

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

				_SCREAMING_SNAKE_CASE       :  Union[str, Any]        = True
				_SCREAMING_SNAKE_CASE       :  List[str]        = """"""
except Exception as e:
				_SCREAMING_SNAKE_CASE       :  int        = False
				_SCREAMING_SNAKE_CASE       :  str        = (
				    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     __a   (      UpperCAmelCase__,    UpperCAmelCase__    ):

			"""simple docstring"""

			SCREAMING_SNAKE_CASE_						     =						'mel_config.json'






			@register_to_config
			def __init__(							self     :					Optional[Any]						,  lowercase_     :					Optional[int] = 256						,  lowercase_     :					Union[str, Any] = 256						,  lowercase_     :					List[Any] = 2_2050						,  lowercase_     :					List[Any] = 2048						,  lowercase_     :					Union[str, Any] = 512						,  lowercase_     :					Optional[Any] = 80						,  lowercase_     :					List[Any] = 32						,  ):
								UpperCamelCase__		:    Optional[int]         =hop_length
								UpperCamelCase__		:    List[str]         =sample_rate
								UpperCamelCase__		:    Any         =n_fft
								UpperCamelCase__		:    List[str]         =top_db
								UpperCamelCase__		:    Union[str, Any]         =n_iter
								self.set_resolution(lowerCamelCase__						,  lowerCamelCase__						)
								UpperCamelCase__		:    Union[str, Any]         =None

								if not _librosa_can_be_imported:
													raise ValueError(_import_error						)






			def    _lowerCAmelCase			(							self     :					List[Any]						,  lowercase_     :					List[Any]						,  lowercase_     :					int						):
								UpperCamelCase__		:    Union[str, Any]         =x_res
								UpperCamelCase__		:    Any         =y_res
								UpperCamelCase__		:    List[str]         =self.y_res
								UpperCamelCase__		:    Optional[int]         =self.x_res * self.hop_length - 1






			def    _lowerCAmelCase			(							self     :					int						,  lowercase_     :					List[str] = None						,  lowercase_     :					str = None						):
								if audio_file is not None:
													UpperCamelCase__		:    List[Any]         =librosa.load(lowerCamelCase__						,  mono=lowerCamelCase__						,  sr=self.sr						)
								else:
													UpperCamelCase__		:    Tuple         =raw_audio

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






			def    _lowerCAmelCase			(							self     :					Dict						):
								return len(self.audio						) // self.slice_size






			def    _lowerCAmelCase			(							self     :					Dict						,  lowercase_     :					Tuple = 0						):
								return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]






			def    _lowerCAmelCase			(							self     :					str						):
								return self.sr






			def    _lowerCAmelCase			(							self     :					Dict						,  lowercase_     :					Dict						):
								UpperCamelCase__		:    Optional[Any]         =librosa.feature.melspectrogram(
								    y=self.get_audio_slice(lowerCamelCase__						)						,  sr=self.sr						,  n_fft=self.n_fft						,  hop_length=self.hop_length						,  n_mels=self.n_mels						)
								UpperCamelCase__		:    int         =librosa.power_to_db(lowerCamelCase__						,  ref=np.max						,  top_db=self.top_db						)
								UpperCamelCase__		:    int         =(((log_S + self.top_db) * 255 / self.top_db).clip(0						,  255						) + 0.5).astype(np.uinta						)
								UpperCamelCase__		:    Optional[Any]         =Image.fromarray(lowerCamelCase__						)
								return image






			def    _lowerCAmelCase			(							self     :					List[Any]						,  lowercase_     :					Tuple						):
								UpperCamelCase__		:    Optional[int]         =np.frombuffer(image.tobytes()						,  dtype='''uint8'''						).reshape((image.height, image.width)						)
								UpperCamelCase__		:    Tuple         =bytedata.astype('''float'''						) * self.top_db / 255 - self.top_db
								UpperCamelCase__		:    Optional[int]         =librosa.db_to_power(lowerCamelCase__						)
								UpperCamelCase__		:    Tuple         =librosa.feature.inverse.mel_to_audio(
								    lowerCamelCase__						,  sr=self.sr						,  n_fft=self.n_fft						,  hop_length=self.hop_length						,  n_iter=self.n_iter						)
								return audio





"""simple docstring"""





import io
import json
import subprocess


_SCREAMING_SNAKE_CASE       :  List[Any]        = [
    ["""en""", """ru"""],
    ["""ru""", """en"""],
    ["""en""", """de"""],
    ["""de""", """en"""],
]

_SCREAMING_SNAKE_CASE       :  str        = 8



def        _lowerCAmelCase      (						UpperCAmelCase     :							Tuple      ,							UpperCAmelCase     :							List[Any]				):


					'''simple docstring'''






					UpperCamelCase__		:    Any         ={}
					for src, tgt in pairs:
										UpperCamelCase__		:    Optional[int]         =F'''{src}-{tgt}'''
										UpperCamelCase__		:    int         =F'''sacrebleu -t wmt19 -l {pair} --echo src'''.split()
										UpperCamelCase__		:    str         =subprocess.run(UpperCAmelCase      ,							stdout=subprocess.PIPE				).stdout.decode('''utf-8'''				).splitlines()
										UpperCamelCase__		:    List[Any]         =F'''sacrebleu -t wmt19 -l {pair} --echo ref'''.split()
										UpperCamelCase__		:    str         =subprocess.run(UpperCAmelCase      ,							stdout=subprocess.PIPE				).stdout.decode('''utf-8'''				).splitlines()
										UpperCamelCase__		:    Any         ={'''src''': src_lines[:n_objs], '''tgt''': tgt_lines[:n_objs]}
					return text


_SCREAMING_SNAKE_CASE       :  List[str]        = get_all_data(pairs, n_objs)
_SCREAMING_SNAKE_CASE       :  Optional[Any]        = """./fsmt_val_data.json"""
with io.open(filename, """w""", encoding="""utf-8""") as f:
				_SCREAMING_SNAKE_CASE       :  Any        = json.dump(text, f, indent=2, ensure_ascii=False)


