






from collections import OrderedDict
from typing import Mapping

from packaging import version

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


a_							=    logging.get_logger(__name__)

a_							=    {
    '''microsoft/swin-tiny-patch4-window7-224''': (
        '''https://huggingface.co/microsoft/swin-tiny-patch4-window7-224/resolve/main/config.json'''
    ),
    # See all Swin models at https://huggingface.co/models?filter=swin
}


class      lowercase__     (			SCREAMING_SNAKE_CASE__,					SCREAMING_SNAKE_CASE__   ):
	a_         ="""swin"""

	a_         ={
	    """num_attention_heads""": """num_heads""",
	    """num_hidden_layers""": """num_layers""",
	}

	def __init__(							self		,    __UpperCAmelCase=224		,    __UpperCAmelCase=4		,    __UpperCAmelCase=3		,    __UpperCAmelCase=96		,    __UpperCAmelCase=[2, 2, 6, 2]		,    __UpperCAmelCase=[3, 6, 12, 24]		,    __UpperCAmelCase=7		,    __UpperCAmelCase=4.0		,    __UpperCAmelCase=True		,    __UpperCAmelCase=0.0		,    __UpperCAmelCase=0.0		,    __UpperCAmelCase=0.1		,    __UpperCAmelCase="gelu"		,    __UpperCAmelCase=False		,    __UpperCAmelCase=0.02		,    __UpperCAmelCase=1E-5		,    __UpperCAmelCase=32		,    __UpperCAmelCase=None		,    __UpperCAmelCase=None		,    **__UpperCAmelCase		,    )->					Union[str, Any]:







							'''simple docstring'''





							super().__init__(**_lowercase       )

							lowerCAmelCase__       =						image_size
							lowerCAmelCase__       =						patch_size
							lowerCAmelCase__       =						num_channels
							lowerCAmelCase__       =						embed_dim
							lowerCAmelCase__       =						depths
							lowerCAmelCase__       =						len(_lowercase       )
							lowerCAmelCase__       =						num_heads
							lowerCAmelCase__       =						window_size
							lowerCAmelCase__       =						mlp_ratio
							lowerCAmelCase__       =						qkv_bias
							lowerCAmelCase__       =						hidden_dropout_prob
							lowerCAmelCase__       =						attention_probs_dropout_prob
							lowerCAmelCase__       =						drop_path_rate
							lowerCAmelCase__       =						hidden_act
							lowerCAmelCase__       =						use_absolute_embeddings
							lowerCAmelCase__       =						layer_norm_eps
							lowerCAmelCase__       =						initializer_range
							lowerCAmelCase__       =						encoder_stride
							# we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
							# this indicates the channel dimension after the last stage of the model
							lowerCAmelCase__       =						int(embed_dim * 2 ** (len(_lowercase       ) - 1)       )
							lowerCAmelCase__       =						["""stem"""] + [F"stage{idx}" for idx in range(1		,    len(_lowercase       ) + 1       )]
							lowerCAmelCase__       =						get_aligned_output_features_output_indices(
							    out_features=_lowercase		,    out_indices=_lowercase		,    stage_names=self.stage_names       )





class      lowercase__     (			SCREAMING_SNAKE_CASE__   ):
	a_         =version.parse("""1.11"""   )

	@property
	def 		UpperCAmelCase  (							self       )->					Mapping[str, Mapping[int, str]]:







							'''simple docstring'''





							return OrderedDict(
							    [
							        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
							    ]       )


	@property
	def 		UpperCAmelCase  (							self       )->					float:







							'''simple docstring'''





							return 1E-4














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_							=    False, False, False


@dataclass
class      lowercase__     :
	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=_UpperCAmelCase,					repr=_UpperCAmelCase	)

	def __call__(							self       )->					Optional[int]:







							'''simple docstring'''





							return self.pa_type

	def 		UpperCAmelCase  (							self		,    __UpperCAmelCase       )->					dict:







							'''simple docstring'''





							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(__UpperCAmelCase		,    __UpperCAmelCase       ):
													return {"bytes": None, "path": value}
							elif isinstance(__UpperCAmelCase		,    __UpperCAmelCase       ):
													return {"bytes": value, "path": None}
							elif "array" in value:
													# convert the audio array to wav bytes
													lowerCAmelCase__       =						BytesIO()
													sf.write(__UpperCAmelCase		,    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!)
																									lowerCAmelCase__       =						np.frombuffer(value["bytes"]		,    dtype=np.intaa       ).astype(np.floataa       ) / 32767
																			else:
																									lowerCAmelCase__       =						np.memmap(value["path"]		,    dtype="h"		,    mode="r"       ).astype(np.floataa       ) / 32767

																			lowerCAmelCase__       =						BytesIO(bytes()       )
																			sf.write(__UpperCAmelCase		,    __UpperCAmelCase		,    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 		UpperCAmelCase  (							self		,    __UpperCAmelCase		,    __UpperCAmelCase = None       )->					dict:







