError('''To support decoding audio files, please install \'librosa\' and \'soundfile\'.'''			) from err

              lowercase__    :   Union[str, Any]						= xsplitext(_snake_case			)[1][1:].lower() if path is not None else None
              if not config.IS_OPUS_SUPPORTED and audio_format == "opus":
                     raise RuntimeError(
                         '''Decoding \'opus\' files requires system library \'libsndfile\'>=1.0.31, '''
                         '''You can try to update `soundfile` python library: `pip install \"soundfile>=0.12.1\"`. '''			)
              elif not config.IS_MP3_SUPPORTED and audio_format == "mp3":
                     raise RuntimeError(
                         '''Decoding \'mp3\' files requires system library \'libsndfile\'>=1.1.0, '''
                         '''You can try to update `soundfile` python library: `pip install \"soundfile>=0.12.1\"`. '''			)

              if file is None:
                     lowercase__    :   Any						= token_per_repo_id or {}
                     lowercase__    :   int						= path.split('''::'''			)[-1]
                     try:
                            lowercase__    :   Any						= string_to_dict(_snake_case     ,       config.HUB_DATASETS_URL			)["repo_id"]
                            lowercase__    :   Optional[Any]						= token_per_repo_id[repo_id]
                     except (ValueError, KeyError):
                            lowercase__    :   List[Any]						= None

                     with xopen(_snake_case     ,       '''rb'''     ,       use_auth_token=_snake_case			) as f:
                            lowercase__    :   str						= sf.read(_snake_case			)

              else:
                     lowercase__    :   List[Any]						= sf.read(_snake_case			)

              lowercase__    :   Optional[Any]						= array.T
              if self.mono:
                     lowercase__    :   str						= librosa.to_mono(_snake_case			)
              if self.sampling_rate and self.sampling_rate != sampling_rate:
                     lowercase__    :   Tuple						= librosa.resample(_snake_case     ,       orig_sr=_snake_case     ,       target_sr=self.sampling_rate			)
                     lowercase__    :   Optional[int]						= self.sampling_rate

              return {"path": path, "array": array, "sampling_rate": sampling_rate}

       def _lowerCAmelCase(						self			)  ->  Tuple:
              from .features import Value

              if self.decode:
                     raise ValueError('''Cannot flatten a decoded Audio feature.'''			)
              return {
                  "bytes": Value('''binary'''			),
                  "path": Value('''string'''			),
              }

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  List[str]:
              if pa.types.is_string(storage.type			):
                     lowercase__    :   Union[str, Any]						= pa.array([None] * len(_snake_case			)     ,       type=pa.binary()			)
                     lowercase__    :   List[str]						= pa.StructArray.from_arrays([bytes_array, storage]     ,       ['''bytes''', '''path''']     ,       mask=storage.is_null()			)
              elif pa.types.is_binary(storage.type			):
                     lowercase__    :   Tuple						= pa.array([None] * len(_snake_case			)     ,       type=pa.string()			)
                     lowercase__    :   List[str]						= pa.StructArray.from_arrays([storage, path_array]     ,       ['''bytes''', '''path''']     ,       mask=storage.is_null()			)
              elif pa.types.is_struct(storage.type			) and storage.type.get_all_field_indices('''array'''			):
                     lowercase__    :   List[str]						= pa.array([Audio().encode_example(_snake_case			) if x is not None else None for x in storage.to_pylist()]			)
              elif pa.types.is_struct(storage.type			):
                     if storage.type.get_field_index('''bytes'''			) >= 0:
                            lowercase__    :   Optional[int]						= storage.field('''bytes'''			)
                     else:
                            lowercase__    :   Dict						= pa.array([None] * len(_snake_case			)     ,       type=pa.binary()			)
                     if storage.type.get_field_index('''path'''			) >= 0:
                            lowercase__    :   str						= storage.field('''path'''			)
                     else:
                            lowercase__    :   List[str]						= pa.array([None] * len(_snake_case			)     ,       type=pa.string()			)
                     lowercase__    :   List[Any]						= pa.StructArray.from_arrays([bytes_array, path_array]     ,       ['''bytes''', '''path''']     ,       mask=storage.is_null()			)
              return array_cast(_snake_case     ,       self.pa_type			)


       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  str:

              @no_op_if_value_is_null
              def path_to_bytes(__lowerCAmelCase			):
                     with xopen(_snake_case     ,       '''rb'''			) as f:
                            lowercase__    :   Union[str, Any]						= f.read()
                     return bytes_

              lowercase__    :   List[Any]						= pa.array(
                  [
                      (path_to_bytes(x['''path''']			) if x['''bytes'''] is None else x['''bytes''']) if x is not None else None
                      for x in storage.to_pylist()
                  ]     ,       type=pa.binary()     ,       )
              lowercase__    :   List[Any]						= pa.array(
                  [os.path.basename(_snake_case			) if path is not None else None for path in storage.field('''path'''			).to_pylist()]     ,       type=pa.string()     ,       )
              lowercase__    :   int						= pa.StructArray.from_arrays([bytes_array, path_array]     ,       ['''bytes''', '''path''']     ,       mask=bytes_array.is_null()			)
              return array_cast(_snake_case     ,       self.pa_type			)


