



"""simple docstring"""
import numpy as np  # noqa: E402

from ...configuration_utils import ConfigMixin, register_to_config
from ...schedulers.scheduling_utils import SchedulerMixin


try:
						import librosa  # noqa: E402

						__a     =    True
						__a     =    ""
except Exception as e:
						__a     =    False
						__a     =    (
						    F"""Cannot import librosa because {e}. Make sure to correctly install librosa to be able to install it."""
						)


from PIL import Image  # noqa: E402
class     lowerCamelCase  (      _lowerCAmelCase   ,						_lowerCAmelCase    ):






					'''simple docstring'''





					_A		:      Optional[Any]						=					"""mel_config.json"""






					@register_to_config
					def __init__(	self:							Tuple						,					snake_case:							int = 256						,					snake_case:							int = 256						,					snake_case:							int = 22_050						,					snake_case:							int = 2_048						,					snake_case:							int = 512						,					snake_case:							int = 80						,					snake_case:							int = 32						,					)       ->     Tuple:
											snake_case_			:Union[str, Any]						=      hop_length
											snake_case_			:List[str]						=      sample_rate
											snake_case_			:List[Any]						=      n_fft
											snake_case_			:List[Any]						=      top_db
											snake_case_			:Optional[int]						=      n_iter
											self.set_resolution(snake_case						,					snake_case						)
											snake_case_			:List[Any]						=      None

											if not _librosa_can_be_imported:
																	raise ValueError(_import_error						)






					def        lowerCAmelCase_    (	self:							List[str]						,					snake_case:							int						,					snake_case:							int						)       ->     Tuple:
											snake_case_			:Optional[Any]						=      x_res
											snake_case_			:Optional[int]						=      y_res
											snake_case_			:Tuple						=      self.y_res
											snake_case_			:Tuple						=      self.x_res * self.hop_length - 1






					def        lowerCAmelCase_    (	self:							List[Any]						,					snake_case:							str = None						,					snake_case:							np.ndarray = None						)       ->     Tuple:
											if audio_file is not None:
																	snake_case_,	snake_case_			:List[Any]						=      librosa.load(snake_case						,					mono=snake_case						,					sr=self.sr						)
											else:
																	snake_case_			:Optional[Any]						=      raw_audio

											# Pad with silence if necessary.
											if len(self.audio						) < self.x_res * self.hop_length:
																	snake_case_			:Dict						=      np.concatenate([self.audio, np.zeros((self.x_res * self.hop_length - len(self.audio						),)						)]						)






					def        lowerCAmelCase_    (	self:							int						)       ->     int:
											return len(self.audio						) // self.slice_size






					def        lowerCAmelCase_    (	self:							str						,					snake_case:							int = 0						)       ->     np.ndarray:
											return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]






					def        lowerCAmelCase_    (	self:							Any						)       ->     int:
											return self.sr






					def        lowerCAmelCase_    (	self:							int						,					snake_case:							int						)       ->     Image.Image:
											snake_case_			:Union[str, Any]						=      librosa.feature.melspectrogram(
											    y=self.get_audio_slice(snake_case						)						,					sr=self.sr						,					n_fft=self.n_fft						,					hop_length=self.hop_length						,					n_mels=self.n_mels						)
											snake_case_			:List[str]						=      librosa.power_to_db(snake_case						,					ref=np.max						,					top_db=self.top_db						)
											snake_case_			:Dict						=      (((log_S + self.top_db) * 255 / self.top_db).clip(0						,					255						) + 0.5).astype(np.uinta						)
											snake_case_			:Dict						=      Image.fromarray(snake_case						)
											return image






					def        lowerCAmelCase_    (	self:							Tuple						,					snake_case:							Image.Image						)       ->     np.ndarray:
											snake_case_			:Optional[Any]						=      np.frombuffer(image.tobytes()						,					dtype="""uint8"""						).reshape((image.height, image.width)						)
											snake_case_			:int						=      bytedata.astype("""float"""						) * self.top_db / 255 - self.top_db
											snake_case_			:Optional[Any]						=      librosa.db_to_power(snake_case						)
											snake_case_			:int						=      librosa.feature.inverse.mel_to_audio(
											    snake_case						,					sr=self.sr						,					n_fft=self.n_fft						,					hop_length=self.hop_length						,					n_iter=self.n_iter						)
											return audio





"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from unittest.mock import Mock, patch

import diffusers.utils.hub_utils
class     lowerCamelCase  (      unittest.TestCase    ):






					'''simple docstring'''





					@patch("""diffusers.utils.hub_utils.get_full_repo_name"""						)
					def        lowerCAmelCase_    (	self:							int						,					snake_case:							Mock						)       ->     None:
											snake_case_			:str						=      """full_repo_name"""
											with TemporaryDirectory() as tmpdir:
																	# Dummy args values
																	snake_case_			:int						=      Mock()
																	snake_case_			:Any						=      tmpdir
																	snake_case_			:int						=      0
																	snake_case_			:Optional[int]						=      """hub_token"""
																	snake_case_			:str						=      """dataset_name"""
																	snake_case_			:List[str]						=      0.0_1
																	snake_case_			:Dict						=      100_000
																	snake_case_			:Optional[Any]						=      10_000
																	snake_case_			:Optional[Any]						=      0.0_1
																	snake_case_			:Dict						=      0.0_2
																	snake_case_			:Dict						=      0.0_3
																	snake_case_			:Union[str, Any]						=      0.0_0_0_5
																	snake_case_			:Optional[Any]						=      0.0_0_0_0_0_1
																	snake_case_			:List[Any]						=      1
																	snake_case_			:Optional[Any]						=      10
																	snake_case_			:Dict						=      0.0_0_1
																	snake_case_			:Any						=      0.1
																	snake_case_			:List[Any]						=      0.2
																	snake_case_			:Any						=      True

																	# Model card mush be rendered and saved
																	diffusers.utils.hub_utils.create_model_card(snake_case						,					model_name="""model_name"""						)
																	self.assertTrue((Path(snake_case						) / """README.md""").is_file()						)