							'''simple docstring'''





							if not self.decode:
													raise RuntimeError("Decoding is disabled for this feature. Please use Audio(decode=True) instead."       )

							lowerCAmelCase__      ,							lowerCAmelCase__       =						(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

							lowerCAmelCase__       =						xsplitext(__UpperCAmelCase       )[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:
													lowerCAmelCase__       =						token_per_repo_id or {}
													lowerCAmelCase__       =						path.split("::"       )[-1]
													try:
																			lowerCAmelCase__       =						string_to_dict(__UpperCAmelCase		,    config.HUB_DATASETS_URL       )["repo_id"]
																			lowerCAmelCase__       =						token_per_repo_id[repo_id]
													except (ValueError, KeyError):
																			lowerCAmelCase__       =						None

													with xopen(__UpperCAmelCase		,    "rb"		,    use_auth_token=__UpperCAmelCase       ) as f:
																			lowerCAmelCase__      ,							lowerCAmelCase__       =						sf.read(__UpperCAmelCase       )

							else:
													lowerCAmelCase__      ,							lowerCAmelCase__       =						sf.read(__UpperCAmelCase       )

							lowerCAmelCase__       =						array.T
							if self.mono:
													lowerCAmelCase__       =						librosa.to_mono(__UpperCAmelCase       )
							if self.sampling_rate and self.sampling_rate != sampling_rate:
													lowerCAmelCase__       =						librosa.resample(__UpperCAmelCase		,    orig_sr=__UpperCAmelCase		,    target_sr=self.sampling_rate       )
													lowerCAmelCase__       =						self.sampling_rate

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

	def 		UpperCAmelCase  (							self       )->					Union["FeatureType", Dict[str, "FeatureType"]]:







							'''simple docstring'''





							from .features import Value

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

	def 		UpperCAmelCase  (							self		,    __UpperCAmelCase       )->					pa.StructArray:







							'''simple docstring'''





							if pa.types.is_string(storage.type       ):
													lowerCAmelCase__       =						pa.array([None] * len(__UpperCAmelCase       )		,    type=pa.binary()       )
													lowerCAmelCase__       =						pa.StructArray.from_arrays([bytes_array, storage]		,    ["bytes", "path"]		,    mask=storage.is_null()       )
							elif pa.types.is_binary(storage.type       ):
													lowerCAmelCase__       =						pa.array([None] * len(__UpperCAmelCase       )		,    type=pa.string()       )
													lowerCAmelCase__       =						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"       ):
													lowerCAmelCase__       =						pa.array([Audio().encode_example(__UpperCAmelCase       ) 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:
																			lowerCAmelCase__       =						storage.field("bytes"       )
													else:
																			lowerCAmelCase__       =						pa.array([None] * len(__UpperCAmelCase       )		,    type=pa.binary()       )
													if storage.type.get_field_index("path"       ) >= 0:
																			lowerCAmelCase__       =						storage.field("path"       )
													else:
																			lowerCAmelCase__       =						pa.array([None] * len(__UpperCAmelCase       )		,    type=pa.string()       )
													lowerCAmelCase__       =						pa.StructArray.from_arrays([bytes_array, path_array]		,    ["bytes", "path"]		,    mask=storage.is_null()       )
							return array_cast(__UpperCAmelCase		,    self.pa_type       )


	def 		UpperCAmelCase  (							self		,    __UpperCAmelCase       )->					pa.StructArray:







							'''simple docstring'''





							@no_op_if_value_is_null
							def path_to_bytes(__UpperCAmelCase       ):
													with xopen(__UpperCAmelCase		,    "rb"       ) as f:
																			lowerCAmelCase__       =						f.read()
													return bytes_

							lowerCAmelCase__       =						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()		,    )
							lowerCAmelCase__       =						pa.array(
							    [os.path.basename(__UpperCAmelCase       ) if path is not None else None for path in storage.field("path"       ).to_pylist()]		,    type=pa.string()		,    )
							lowerCAmelCase__       =						pa.StructArray.from_arrays([bytes_array, path_array]		,    ["bytes", "path"]		,    mask=bytes_array.is_null()       )
							return array_cast(__UpperCAmelCase		,    self.pa_type       )






