Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)  1.0.0
Performance library for Deep Learning
Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 123]
 Cmkldnn::convolution_forward::descDescriptor for convolution forward propagation
 Cmkldnn::batch_normalization_backward::descDescriptor for batch normalization backward propagation
 Cmkldnn::inner_product_forward::descInitializes an inner product descriptor for forward propagation using prop_kind (possible values are mkldnn::prop_kind::forward_training and mkldnn::prop_kind::forward_inference) and memory descriptors
 Cmkldnn::deconvolution_backward_weights::descDescriptor for deconvolution weight update
 Cmkldnn::inner_product_backward_data::descInitializes an inner product descriptor for backward propagation with respect to data using memory descriptors
 Cmkldnn::lrn_forward::descDescriptor for local response normalization forward propagation
 Cmkldnn::inner_product_backward_weights::descInitializes an inner product descriptor for backward propagation with respect to weights using memory descriptors
 Cmkldnn::vanilla_rnn_forward::descDescriptor for RNN forward propagation
 Cmkldnn::vanilla_rnn_backward::descRNN descriptor for backward propagation
 Cmkldnn::lrn_backward::descDescriptor for local response normalization backward propagation
 Cmkldnn::lstm_forward::descDescriptor for LSTM forward propagation
 Cmkldnn::pooling_forward::descDescriptor for pooling forward propagation
 Cmkldnn::lstm_backward::descLSTM descriptor for backward propagation
 Cmkldnn::convolution_backward_data::descDescriptor for convolution backward propagation
 Cmkldnn::gru_forward::descDescriptor for GRU forward propagation
 Cmkldnn::gru_backward::descGRU descriptor for backward propagation
 Cmkldnn::pooling_backward::descDescriptor for pooling backward propagation
 Cmkldnn::lbr_gru_forward::descDescriptor for LBR GRU forward propagation
 Cmkldnn::convolution_backward_weights::descDescriptor for convolution weight update
 Cmkldnn::eltwise_forward::descInitializes an eltwise descriptor for forward propagation using prop_kind (possible values are mkldnn::forward_training and mkldnn::forward_inference), aalgorithm algorithm, memory descriptor data_desc, alpha, and beta parameters
 Cmkldnn::lbr_gru_backward::descLBR_GRU descriptor for backward propagation
 Cmkldnn::shuffle_forward::descDescriptor for shuffle forward propagation
 Cmkldnn::eltwise_backward::descInitializes an eltwise descriptor for backward propagation using aalgorithm algorithm memory descriptors diff_data_desc and data_desc, and the alpha and beta parameters
 Cmkldnn::memory::descA memory descriptor
 Cmkldnn::softmax_forward::descDescriptor for softmax forward propagation
 Cmkldnn::softmax_backward::descDescriptor for softmax backward propagation
 Cmkldnn::deconvolution_forward::descDescriptor for convolution forward propagation
 Cmkldnn::batch_normalization_forward::descDescriptor for batch normalization forward propagation
 Cmkldnn::deconvolution_backward_data::descDescriptor for deconvolution backward propagation
 Cmkldnn::errorIntel(R) MKL-DNN exception class
 Cmkldnn::handle< T, traits >A class for wrapping an Intel(R) MKL-DNN handle
 Cmkldnn::handle< mkldnn_engine_t >
 Cmkldnn::engineAn execution engine
 Cmkldnn::handle< mkldnn_memory_t >
 Cmkldnn::memoryMemory that describes the data
 Cmkldnn::handle< mkldnn_post_ops_t >
 Cmkldnn::post_opsPost operations
 Cmkldnn::handle< mkldnn_primitive_attr_t >
 Cmkldnn::primitive_attrPrimitive attributes
 Cmkldnn::handle< mkldnn_primitive_desc_iterator >
 Cmkldnn::handle< mkldnn_primitive_desc_t >
 Cmkldnn::primitive_descA base class for all primitive descriptors
 Cmkldnn::handle< mkldnn_primitive_t >
 Cmkldnn::primitiveBase class for all computational primitives
 Cmkldnn::handle< mkldnn_stream_t >
 Cmkldnn::streamAn execution stream
 Cmkldnn::handle_traits< T >A class that provides the destructor for an Intel(R) MKL-DNN C handle
 Cmkldnn_batch_normalization_desc_tA descriptor of a Batch Normalization operation
 Cmkldnn_blocking_desc_tGeneric description of blocked data layout for most memory formats
 Cmkldnn_convolution_desc_tA descriptor of a convolution operation
 Cmkldnn_eltwise_desc_tA descriptor of a element-wise operation
 Cmkldnn_engineAn opaque structure to describe an engine
 Cmkldnn_exec_arg_tAn auxiliary structure to specify primitive's inputs/outputs at execution
 Cmkldnn_inner_product_desc_tA descriptor of an inner product operation
 Cmkldnn_lrn_desc_tA descriptor of a Local Response Normalization (LRN) operation
 Cmkldnn_memoryAn opaque structure to describe a memory
 Cmkldnn_memory_desc_tMemory descriptor
 Cmkldnn_memory_extra_desc_tDescription of extra information stored in memory
 Cmkldnn_pooling_desc_tA descriptor of a pooling operation
 Cmkldnn_post_opsAn opaque structure for a chain of post operations
 Cmkldnn_primitiveAn opaque structure to describe a primitive
 Cmkldnn_primitive_attrAn opaque structure for primitive descriptor attributes
 Cmkldnn_primitive_descAn opaque structure to describe a primitive descriptor
 Cmkldnn_primitive_desc_iteratorAn opaque structure to describe a primitive descriptor iterator
 Cmkldnn_rnn_desc_tA descriptor for an RNN operation
 Cmkldnn_rnn_packed_desc_tDescription of tensor of packed weights for rnn
 Cmkldnn_shuffle_desc_tA descriptor of a shuffle operation
 Cmkldnn_softmax_desc_tA descriptor of a Softmax operation
 Cmkldnn_streamAn opaque structure to describe an execution stream
 Cmkldnn_version_tVersion type
 Cmkldnn_wino_desc_tDescription of tensor of weights for winograd 2x3 convolution