


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


_UpperCAmelCase		:       Optional[Any]						    =	False, False, False







@dataclass
class 			lowercase    :
				__SCREAMING_SNAKE_CASE :			Optional[int]	      =      None
				__SCREAMING_SNAKE_CASE :			bool	      =      True
				__SCREAMING_SNAKE_CASE :			bool	      =      True
				__SCREAMING_SNAKE_CASE :			Optional[str]	      =      None
				# Automatically constructed
				__SCREAMING_SNAKE_CASE :			ClassVar[str]	      =      "dict"
				__SCREAMING_SNAKE_CASE :			ClassVar[Any]	      =      pa.struct({'''bytes''': pa.binary(), '''path''': pa.string()}      )
				__SCREAMING_SNAKE_CASE :			str	      =      field(default='''Audio'''     ,  init=lowercase_     ,  repr=lowercase_      )




				def __call__( self	):
											return self.pa_type




				def    a							( self				,       snake_case	):
											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
																		snake_case_          =   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!)
																																snake_case_          =   np.frombuffer(value['bytes']				,       dtype=np.intaa	).astype(np.floataa	) / 3_2767
																									else:
																																snake_case_          =   np.memmap(value['path']				,       dtype='h'				,       mode='r'	).astype(np.floataa	) / 3_2767

																									snake_case_          =   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    a							( self				,       snake_case				,       snake_case = None	):
											if not self.decode:
																		raise RuntimeError('Decoding is disabled for this feature. Please use Audio(decode=True) instead.'	)

											snake_case_    ,   snake_case_          =   (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

											snake_case_          =   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:
																		snake_case_          =   token_per_repo_id or {}
																		snake_case_          =   path.split('::'	)[-1]
																		try:
																									snake_case_          =   string_to_dict(snake_case				,       config.HUB_DATASETS_URL	)['repo_id']
																									snake_case_          =   token_per_repo_id[repo_id]
																		except (ValueError, KeyError):
																									snake_case_          =   None

																		with xopen(snake_case				,       'rb'				,       use_auth_token=snake_case	) as f:
																									snake_case_    ,   snake_case_          =   sf.read(snake_case	)

											else:
																		snake_case_    ,   snake_case_          =   sf.read(snake_case	)

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

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




				def    a							( self	):
											from .features import Value

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




				def    a							( self				,       snake_case	):
											if pa.types.is_string(storage.type	):
																		snake_case_          =   pa.array([None] * len(snake_case	)				,       type=pa.binary()	)
																		snake_case_          =   pa.StructArray.from_arrays([bytes_array, storage]				,       ['bytes', 'path']				,       mask=storage.is_null()	)
											elif pa.types.is_binary(storage.type	):
																		snake_case_          =   pa.array([None] * len(snake_case	)				,       type=pa.string()	)
																		snake_case_          =   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'	):
																		snake_case_          =   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:
																									snake_case_          =   storage.field('bytes'	)
																		else:
																									snake_case_          =   pa.array([None] * len(snake_case	)				,       type=pa.binary()	)
																		if storage.type.get_field_index('path'	) >= 0:
																									snake_case_          =   storage.field('path'	)
																		else:
																									snake_case_          =   pa.array([None] * len(snake_case	)				,       type=pa.string()	)
																		snake_case_          =   pa.StructArray.from_arrays([bytes_array, path_array]				,       ['bytes', 'path']				,       mask=storage.is_null()	)
											return array_cast(snake_case				,       self.pa_type	)




				def    a							( self				,       snake_case	):

											@no_op_if_value_is_null
											def path_to_bytes(snake_case	):
																		with xopen(snake_case				,       'rb'	) as f:
																									snake_case_          =   f.read()
																		return bytes_

											snake_case_          =   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()				,       )
											snake_case_          =   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()				,       )
											snake_case_          =   pa.StructArray.from_arrays([bytes_array, path_array]				,       ['bytes', 'path']				,       mask=bytes_array.is_null()	)
											return array_cast(snake_case				,       self.pa_type	)







import os
import sys
import unittest


_UpperCAmelCase		:       str						    =	os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))

import get_test_info  # noqa: E402
from get_test_info import (  # noqa: E402
    get_model_to_test_mapping,
    get_model_to_tester_mapping,
    get_test_to_tester_mapping,
)


