


'''simple docstring'''





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												=						{
    '''microsoft/focalnet-tiny''': '''https://huggingface.co/microsoft/focalnet-tiny/resolve/main/config.json''',
}




class 				UpperCAmelCase			(			_snake_case						, _snake_case						):
 UpperCAmelCase				=					"focalnet"


 def __init__(      self							:	Optional[int]			,       __lowerCamelCase							:	Any=2_2_4			,       __lowerCamelCase							:	List[str]=4			,       __lowerCamelCase							:	Optional[int]=3			,       __lowerCamelCase							:	Optional[Any]=9_6			,       __lowerCamelCase							:	Optional[int]=False			,       __lowerCamelCase							:	int=[1_9_2, 3_8_4, 7_6_8, 7_6_8]			,       __lowerCamelCase							:	Union[str, Any]=[2, 2, 6, 2]			,       __lowerCamelCase							:	Any=[2, 2, 2, 2]			,       __lowerCamelCase							:	Optional[int]=[3, 3, 3, 3]			,       __lowerCamelCase							:	Dict="gelu"			,       __lowerCamelCase							:	Tuple=4.0			,       __lowerCamelCase							:	Optional[int]=0.0			,       __lowerCamelCase							:	Dict=0.1			,       __lowerCamelCase							:	Dict=False			,       __lowerCamelCase							:	int=1e-4			,       __lowerCamelCase							:	Optional[Any]=False			,       __lowerCamelCase							:	Any=False			,       __lowerCamelCase							:	Tuple=False			,       __lowerCamelCase							:	Optional[Any]=0.02			,       __lowerCamelCase							:	str=1e-5			,       __lowerCamelCase							:	Dict=3_2			,       __lowerCamelCase							:	Union[str, Any]=None			,       __lowerCamelCase							:	Dict=None			,       **__lowerCamelCase							:	Dict			,       ):
    super().__init__(**__lowerCamelCase )

    UpperCAmelCase__	:List[str]      =      image_size
    UpperCAmelCase__	:Tuple      =      patch_size
    UpperCAmelCase__	:Optional[int]      =      num_channels
    UpperCAmelCase__	:List[Any]      =      embed_dim
    UpperCAmelCase__	:Tuple      =      use_conv_embed
    UpperCAmelCase__	:List[Any]      =      hidden_sizes
    UpperCAmelCase__	:Tuple      =      depths
    UpperCAmelCase__	:Tuple      =      focal_levels
    UpperCAmelCase__	:Optional[int]      =      focal_windows
    UpperCAmelCase__	:List[str]      =      hidden_act
    UpperCAmelCase__	:str      =      mlp_ratio
    UpperCAmelCase__	:Dict      =      hidden_dropout_prob
    UpperCAmelCase__	:Any      =      drop_path_rate
    UpperCAmelCase__	:List[str]      =      use_layerscale
    UpperCAmelCase__	:List[str]      =      layerscale_value
    UpperCAmelCase__	:Optional[int]      =      use_post_layernorm
    UpperCAmelCase__	:Union[str, Any]      =      use_post_layernorm_in_modulation
    UpperCAmelCase__	:Optional[int]      =      normalize_modulator
    UpperCAmelCase__	:Any      =      initializer_range
    UpperCAmelCase__	:Tuple      =      layer_norm_eps
    UpperCAmelCase__	:Dict      =      encoder_stride
    UpperCAmelCase__	:Any      =      ['''stem'''] + [f'''stage{idx}''' for idx in range(1			,       len(self.depths ) + 1 )]
    UpperCAmelCase__   ,						UpperCAmelCase__	:int      =      get_aligned_output_features_output_indices(
        out_features=__lowerCamelCase			,       out_indices=__lowerCamelCase			,       stage_names=self.stage_names )







'''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												=						False, False, False




