



"""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


_lowerCAmelCase,_lowerCAmelCase,_lowerCAmelCase    :List[Any]     =					False, False, False
@dataclass
class 							_UpperCAmelCase							:





     '''simple docstring'''



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





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





     def  __lowerCAmelCase	(					self       ,	A		)							->					dict:
         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(A       ,	A		):
             return {"bytes": None, "path": value}
         elif isinstance(A       ,	A		):
             return {"bytes": value, "path": None}
         elif "array" in value:
             # convert the audio array to wav bytes
             _UpperCAmelCase							:  Any											=    BytesIO()
             sf.write(A       ,	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!)
                     _UpperCAmelCase							:  Tuple											=    np.frombuffer(value['''bytes''']       ,	dtype=np.intaa		).astype(np.floataa		) / 3_2_7_6_7
                 else:
                     _UpperCAmelCase							:  Tuple											=    np.memmap(value['''path''']       ,	dtype='''h'''       ,	mode='''r'''		).astype(np.floataa		) / 3_2_7_6_7

                 _UpperCAmelCase							:  Union[str, Any]											=    BytesIO(bytes()		)
                 sf.write(A       ,	A       ,	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       ,	A       ,	A = None		)							->					dict:
         if not self.decode:
             raise RuntimeError('''Decoding is disabled for this feature. Please use Audio(decode=True) instead.'''		)

         _UpperCAmelCase							,				_UpperCAmelCase							:  Any											=    (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

         _UpperCAmelCase							:  Any											=    xsplitext(A		)[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:
             _UpperCAmelCase							:  List[str]											=    token_per_repo_id or {}
             _UpperCAmelCase							:  Tuple											=    path.split('''::'''		)[-1]
             try:
                 _UpperCAmelCase							:  List[Any]											=    string_to_dict(A       ,	config.HUB_DATASETS_URL		)['''repo_id''']
                 _UpperCAmelCase							:  int											=    token_per_repo_id[repo_id]
             except (ValueError, KeyError):
                 _UpperCAmelCase							:  int											=    None

             with xopen(A       ,	'''rb'''       ,	use_auth_token=A		) as f:
                 _UpperCAmelCase							,				_UpperCAmelCase							:  Union[str, Any]											=    sf.read(A		)

         else:
             _UpperCAmelCase							,				_UpperCAmelCase							:  Optional[int]											=    sf.read(A		)

         _UpperCAmelCase							:  List[str]											=    array.T
         if self.mono:
             _UpperCAmelCase							:  str											=    librosa.to_mono(A		)
         if self.sampling_rate and self.sampling_rate != sampling_rate:
             _UpperCAmelCase							:  int											=    librosa.resample(A       ,	orig_sr=A       ,	target_sr=self.sampling_rate		)
             _UpperCAmelCase							:  List[str]											=    self.sampling_rate

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





     def  __lowerCAmelCase	(					self		)							->					Union["FeatureType", Dict[str, "FeatureType"]]:
         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       ,	A		)							->					pa.StructArray:
         if pa.types.is_string(storage.type		):
             _UpperCAmelCase							:  List[str]											=    pa.array([None] * len(A		)       ,	type=pa.binary()		)
             _UpperCAmelCase							:  int											=    pa.StructArray.from_arrays([bytes_array, storage]       ,	['''bytes''', '''path''']       ,	mask=storage.is_null()		)
         elif pa.types.is_binary(storage.type		):
             _UpperCAmelCase							:  Optional[Any]											=    pa.array([None] * len(A		)       ,	type=pa.string()		)
             _UpperCAmelCase							:  int											=    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'''		):
             _UpperCAmelCase							:  Any											=    pa.array([Audio().encode_example(A		) 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:
                 _UpperCAmelCase							:  List[str]											=    storage.field('''bytes'''		)
             else:
                 _UpperCAmelCase							:  int											=    pa.array([None] * len(A		)       ,	type=pa.binary()		)
             if storage.type.get_field_index('''path'''		) >= 0:
                 _UpperCAmelCase							:  Optional[Any]											=    storage.field('''path'''		)
             else:
                 _UpperCAmelCase							:  Dict											=    pa.array([None] * len(A		)       ,	type=pa.string()		)
             _UpperCAmelCase							:  int											=    pa.StructArray.from_arrays([bytes_array, path_array]       ,	['''bytes''', '''path''']       ,	mask=storage.is_null()		)
         return array_cast(A       ,	self.pa_type		)





     def  __lowerCAmelCase	(					self       ,	A		)							->					pa.StructArray:

