
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 		lowercase_							(							__SCREAMING_SNAKE_CASE				,						__SCREAMING_SNAKE_CASE					):
 A__    :					Optional[Any]    =     """mel_config.json"""

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




        """simple docstring"""


        UpperCamelCase_											=							hop_length
        UpperCamelCase_											=							sample_rate
        UpperCamelCase_											=							n_fft
        UpperCamelCase_											=							top_db
        UpperCamelCase_											=							n_iter
        self.set_resolution(__UpperCamelCase  ,						__UpperCamelCase  )
        UpperCamelCase_											=							None

        if not _librosa_can_be_imported:
               raise ValueError(_import_error  )

 def lowerCamelCase_					(   self  ,						__UpperCamelCase  ,						__UpperCamelCase  ):




        """simple docstring"""


        UpperCamelCase_											=							x_res
        UpperCamelCase_											=							y_res
        UpperCamelCase_											=							self.y_res
        UpperCamelCase_											=							self.x_res * self.hop_length - 1

 def lowerCamelCase_					(   self  ,						__UpperCamelCase = None  ,						__UpperCamelCase = None  ):




        """simple docstring"""


        if audio_file is not None:
               UpperCamelCase_							,					UpperCamelCase_											=							librosa.load(__UpperCamelCase  ,						mono=__UpperCamelCase  ,						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 lowerCamelCase_					(   self  ):




        """simple docstring"""


        return len(self.audio  ) // self.slice_size

 def lowerCamelCase_					(   self  ,						__UpperCamelCase = 0  ):




        """simple docstring"""


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

 def lowerCamelCase_					(   self  ):




        """simple docstring"""


        return self.sr

 def lowerCamelCase_					(   self  ,						__UpperCamelCase  ):




        """simple docstring"""


        UpperCamelCase_											=							librosa.feature.melspectrogram(
            y=self.get_audio_slice(__UpperCamelCase  )  ,						sr=self.sr  ,						n_fft=self.n_fft  ,						hop_length=self.hop_length  ,						n_mels=self.n_mels  )
        UpperCamelCase_											=							librosa.power_to_db(__UpperCamelCase  ,						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(__UpperCamelCase  )
        return image

 def lowerCamelCase_					(   self  ,						__UpperCamelCase  ):




        """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(__UpperCamelCase  )
        UpperCamelCase_											=							librosa.feature.inverse.mel_to_audio(
            __UpperCamelCase  ,						sr=self.sr  ,						n_fft=self.n_fft  ,						hop_length=self.hop_length  ,						n_iter=self.n_iter  )
        return audio





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


_A							=       logging.get_logger(__name__)

_A							=       {
    '''facebook/opt-125m''': '''https://huggingface.co/facebook/opt-125m/blob/main/config.json''',
    '''facebook/opt-350m''': '''https://huggingface.co/facebook/opt-350m/blob/main/config.json''',
    '''facebook/opt-1.3b''': '''https://huggingface.co/facebook/opt-1.3b/blob/main/config.json''',
    '''facebook/opt-2.7b''': '''https://huggingface.co/facebook/opt-2.7b/blob/main/config.json''',
    '''facebook/opt-6.7b''': '''https://huggingface.co/facebook/opt-6.7b/blob/main/config.json''',
    '''facebook/opt-13b''': '''https://huggingface.co/facebook/opt-13b/blob/main/config.json''',
}

class 		lowercase_							(							__SCREAMING_SNAKE_CASE					):
 A__    :					Dict    =     """opt"""
 A__    :					int    =     ["""past_key_values"""]

 def __init__(   self  ,						__UpperCamelCase=5_0_2_7_2  ,						__UpperCamelCase=7_6_8  ,						__UpperCamelCase=1_2  ,						__UpperCamelCase=3_0_7_2  ,						__UpperCamelCase=2_0_4_8  ,						__UpperCamelCase=True  ,						__UpperCamelCase=False  ,						__UpperCamelCase=None  ,						__UpperCamelCase=0.1  ,						__UpperCamelCase=0.0  ,						__UpperCamelCase=1_2  ,						__UpperCamelCase="relu"  ,						__UpperCamelCase=0.0  ,						__UpperCamelCase=0.02  ,						__UpperCamelCase=True  ,						__UpperCamelCase=1  ,						__UpperCamelCase=2  ,						__UpperCamelCase=2  ,						__UpperCamelCase=True  ,						__UpperCamelCase=True  ,						**__UpperCamelCase  ,						):




        """simple docstring"""


        super().__init__(
            pad_token_id=__UpperCamelCase  ,						bos_token_id=__UpperCamelCase  ,						eos_token_id=__UpperCamelCase  ,						**__UpperCamelCase  ,						)
        UpperCamelCase_											=							vocab_size
        UpperCamelCase_											=							max_position_embeddings
        UpperCamelCase_											=							num_attention_heads
        UpperCamelCase_											=							word_embed_proj_dim if word_embed_proj_dim is not None else hidden_size
        UpperCamelCase_											=							ffn_dim
        UpperCamelCase_											=							hidden_size
        UpperCamelCase_											=							num_hidden_layers
        UpperCamelCase_											=							dropout
        UpperCamelCase_											=							attention_dropout
        UpperCamelCase_											=							activation_function
        UpperCamelCase_											=							init_std
        UpperCamelCase_											=							layerdrop
        UpperCamelCase_											=							use_cache
        UpperCamelCase_											=							do_layer_norm_before
        # We keep these variables at `True` for backward compatibility.
        UpperCamelCase_											=							enable_bias
        UpperCamelCase_											=							layer_norm_elementwise_affine

        # Note that the only purpose of `_remove_final_layer_norm` is to keep backward compatibility
        # with checkpoints that have been fine-tuned before transformers v4.20.1
        # see https://github.com/facebookresearch/metaseq/pull/164
        UpperCamelCase_											=							_remove_final_layer_norm