@dataclass
class 				UpperCAmelCase			:
 UpperCAmelCase				=					None
 UpperCAmelCase				=					True
 UpperCAmelCase				=					True
 UpperCAmelCase				=					None
 # Automatically constructed
 UpperCAmelCase				=					"dict"
 UpperCAmelCase				=					pa.struct({"bytes": pa.binary(), "path": pa.string()}						)
 UpperCAmelCase				=					field(default="Audio"						, init=_snake_case						, repr=_snake_case						)


 def __call__(      self							:	Any ):
    return self.pa_type


 def        __SCREAMING_SNAKE_CASE					(      self							:	Dict			,       __lowerCamelCase							:	Union[str, bytes, 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(__lowerCamelCase			,       __lowerCamelCase ):
       return {"bytes": None, "path": value}
    elif isinstance(__lowerCamelCase			,       __lowerCamelCase ):
       return {"bytes": value, "path": None}
    elif "array" in value:
       # convert the audio array to wav bytes
       UpperCAmelCase__	:int      =      BytesIO()
       sf.write(__lowerCamelCase			,       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__	:List[Any]      =      np.frombuffer(value['''bytes''']			,       dtype=np.intaa ).astype(np.floataa ) / 3_2_7_6_7
          else:
             UpperCAmelCase__	:Optional[Any]      =      np.memmap(value['''path''']			,       dtype='''h'''			,       mode='''r''' ).astype(np.floataa ) / 3_2_7_6_7

          UpperCAmelCase__	:Optional[Any]      =      BytesIO(bytes() )
          sf.write(__lowerCamelCase			,       __lowerCamelCase			,       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        __SCREAMING_SNAKE_CASE					(      self							:	List[Any]			,       __lowerCamelCase							:	dict			,       __lowerCamelCase							:	Optional[Dict[str, Union[str, bool, None]]] = None ):
    if not self.decode:
       raise RuntimeError('''Decoding is disabled for this feature. Please use Audio(decode=True) instead.''' )

    UpperCAmelCase__   ,						UpperCAmelCase__	: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

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

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

    else:
       UpperCAmelCase__   ,						UpperCAmelCase__	:List[Any]      =      sf.read(__lowerCamelCase )

    UpperCAmelCase__	:Optional[int]      =      array.T
    if self.mono:
       UpperCAmelCase__	:Any      =      librosa.to_mono(__lowerCamelCase )
    if self.sampling_rate and self.sampling_rate != sampling_rate:
       UpperCAmelCase__	:Union[str, Any]      =      librosa.resample(__lowerCamelCase			,       orig_sr=__lowerCamelCase			,       target_sr=self.sampling_rate )
       UpperCAmelCase__	:List[str]      =      self.sampling_rate

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


 def        __SCREAMING_SNAKE_CASE					(      self							:	Optional[Any] ):
    from .features import Value

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


 def        __SCREAMING_SNAKE_CASE					(      self							:	Any			,       __lowerCamelCase							:	Union[pa.StringArray, pa.StructArray] ):
    if pa.types.is_string(storage.type ):
       UpperCAmelCase__	:List[str]      =      pa.array([None] * len(__lowerCamelCase )			,       type=pa.binary() )
       UpperCAmelCase__	:Tuple      =      pa.StructArray.from_arrays([bytes_array, storage]			,       ['''bytes''', '''path''']			,       mask=storage.is_null() )
    elif pa.types.is_binary(storage.type ):
       UpperCAmelCase__	:str      =      pa.array([None] * len(__lowerCamelCase )			,       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(__lowerCamelCase ) 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__	:str      =      storage.field('''bytes''' )
       else:
          UpperCAmelCase__	:List[str]      =      pa.array([None] * len(__lowerCamelCase )			,       type=pa.binary() )
       if storage.type.get_field_index('''path''' ) >= 0:
          UpperCAmelCase__	:Optional[int]      =      storage.field('''path''' )
       else:
          UpperCAmelCase__	:Optional[int]      =      pa.array([None] * len(__lowerCamelCase )			,       type=pa.string() )
       UpperCAmelCase__	:List[str]      =      pa.StructArray.from_arrays([bytes_array, path_array]			,       ['''bytes''', '''path''']			,       mask=storage.is_null() )
    return array_cast(__lowerCamelCase			,       self.pa_type )





 def        __SCREAMING_SNAKE_CASE					(      self							:	Optional[Any]			,       __lowerCamelCase							:	pa.StructArray ):

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

    UpperCAmelCase__	:Union[str, 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()			,       )
    UpperCAmelCase__	:Optional[int]      =      pa.array(
        [os.path.basename(__lowerCamelCase ) if path is not None else None for path in storage.field('''path''' ).to_pylist()]			,       type=pa.string()			,       )
    UpperCAmelCase__	:Optional[int]      =      pa.StructArray.from_arrays([bytes_array, path_array]			,       ['''bytes''', '''path''']			,       mask=bytes_array.is_null() )
    return array_cast(__lowerCamelCase			,       self.pa_type )



