npdl.layers
ΒΆ
Layer |
The Layer class represents a single layer of a neural network. |
Linear |
A fully connected layer implemented as the dot product of inputs and weights. |
Dense |
A fully connected layer implemented as the dot product of inputs and weights. |
Softmax |
A fully connected layer implemented as the dot product of inputs and weights. |
Dropout |
A dropout layer. |
Convolution |
Convolution operator for filtering windows of two-dimensional inputs. |
Embedding |
BatchNormal |
Batch normalization layer (Ioffe and Szegedy, 2014) [R1] . |
MeanPooling |
Average pooling operation for spatial data. |
MaxPooling |
Max pooling operation for spatial data. |
Recurrent |
A recurrent neural network (RNN) is a class of artificial neural network where connections between units form a directed cycle. |
SimpleRNN |
Fully-connected RNN where the output is to be fed back to input. |
GRU |
Gated recurrent units (GRUs) are a gating mechanism in recurrent neural networks, introduced in 2014. |
LSTM |
Bacth LSTM, support mask, but not support training. |
BatchLSTM |
Batch LSTM, support training, but not support mask. |
Flatten |