nirs4all.operators.models.pytorch.nicon module

class nirs4all.operators.models.pytorch.nicon.DepthwiseConv1D(*args: Any, **kwargs: Any)

Bases: Module

forward(x)

class nirs4all.operators.models.pytorch.nicon.GlobalAveragePooling1D(*args: Any, **kwargs: Any)

Bases: Module

forward(x)

class nirs4all.operators.models.pytorch.nicon.LayerNorm1D(*args: Any, **kwargs: Any)

Bases: Module

Layer Normalization over the channel dimension for (N, C, L) input.

forward(x)

class nirs4all.operators.models.pytorch.nicon.SeparableConv1D(*args: Any, **kwargs: Any)

Bases: Module

forward(x)

class nirs4all.operators.models.pytorch.nicon.SpatialDropout1D(*args: Any, **kwargs: Any)

Bases: Module

Spatial Dropout 1D (drops entire channels). Expects input shape: (Batch, Channels, Length)

forward(x: torch.Tensor) → torch.Tensor

nirs4all.operators.models.pytorch.nicon.customizable_decon(input_shape, params=None)

nirs4all.operators.models.pytorch.nicon.customizable_decon_classification(input_shape, num_classes=2, params=None)

nirs4all.operators.models.pytorch.nicon.customizable_nicon(input_shape, params=None)

nirs4all.operators.models.pytorch.nicon.customizable_nicon_classification(input_shape, num_classes=2, params=None)

nirs4all.operators.models.pytorch.nicon.decon(input_shape, params=None)

nirs4all.operators.models.pytorch.nicon.decon_Sep(input_shape, params=None)

nirs4all.operators.models.pytorch.nicon.decon_Sep_classification(input_shape, num_classes=2, params=None)

nirs4all.operators.models.pytorch.nicon.decon_classification(input_shape, num_classes=2, params=None)

nirs4all.operators.models.pytorch.nicon.decon_layer_classification(input_shape, num_classes=2, params=None)

nirs4all.operators.models.pytorch.nicon.get_activation(name: str | None)

nirs4all.operators.models.pytorch.nicon.get_norm(method: str, num_features: int)

nirs4all.operators.models.pytorch.nicon.nicon(input_shape, params=None)

nirs4all.operators.models.pytorch.nicon.nicon_VG(input_shape, params=None)

nirs4all.operators.models.pytorch.nicon.nicon_VG_classification(input_shape, num_classes=2, params=None)

nirs4all.operators.models.pytorch.nicon.nicon_classification(input_shape, num_classes=2, params=None)

nirs4all.operators.models.pytorch.nicon.thin_nicon(input_shape, params=None)

nirs4all.operators.models.pytorch.nicon.transformer(input_shape, params=None)

nirs4all.operators.models.pytorch.nicon.transformer_VG(input_shape, params=None)

nirs4all.operators.models.pytorch.nicon.transformer_VG_classification(input_shape, num_classes=2, params=None)

nirs4all.operators.models.pytorch.nicon.transformer_classification(input_shape, num_classes=2, params=None)

nirs4all.operators.models.pytorch.nicon.transformer_model(input_shape, params=None)

nirs4all.operators.models.pytorch.nicon.transformer_model_classification(input_shape, num_classes=2, params=None)