Deep Neural Network Library (DNNL)  1.1.3
Performance library for Deep Learning
Modules

Modules

 Primitive descriptors
 
 Convolution
 Computes a forward propagation, backward propagation, or weight update for convolution operation with bias on a batch of multi-dimensional tensors.
 
 Deconvolution
 A primitive to compute deconvolution using different algorithms.
 
 LRN
 A primitive to perform local response normalization (LRN) across or within channels.
 
 Pooling
 A primitive to perform max or average pooling.
 
 Eltwise
 A primitive to compute element-wise operations such as rectified linear unit (ReLU).
 
 Softmax
 A primitive to perform softmax.
 
 Batch normalization
 A primitive to perform batch normalization.
 
 layer normalization
 A primitive to perform layer normalization.
 
 Inner Product
 A primitive to compute an inner product.
 
 RNN
 A primitive to compute common recurrent layer.
 
 Shuffle
 A primitive to shuffle data along the axis.
 
 Binary
 A primitive to perform tensor operations over two tensors.
 

Detailed Description