Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)  0.17
Performance library for Deep Learning
Modules
Here is a list of all modules:
[detail level 1234]
 C API
 Primitive operations
 Common primitive operations
 AttributesAn extension for controlling primitive behavior
 Sequence of post operationsAn extension for performing extra operations after base operation
 MemoryA primitive to describe and store data
 ReorderA primitive to copy data between memory formats
 ConcatA primitive to concatenate data by arbitrary dimension
 SumA primitive to sum data
 ConvolutionA primitive to compute convolution using different algorithms
 DeconvolutionA primitive to compute deconvolution using different algorithms
 ShuffleA primitive to shuffle data along the axis
 EltwiseA primitive to compute element wise operations like parametric rectifier linear unit (ReLU)
 ReLU (deprecated, use Eltwise instead)A primitive to compute a parametric rectifier linear unit (ReLU)
 SoftmaxA primitive to perform softmax
 PoolingA primitive to perform max or average pooling
 LRNA primitive to perform local response normalization (LRN) across or within channels
 Batch NormalizationA primitive to perform batch normalization
 Inner productA primitive to compute an inner product
 Convolution followed by ReLU (deprecated)A merged primitive to compute a convolution followed by relu
 RNNA primitive to compute common recurrent layer
 Engine operations
 Execution stream operations
 Service functions
 BLAS functions
 Types
 Generic
 Auxiliary types for memory description
 Operation descriptors
 Engine
 Primitive descriptor iterators
 Primitive descriptors
 Primitive descriptor attributes
 Primitive
 Queries
 Execution stream
 C++ API
 Utils
 Common data types and enumerationsA proxy to Types in C API
 AttributesAn extension for controlling primitive behavior
 EngineEngine operations
 Memory and memory related operations
 MemoryA primitive to describe and store data
 ReorderA primitive to copy data between memory formats
 ViewA primitive to view on a memory
 ConcatA primitive to concatenate data by arbitrary dimension
 SumA primitive to sum data
 Primitives
 Primitive descriptors
 ConvolutionA primitive to compute convolution using different algorithms
 DeconvolutionA primitive to compute deconvolution using different algorithms
 LRNA primitive to perform local response normalization (LRN) across or within channels
 PoolingA primitive to perform max or average pooling
 EltwiseA primitive to compute element wise operations like parametric rectifier linear unit (ReLU)
 SoftmaxA primitive to perform softmax
 Batch normalizationA primitive to perform batch normalization
 Inner ProductA primitive to compute an inner product
 RNNA primitive to compute common recurrent layer
 ShuffleA primitive to shuffle data along the axis
 StreamExecution stream operations