mindspore.dataset.audio.MuLawEncoding
- class mindspore.dataset.audio.MuLawEncoding(quantization_channels=256)[source]
Encode signal based on mu-law companding.
- Parameters
quantization_channels (int, optional) – Number of channels, which must be positive. Default:
256
.- Raises
TypeError – If quantization_channels is not of type int.
ValueError – If quantization_channels is not a positive number.
- Supported Platforms:
CPU
Examples
>>> import numpy as np >>> import mindspore.dataset as ds >>> import mindspore.dataset.audio as audio >>> >>> # Use the transform in dataset pipeline mode >>> waveform = np.random.random([5, 3, 4]) # 5 samples >>> numpy_slices_dataset = ds.NumpySlicesDataset(data=waveform, column_names=["audio"]) >>> transforms = [audio.MuLawEncoding()] >>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms, input_columns=["audio"]) >>> for item in numpy_slices_dataset.create_dict_iterator(num_epochs=1, output_numpy=True): ... print(item["audio"].shape, item["audio"].dtype) ... break (3, 4) int32 >>> >>> # Use the transform in eager mode >>> waveform = np.random.random([3, 4]) # 1 sample >>> output = audio.MuLawEncoding()(waveform) >>> print(output.shape, output.dtype) (3, 4) int32
- Tutorial Examples: