mindspore.dataset.audio.Gain

class mindspore.dataset.audio.Gain(gain_db=1.0)[source]

Apply amplification or attenuation to the whole waveform.

Parameters: gain_db (float) – Gain adjustment in decibels (dB). Default: 1.0.
Raises: TypeError – If gain_db is not of type float.

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, 8])  # 5 samples
>>> numpy_slices_dataset = ds.NumpySlicesDataset(data=waveform, column_names=["audio"])
>>> transforms = [audio.Gain(1.2)]
>>> 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
(8,) float64
>>>
>>> # Use the transform in eager mode
>>> waveform = np.random.random([8])  # 1 sample
>>> output = audio.Gain(1.2)(waveform)
>>> print(output.shape, output.dtype)
(8,) float64

Tutorial Examples:

Illustration of audio transforms