Gain/Volume

This section covers several types of gain/volume effects, including gain.

Gain

class diffFx_pytorch.processors.gain.Gain(sample_rate, param_range=None)

Bases: ProcessorsBase

Differentiable implementation of a simple gain/volume control.

This processor implements a basic gain stage that applies amplitude scaling to the input signal. The gain is specified in decibels and converted to linear scaling internally.

The gain calculation follows:

\[y[n] = x[n] * 10^{gain_{dB}/20}\]

where:

• x[n] is the input signal

• gain_dB is the gain in decibels

• Division by 20 converts dB to amplitude ratio

Parameters:

• sample_rate (int) – Audio sample rate in Hz

• param_range (Dict[str, EffectParam]) – Parameter range for the gain control

Parameters Details:

gain_db: Gain control in decibels

• Default Range: -12.0 to 12.0 dB

• Logarithmic control for natural volume scaling

Examples

Basic DSP Usage:

>>> # Create a gain stage
>>> gain = Gain(sample_rate=44100)
>>> # Process audio
>>> output = gain(input_audio, dsp_params={
...     'gain_db': 6.0  # Boost by 6 dB (2x amplitude)
... })

Neural Network Control:

>>> # 1. Simple parameter prediction
>>> class GainController(nn.Module):
...     def __init__(self, input_size):
...         super().__init__()
...         self.net = nn.Sequential(
...             nn.Linear(input_size, 32),
...             nn.ReLU(),
...             nn.Linear(32, 1),  # Single gain parameter
...             nn.Sigmoid()  # Ensures output is in [0,1] range
...         )
...
...     def forward(self, x):
...         return self.net(x)
>>>
>>> # Process with features
>>> controller = GainController(input_size=16)
>>> features = torch.randn(batch_size, 16)
>>> norm_params = controller(features)
>>> output = gain(input_audio, norm_params=norm_params)

A classic gain stage that applies amplitude scaling to the input signal

__init__(sample_rate, param_range=None)

Initialize the processor base.

Parameters:

• sample_rate (int) – Audio sample rate in Hz

• param_range (Optional[Dict[str, EffectParam]]) – Optional parameter definitions to override defaults

_register_default_parameters()

Register gain parameter (-12.0 to 12.0 dB).

process(x, norm_params=None, dsp_params=None)

Process input signal through the gain stage.

Parameters:

• x (torch.Tensor) – Input audio tensor. Shape: (batch, channels, samples)

• norm_params (Dict[str, torch.Tensor]) – Normalized parameters (0 to 1)

• dsp_params (Dict[str, Union[float, torch.Tensor]], optional) – Direct DSP parameters. Can specify gain_db as: - float/int: Single value applied to entire batch - 0D tensor: Single value applied to entire batch - 1D tensor: Batch of values matching input batch size Parameters will be automatically expanded to match batch size and moved to input device if necessary. If provided, norm_params must be None.

Returns:

Processed audio tensor of same shape as input

Return type:

torch.Tensor