_UpperCAmelCase		:       List[Any]						    =	os.path.join("""tests""", """models""", """bert""", """test_modeling_bert.py""")
_UpperCAmelCase		:       Dict						    =	os.path.join("""tests""", """models""", """blip""", """test_modeling_blip.py""")







class 			lowercase    (	unittest.TestCase      ):




				def    a							( self	):
											snake_case_          =   get_test_to_tester_mapping(snake_case	)
											snake_case_          =   get_test_to_tester_mapping(snake_case	)

											snake_case_          =   {'BertModelTest': 'BertModelTester'}

											snake_case_          =   {
											    'BlipModelTest': 'BlipModelTester',
											    'BlipTextImageModelTest': 'BlipTextImageModelsModelTester',
											    'BlipTextModelTest': 'BlipTextModelTester',
											    'BlipTextRetrievalModelTest': 'BlipTextRetrievalModelTester',
											    'BlipVQAModelTest': 'BlipVQAModelTester',
											    'BlipVisionModelTest': 'BlipVisionModelTester',
											}

											self.assertEqual(get_test_info.to_json(snake_case	)				,       snake_case	)
											self.assertEqual(get_test_info.to_json(snake_case	)				,       snake_case	)




				def    a							( self	):
											snake_case_          =   get_model_to_test_mapping(snake_case	)
											snake_case_          =   get_model_to_test_mapping(snake_case	)

											snake_case_          =   {
											    'BertForMaskedLM': ['BertModelTest'],
											    'BertForMultipleChoice': ['BertModelTest'],
											    'BertForNextSentencePrediction': ['BertModelTest'],
											    'BertForPreTraining': ['BertModelTest'],
											    'BertForQuestionAnswering': ['BertModelTest'],
											    'BertForSequenceClassification': ['BertModelTest'],
											    'BertForTokenClassification': ['BertModelTest'],
											    'BertLMHeadModel': ['BertModelTest'],
											    'BertModel': ['BertModelTest'],
											}

											snake_case_          =   {
											    'BlipForConditionalGeneration': ['BlipTextImageModelTest'],
											    'BlipForImageTextRetrieval': ['BlipTextRetrievalModelTest'],
											    'BlipForQuestionAnswering': ['BlipVQAModelTest'],
											    'BlipModel': ['BlipModelTest'],
											    'BlipTextModel': ['BlipTextModelTest'],
											    'BlipVisionModel': ['BlipVisionModelTest'],
											}

											self.assertEqual(get_test_info.to_json(snake_case	)				,       snake_case	)
											self.assertEqual(get_test_info.to_json(snake_case	)				,       snake_case	)




				def    a							( self	):
											snake_case_          =   get_model_to_tester_mapping(snake_case	)
											snake_case_          =   get_model_to_tester_mapping(snake_case	)

											snake_case_          =   {
											    'BertForMaskedLM': ['BertModelTester'],
											    'BertForMultipleChoice': ['BertModelTester'],
											    'BertForNextSentencePrediction': ['BertModelTester'],
											    'BertForPreTraining': ['BertModelTester'],
											    'BertForQuestionAnswering': ['BertModelTester'],
											    'BertForSequenceClassification': ['BertModelTester'],
											    'BertForTokenClassification': ['BertModelTester'],
											    'BertLMHeadModel': ['BertModelTester'],
											    'BertModel': ['BertModelTester'],
											}

											snake_case_          =   {
											    'BlipForConditionalGeneration': ['BlipTextImageModelsModelTester'],
											    'BlipForImageTextRetrieval': ['BlipTextRetrievalModelTester'],
											    'BlipForQuestionAnswering': ['BlipVQAModelTester'],
											    'BlipModel': ['BlipModelTester'],
											    'BlipTextModel': ['BlipTextModelTester'],
											    'BlipVisionModel': ['BlipVisionModelTester'],
											}

											self.assertEqual(get_test_info.to_json(snake_case	)				,       snake_case	)
											self.assertEqual(get_test_info.to_json(snake_case	)				,       snake_case	)




