Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)
0.21.0
Performance library for Deep Learning
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Modules | |
Common primitive operations | |
Attributes | |
An extension for controlling primitive behavior. | |
Memory | |
A primitive to describe and store data. | |
Reorder | |
A primitive to copy data between memory formats. | |
Concat | |
A primitive to concatenate data by arbitrary dimension. | |
Sum | |
A primitive to sum data. | |
Convolution | |
A primitive to compute convolution using different algorithms. | |
Deconvolution | |
A primitive to compute deconvolution using different algorithms. | |
Shuffle | |
A primitive to shuffle data along the axis. | |
Eltwise | |
A primitive to compute element-wise operations like parametric rectifier linear unit (ReLU). | |
Softmax | |
A primitive to perform softmax. | |
Pooling | |
A primitive to perform max or average pooling. | |
LRN | |
A primitive to perform local response normalization (LRN) across or within channels. | |
Batch Normalization | |
A primitive to perform batch normalization. | |
Inner product | |
A primitive to compute an inner product. | |
RNN | |
A primitive to compute the common recurrent layer. | |