         @no_op_if_value_is_null
         def path_to_bytes(A		):
             with xopen(A       ,	'''rb'''		) as f:
                 _UpperCAmelCase							:  Any											=    f.read()
             return bytes_

         _UpperCAmelCase							:  Dict											=    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()       ,	)
         _UpperCAmelCase							:  Tuple											=    pa.array(
             [os.path.basename(A		) if path is not None else None for path in storage.field('''path'''		).to_pylist()]       ,	type=pa.string()       ,	)
         _UpperCAmelCase							:  Optional[Any]											=    pa.StructArray.from_arrays([bytes_array, path_array]       ,	['''bytes''', '''path''']       ,	mask=bytes_array.is_null()		)
         return array_cast(A       ,	self.pa_type		)







"""simple docstring"""
import re

from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P


# Sentinels
_lowerCAmelCase    :str     =					object()

# For specifying empty leaf dict `{}`
_lowerCAmelCase    :str     =					object()





def  lowerCamelCase_						(UpperCamelCase__		:		List[str]     ,       UpperCamelCase__		:		int							):
    _UpperCAmelCase							:  Dict											=    tuple((re.compile(x + '''$'''							) for x in qs)							)
    for i in range(len(UpperCamelCase__							) - len(UpperCamelCase__							) + 1							):
        _UpperCAmelCase							:  str											=    [x.match(UpperCamelCase__							) for x, y in zip(UpperCamelCase__     ,       ks[i:]							)]
        if matches and all(UpperCamelCase__							):
            return True
    return False





def  lowerCamelCase_						(UpperCamelCase__		:		List[str]							):
    def replace(UpperCamelCase__		:		List[str]     ,       UpperCamelCase__		:		Tuple							):
        for rule, replacement in rules:
            if _match(UpperCamelCase__     ,       UpperCamelCase__							):
                return replacement
        return val

    return replace





def  lowerCamelCase_						():
    return [
        # embeddings
        (("transformer", "wpe", "embedding"), P('''mp'''     ,       UpperCamelCase__							)),
        (("transformer", "wte", "embedding"), P('''mp'''     ,       UpperCamelCase__							)),
        # atention
        (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(UpperCamelCase__     ,       '''mp'''							)),
        (("attention", "out_proj", "kernel"), P('''mp'''     ,       UpperCamelCase__							)),
        (("attention", "out_proj", "bias"), None),
        # mlp
        (("mlp", "c_fc", "kernel"), P(UpperCamelCase__     ,       '''mp'''							)),
        (("mlp", "c_fc", "bias"), P('''mp'''							)),
        (("mlp", "c_proj", "kernel"), P('''mp'''     ,       UpperCamelCase__							)),
        (("mlp", "c_proj", "bias"), None),
        # layer norms
        ((r"ln_\d+", "bias"), None),
        ((r"\d+", r"ln_\d+", "scale"), None),
        (("ln_f", "bias"), None),
        (("ln_f", "scale"), None),
    ]





def  lowerCamelCase_						(UpperCamelCase__		:		str							):
    _UpperCAmelCase							:  List[str]											=    _get_partition_rules()
    _UpperCAmelCase							:  List[str]											=    _replacement_rules(UpperCamelCase__							)
    _UpperCAmelCase							:  List[Any]											=    {k: _unmatched for k in flatten_dict(UpperCamelCase__							)}
    _UpperCAmelCase							:  int											=    {k: replace(UpperCamelCase__     ,       UpperCamelCase__							) for k, v in initd.items()}
    assert _unmatched not in result.values(), "Incomplete partition spec."
    return freeze(unflatten_dict(UpperCamelCase__							)							)


