Modules

Here is a list of all modules:

[detail level 1234]

▼C API
▼Primitive operations
Common primitive operations
▼Attributes	An extension for controlling primitive behavior
Sequence of post operations	An extension for performing extra operations after a base operation
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
Binary	A primitive to perform tensor operations over two tensors
Convolution	The convolution primitive computes a forward, backward, or weight update for a batched convolution operation on 1D, 2D, or 3D spatial data with bias
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 such as 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
Layer Normalization	A primitive to perform layer normalization
Inner product	A primitive to compute an inner product
RNN	A primitive to compute the common recurrent layer
Engine operations
Execution stream operations
Service functions
BLAS functions	A subset of Basic Linear ALgebra (BLAS) functions to perform matrix-matrix multiplication
▼Types
Generic
Memory
Operation descriptors
Engine
Primitive descriptor iterators
Primitive descriptors
Primitive descriptor attributes
▼Primitive
Argument indices
Queries
Execution stream
▼C++ API
Utils
Common data types and enumerations	A proxy to Types in C API
Attributes	An extension for controlling primitive behavior
Engine	Engine operations
Stream	Execution stream operations
▼Memory and memory related operations
Memory	A primitive to describe and store data
▼Primitives
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
Reorder	A primitive to copy data between memory formats
Concat	A primitive to concatenate data by arbitrary dimension
Sum	A primitive to sum data