fishy.models.deep.cnn

Simple Convolutional Neural Network (CNN) model for spectral classification.

Classes

class fishy.models.deep.cnn.CNN(input_dim: int, output_dim: int, hidden_dim: int = 128, num_layers: int = 4, dropout: float = 0.2, **kwargs)[source]

Bases: Module

Standard CNN architecture for 1D spectral data.

__init__(input_dim: int, output_dim: int, hidden_dim: int = 128, num_layers: int = 4, dropout: float = 0.2, **kwargs) → None[source]

Initializes the CNN model.

Parameters:

  • input_dim (int) – Number of input features.

  • output_dim (int) – Number of output classes.

  • hidden_dim (int, optional) – Hidden dimension. Defaults to 128.

  • num_layers (int, optional) – Number of layers. Defaults to 4.

  • dropout (float, optional) – Dropout rate. Defaults to 0.2.

forward(x: Tensor) → Tensor[source]

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

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