'''simple docstring'''

import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
  from transformers.pipelines.conversational import Conversation


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

__a:			Tuple	       =       {"""tokenizer_file""": """tokenizer.json"""}

__a:			Union[str, Any]	       =       {
    """tokenizer_file""": {
        """bigscience/tokenizer""": """https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json""",
        """bigscience/bloom-560m""": """https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json""",
        """bigscience/bloom-1b1""": """https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json""",
        """bigscience/bloom-1b7""": """https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json""",
        """bigscience/bloom-3b""": """https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json""",
        """bigscience/bloom-7b1""": """https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json""",
        """bigscience/bloom""": """https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json""",
    },
}



class       UpperCAmelCase  (						a__ ):





       '''simple docstring'''



       SCREAMING_SNAKE_CASE 		=   VOCAB_FILES_NAMES
       SCREAMING_SNAKE_CASE 		=   PRETRAINED_VOCAB_FILES_MAP
       SCREAMING_SNAKE_CASE 		=   ["input_ids", "attention_mask"]
       SCREAMING_SNAKE_CASE 		=   None

       def __init__(						self     ,       __lowerCAmelCase=None     ,       __lowerCAmelCase=None     ,       __lowerCAmelCase=None     ,       __lowerCAmelCase="<unk>"     ,       __lowerCAmelCase="<s>"     ,       __lowerCAmelCase="</s>"     ,       __lowerCAmelCase="<pad>"     ,       __lowerCAmelCase=False     ,       __lowerCAmelCase=False     ,       **__lowerCAmelCase     ,       )  ->  Union[str, Any]:
        super().__init__(
            __lowerCAmelCase     ,       __lowerCAmelCase     ,       tokenizer_file=__lowerCAmelCase     ,       unk_token=__lowerCAmelCase     ,       bos_token=__lowerCAmelCase     ,       eos_token=__lowerCAmelCase     ,       pad_token=__lowerCAmelCase     ,       add_prefix_space=__lowerCAmelCase     ,       clean_up_tokenization_spaces=__lowerCAmelCase     ,       **__lowerCAmelCase     ,       )
        lowercase__    :   int						= json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()			)
        if pre_tok_state.get('''add_prefix_space'''     ,       __lowerCAmelCase			) != add_prefix_space:
         lowercase__    :   int						= getattr(__lowerCAmelCase     ,       pre_tok_state.pop('''type'''			)			)
         lowercase__    :   Tuple						= add_prefix_space
         lowercase__    :   List[str]						= pre_tok_class(**__lowerCAmelCase			)

        lowercase__    :   Union[str, Any]						= add_prefix_space

       def _lowerCAmelCase(						self     ,       *__lowerCAmelCase     ,       **__lowerCAmelCase			)  ->  BatchEncoding:
        lowercase__    :   Dict						= kwargs.get('''is_split_into_words'''     ,       __lowerCAmelCase			)
        if not (self.add_prefix_space or not is_split_into_words):
         raise Exception(
             F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
             ''' pretokenized inputs.'''			)

        return super()._batch_encode_plus(*__lowerCAmelCase     ,       **__lowerCAmelCase			)

       def _lowerCAmelCase(						self     ,       *__lowerCAmelCase     ,       **__lowerCAmelCase			)  ->  BatchEncoding:
        lowercase__    :   str						= kwargs.get('''is_split_into_words'''     ,       __lowerCAmelCase			)

        if not (self.add_prefix_space or not is_split_into_words):
         raise Exception(
             F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
             ''' pretokenized inputs.'''			)

        return super()._encode_plus(*__lowerCAmelCase     ,       **__lowerCAmelCase			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase = None			)  ->  Tuple[str]:
        lowercase__    :   List[Any]						= self._tokenizer.model.save(__lowerCAmelCase     ,       name=__lowerCAmelCase			)
        return tuple(__lowerCAmelCase			)


       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  List[int]:
        lowercase__    :   Dict						= []
        for is_user, text in conversation.iter_texts():
         input_ids.extend(self.encode(__lowerCAmelCase     ,       add_special_tokens=__lowerCAmelCase			) + [self.eos_token_id]			)

        if len(__lowerCAmelCase			) > self.model_max_length:
         lowercase__    :   Optional[Any]						= input_ids[-self.model_max_length :]
        return input_ids

