asteroid.masknn.norms module¶

class asteroid.masknn.norms.BatchNorm(*args, **kwargs)[source]¶

Bases: sphinx.ext.autodoc.importer._MockObject

Wrapper class for pytorch BatchNorm1D and BatchNorm2D

class asteroid.masknn.norms.ChanLN(channel_size)[source]¶

Bases: asteroid.masknn.norms._LayerNorm

Channel-wise Layer Normalization (chanLN).

forward(x)[source]¶

Applies forward pass.

Works for any input size > 2D.

Parameters:	x (`torch.Tensor`) – [batch, chan, *]
Returns:	`torch.Tensor` – chanLN_x [batch, chan, *]

class asteroid.masknn.norms.CumLN(channel_size)[source]¶

Bases: asteroid.masknn.norms._LayerNorm

Cumulative Global layer normalization(cumLN).

forward(x)[source]¶

Parameters:	x (`torch.Tensor`) – Shape [batch, channels, length]
Returns:	`torch.Tensor` – cumLN_x [batch, channels, length]

class asteroid.masknn.norms.FeatsGlobLN(channel_size)[source]¶

Bases: asteroid.masknn.norms._LayerNorm

feature-wise global Layer Normalization (FeatsGlobLN). Applies normalization over frames for each channel.

forward(x)[source]¶

Applies forward pass.

Works for any input size > 2D.

Parameters:	x (`torch.Tensor`) – [batch, chan, time]
Returns:	`torch.Tensor` – chanLN_x [batch, chan, time]

class asteroid.masknn.norms.GlobLN(channel_size)[source]¶

Bases: asteroid.masknn.norms._LayerNorm

Global Layer Normalization (globLN).

forward(x)[source]¶

Applies forward pass.

Works for any input size > 2D.

Parameters:	x (`torch.Tensor`) – Shape [batch, chan, *]
Returns:	`torch.Tensor` – gLN_x [batch, chan, *]

asteroid.masknn.norms.get(identifier)[source]¶

Returns a norm class from a string. Returns its input if it is callable (already a _LayerNorm for example).

Parameters:	identifier (str or Callable or None) – the norm identifier.
Returns:	`_LayerNorm` or None

asteroid.masknn.norms.register_norm(custom_norm)[source]¶

Register a custom norm, gettable with norms.get.

Parameters:	custom_norm – Custom norm to register.