Layers

Core modules

Module	Base abstract class for all the modules.
Parameter	Class representing a learnable parameter.

Layers

Layers are basic building blocks of neural networks.

The following table lists the available layers:

Conv1D	Apply a 1D convolution.
Conv2D	Apply a 2D convolution.
GRUCell	Apply a Gated Recurrent Unit (GRU) cell.
Linear	Apply a linear transformation over the final dimension of the input.
LSTMCell	Apply a Long Short-Term Memory (LSTM) cell.
RNNCell	Apply a Elman's Recurrent Neural Network (RNN) cell.
Sequential	Apply callable modules (e.g. layers, activation functions, etc.) connected in a cascading sequence.