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| import warnings | |
| from sys import platform | |
| from typing import Optional | |
| import torch | |
| import torchaudio | |
| dict_format = { | |
| torch.uint8: "u8", | |
| torch.int16: "s16", | |
| torch.int32: "s32", | |
| torch.int64: "s64", | |
| torch.float32: "flt", | |
| torch.float64: "dbl", | |
| } | |
| def play_audio( | |
| waveform: torch.Tensor, | |
| sample_rate: Optional[float], | |
| device: Optional[str] = None, | |
| ) -> None: | |
| """Plays audio through specified or available output device. | |
| .. warning:: | |
| This function is currently only supported on MacOS, and requires | |
| libavdevice (FFmpeg) with ``audiotoolbox`` output device. | |
| .. note:: | |
| This function can play up to two audio channels. | |
| Args: | |
| waveform: Tensor containing the audio to play. | |
| Expected shape: `(time, num_channels)`. | |
| sample_rate: Sample rate of the audio to play. | |
| device: Output device to use. If None, the default device is used. | |
| """ | |
| if platform == "darwin": | |
| device = device or "audiotoolbox" | |
| path = "-" | |
| else: | |
| raise ValueError(f"This function only supports MacOS, but current OS is {platform}") | |
| available_devices = list(torchaudio.utils.ffmpeg_utils.get_output_devices().keys()) | |
| if device not in available_devices: | |
| raise ValueError(f"Device {device} is not available. Available devices are: {available_devices}") | |
| if waveform.dtype not in dict_format: | |
| raise ValueError(f"Unsupported type {waveform.dtype}. The list of supported types is: {dict_format.keys()}") | |
| format = dict_format[waveform.dtype] | |
| if waveform.ndim != 2: | |
| raise ValueError(f"Expected 2D tensor with shape `(time, num_channels)`, got {waveform.ndim}D tensor instead") | |
| time, num_channels = waveform.size() | |
| if num_channels > 2: | |
| warnings.warn( | |
| f"Expected up to 2 channels, got {num_channels} channels instead. " | |
| "Only the first 2 channels will be played.", | |
| stacklevel=2, | |
| ) | |
| # Write to speaker device | |
| s = torchaudio.io.StreamWriter(dst=path, format=device) | |
| s.add_audio_stream(sample_rate, num_channels, format=format) | |
| # write audio to the device | |
| block_size = 256 | |
| with s.open(): | |
| for i in range(0, time, block_size): | |
| s.write_audio_chunk(0, waveform[i : i + block_size, :]) | |