yjyddlmZddlmZmZer ddlmZddlmZGddZ d"d Z d#d$dZ d%d&d!Z dS)') annotations) TYPE_CHECKINGBinaryIO)Path)TensorcNeZdZUdZded<ded<ded<ded<ded<d d Zd S) AudioInfoz0Audio info, return type of backend info functionint sample_rate num_samples num_channelsbits_per_samplestrencodingreturnNonecL||_||_||_||_||_dS)N)r r r rr)selfr r r rrs m/lsinfo/ai/hellotax_ai/data_center/backend/venv/lib/python3.11/site-packages/paddle/audio/backends/backend.py__init__zAudioInfo.__init__"s/'&(.  N) r r r r r r rr rrrr)__name__ __module__ __qualname____doc____annotations__rrrr r si::MMM ! ! ! ! ! !rr filepathstr | BinaryIOrc td)aGet signal information of input audio file. Args: filepath: audio path or file object. Returns: AudioInfo: info of the given audio. Example: .. code-block:: python >>> import os >>> import paddle >>> sample_rate = 16000 >>> wav_duration = 0.5 >>> num_channels = 1 >>> num_frames = sample_rate * wav_duration >>> wav_data = paddle.linspace(-1.0, 1.0, int(num_frames)) * 0.1 >>> waveform = wav_data.tile([num_channels, 1]) >>> base_dir = os.getcwd() >>> filepath = os.path.join(base_dir, "test.wav") >>> paddle.audio.save(filepath, waveform, sample_rate) >>> wav_info = paddle.audio.info(filepath) please set audio backendNotImplementedError)rs rinfor$1s8 8 9 99rT str | Path frame_offsetr num_frames normalizeboolchannels_firsttuple[Tensor, int]c td)aLoad audio data from file.Load the audio content start form frame_offset, and get num_frames. Args: frame_offset: from 0 to total frames, num_frames: from -1 (means total frames) or number frames which want to read, normalize: if True: return audio which norm to (-1, 1), dtype=float32 if False: return audio with raw data, dtype=int16 channels_first: if True: return audio with shape (channels, time) Return: Tuple[paddle.Tensor, int]: (audio_content, sample rate) Examples: .. code-block:: python >>> import os >>> import paddle >>> sample_rate = 16000 >>> wav_duration = 0.5 >>> num_channels = 1 >>> num_frames = sample_rate * wav_duration >>> wav_data = paddle.linspace(-1.0, 1.0, int(num_frames)) * 0.1 >>> waveform = wav_data.tile([num_channels, 1]) >>> base_dir = os.getcwd() >>> filepath = os.path.join(base_dir, "test.wav") >>> paddle.audio.save(filepath, waveform, sample_rate) >>> wav_data_read, sr = paddle.audio.load(filepath) r!r")rr'r(r)r+s rloadr.PsR 8 9 99rNrsrcrr r str | Noner int | Nonerc td)a Save audio tensor to file. Args: filepath: saved path src: the audio tensor sample_rate: the number of samples of audio per second. channels_first: src channel information if True, means input tensor is (channels, time) if False, means input tensor is (time, channels) encoding:encoding format, wave_backend only support PCM16 now. bits_per_sample: bits per sample, wave_backend only support 16 bits now. Returns: None Examples: .. code-block:: python >>> import paddle >>> sample_rate = 16000 >>> wav_duration = 0.5 >>> num_channels = 1 >>> num_frames = sample_rate * wav_duration >>> wav_data = paddle.linspace(-1.0, 1.0, int(num_frames)) * 0.1 >>> waveform = wav_data.tile([num_channels, 1]) >>> filepath = "./test.wav" >>> paddle.audio.save(filepath, waveform, sample_rate) r!r")rr0r r+rrs rsaver4|sP 8 9 99r)rrrr )rr%TT) rr&r'r r(r r)r*r+r*rr,)TNr/)rrr0rr r r+r*rr1rr2rr) __future__rtypingrrpathlibrpaddlerr r$r.r4rrrr9s#"""""********!!!!!!!!0::::B ):):):):):` "$ (:(:(:(:(:(:(:r