Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)
0.19.0
Performance library for Deep Learning
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![]() ![]() ![]() | An extension for controlling primitive behavior |
![]() ![]() ![]() ![]() | An extension for performing extra operations after a base operation |
![]() ![]() ![]() | A primitive to describe and store data |
![]() ![]() ![]() | A primitive to copy data between memory formats |
![]() ![]() ![]() | A primitive to concatenate data by arbitrary dimension |
![]() ![]() ![]() | A primitive to sum data |
![]() ![]() ![]() | A primitive to compute convolution using different algorithms |
![]() ![]() ![]() | A primitive to compute deconvolution using different algorithms |
![]() ![]() ![]() | A primitive to shuffle data along the axis |
![]() ![]() ![]() | A primitive to compute element-wise operations like parametric rectifier linear unit (ReLU) |
![]() ![]() ![]() | A primitive to perform softmax |
![]() ![]() ![]() | A primitive to perform max or average pooling |
![]() ![]() ![]() | A primitive to perform local response normalization (LRN) across or within channels |
![]() ![]() ![]() | A primitive to perform batch normalization |
![]() ![]() ![]() | A primitive to compute an inner product |
![]() ![]() ![]() | A primitive to compute the common recurrent layer |
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![]() ![]() | A subset of Basic Linear ALgebra (BLAS) functions to perform matrix-matrix multiplication |
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![]() ![]() | A proxy to Types in C API |
![]() ![]() | An extension for controlling primitive behavior |
![]() ![]() | Engine operations |
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![]() ![]() ![]() | A primitive to describe and store data |
![]() ![]() ![]() | A primitive to copy data between memory formats |
![]() ![]() ![]() | A primitive to view on a memory |
![]() ![]() ![]() | A primitive to concatenate data by arbitrary dimension |
![]() ![]() ![]() | A primitive to sum data |
![]() ![]() | |
![]() ![]() ![]() | |
![]() ![]() ![]() | A primitive to compute convolution using different algorithms |
![]() ![]() ![]() | A primitive to compute deconvolution using different algorithms |
![]() ![]() ![]() | A primitive to perform local response normalization (LRN) across or within channels |
![]() ![]() ![]() | A primitive to perform max or average pooling |
![]() ![]() ![]() | A primitive to compute element-wise operations like parametric rectifier linear unit (ReLU) |
![]() ![]() ![]() | A primitive to perform softmax |
![]() ![]() ![]() | A primitive to perform batch normalization |
![]() ![]() ![]() | A primitive to compute an inner product |
![]() ![]() ![]() | A primitive to compute common recurrent layer |
![]() ![]() ![]() | A primitive to shuffle data along the axis |
![]() ![]() | Execution stream operations |