"""simple docstring"""







from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase_    :    Any											=						logging.get_logger(__name__)

UpperCamelCase_    :    List[Any]											=						{
    """openbmb/cpm-ant-10b""": """https://huggingface.co/openbmb/cpm-ant-10b/blob/main/config.json"""
    # See all CPMAnt models at https://huggingface.co/models?filter=cpmant
}


class      _lowercase						(				__lowerCamelCase					):
				lowerCamelCase__									=    'cpmant'

				def __init__(       self    :      List[Any]    ,      _lowercase    :      int = 3_0_7_2_0    ,      _lowercase    :      int = 4_0_9_6    ,      _lowercase    :      int = 3_2    ,      _lowercase    :      int = 1_2_8    ,      _lowercase    :      int = 1_0_2_4_0    ,      _lowercase    :      int = 4_8    ,      _lowercase    :      int = 0.0    ,      _lowercase    :      int = 5_1_2    ,      _lowercase    :      int = 2_0_4_8    ,      _lowercase    :      int = 1e-6    ,      _lowercase    :      float = 1.0    ,      _lowercase    :      int = 3_2    ,      _lowercase    :      int = 3_2    ,      _lowercase    :      int = 3_2    ,      _lowercase    :      bool = True    ,      **_lowercase    :      List[Any]    ,      ):


										'''simple docstring'''
										super().__init__(**_lowercase       )
										UpperCAmelCase__   		=						prompt_types
										UpperCAmelCase__   		=						prompt_length
										UpperCAmelCase__   		=						segment_types
										UpperCAmelCase__   		=						hidden_size
										UpperCAmelCase__   		=						num_attention_heads
										UpperCAmelCase__   		=						dim_head
										UpperCAmelCase__   		=						dim_ff
										UpperCAmelCase__   		=						num_hidden_layers
										UpperCAmelCase__   		=						position_bias_num_buckets
										UpperCAmelCase__   		=						position_bias_max_distance
										UpperCAmelCase__   		=						dropout_p
										UpperCAmelCase__   		=						eps
										UpperCAmelCase__   		=						use_cache
										UpperCAmelCase__   		=						vocab_size
										UpperCAmelCase__   		=						init_std


"""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

						UpperCamelCase_    :    Union[str, Any]											=						True
						UpperCamelCase_    :    int											=						""""""
except Exception as e:
						UpperCamelCase_    :    Any											=						False
						UpperCamelCase_    :    Any											=						(
						    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      _lowercase						(				__lowerCamelCase , __lowerCamelCase					):
				lowerCamelCase__									=    'mel_config.json'

				@register_to_config
				def __init__(       self    :      int    ,      _lowercase    :      int = 2_5_6    ,      _lowercase    :      int = 2_5_6    ,      _lowercase    :      int = 2_2_0_5_0    ,      _lowercase    :      int = 2_0_4_8    ,      _lowercase    :      int = 5_1_2    ,      _lowercase    :      int = 8_0    ,      _lowercase    :      int = 3_2    ,      ):


										'''simple docstring'''
										UpperCAmelCase__   		=						hop_length
										UpperCAmelCase__   		=						sample_rate
										UpperCAmelCase__   		=						n_fft
										UpperCAmelCase__   		=						top_db
										UpperCAmelCase__   		=						n_iter
										self.set_resolution(_lowercase    ,      _lowercase       )
										UpperCAmelCase__   		=						None

										if not _librosa_can_be_imported:
																raise ValueError(_import_error       )

				def     A	(       self    :      Any    ,      _lowercase    :      int    ,      _lowercase    :      int       ):


										'''simple docstring'''
										UpperCAmelCase__   		=						x_res
										UpperCAmelCase__   		=						y_res
										UpperCAmelCase__   		=						self.y_res
										UpperCAmelCase__   		=						self.x_res * self.hop_length - 1

				def     A	(       self    :      Dict    ,      _lowercase    :      str = None    ,      _lowercase    :      np.ndarray = None       ):


										'''simple docstring'''
										if audio_file is not None:
																UpperCAmelCase__		, UpperCAmelCase__   		=						librosa.load(_lowercase    ,      mono=_lowercase    ,      sr=self.sr       )
										else:
																UpperCAmelCase__   		=						raw_audio

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

				def     A	(       self    :      int       ):


										'''simple docstring'''
										return len(self.audio       ) // self.slice_size

				def     A	(       self    :      Optional[int]    ,      _lowercase    :      int = 0       ):


										'''simple docstring'''
										return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]

				def     A	(       self    :      Dict       ):


										'''simple docstring'''
										return self.sr

				def     A	(       self    :      int    ,      _lowercase    :      int       ):


										'''simple docstring'''
										UpperCAmelCase__   		=						librosa.feature.melspectrogram(
										    y=self.get_audio_slice(_lowercase       )    ,      sr=self.sr    ,      n_fft=self.n_fft    ,      hop_length=self.hop_length    ,      n_mels=self.n_mels       )
										UpperCAmelCase__   		=						librosa.power_to_db(_lowercase    ,      ref=np.max    ,      top_db=self.top_db       )
										UpperCAmelCase__   		=						(((log_S + self.top_db) * 2_5_5 / self.top_db).clip(0    ,      2_5_5       ) + 0.5).astype(np.uinta       )
										UpperCAmelCase__   		=						Image.fromarray(_lowercase       )
										return image

				def     A	(       self    :      Dict    ,      _lowercase    :      Image.Image       ):


										'''simple docstring'''
										UpperCAmelCase__   		=						np.frombuffer(image.tobytes()    ,      dtype="""uint8"""       ).reshape((image.height, image.width)       )
										UpperCAmelCase__   		=						bytedata.astype("""float"""       ) * self.top_db / 2_5_5 - self.top_db
										UpperCAmelCase__   		=						librosa.db_to_power(_lowercase       )
										UpperCAmelCase__   		=						librosa.feature.inverse.mel_to_audio(
										    _lowercase    ,      sr=self.sr    ,      n_fft=self.n_fft    ,      hop_length=self.hop_length    ,      n_iter=self.n_iter       )
										return audio

