oneAPI Deep Neural Network Library (oneDNN)
1.4.0
Performance library for Deep Learning
  dnnl | OneDNN namespace |
   error | OneDNN exception class |
| handle_traits | A class that provides the destructor for a oneDNN C API handle |
| handle | OneDNN C API handle wrapper class |
| primitive | Base class for all computational primitives |
| engine | An execution engine |
| stream_attr | A container for stream attributes |
| stream | An execution stream |
 memory | Memory object |
| post_ops | Post-ops |
| primitive_attr | Primitive attributes |
| primitive_desc_base | Base class for all primitive descriptors |
| reorder | Reorder primitive |
| concat | Tensor concatenation (concat) primitive |
| sum | Out-of-place summation (sum) primitive |
| primitive_desc | A base class for descriptors of all primitives that have an operation descriptor and that support iteration over multiple implementations |
| convolution_forward | Convolution forward propagation primitive |
| convolution_backward_data | Convolution backward propagation primitive |
| convolution_backward_weights | Convolution weights gradient primitive |
| deconvolution_forward | Deconvolution forward propagation primitive |
| deconvolution_backward_data | Deconvolution backward propagation primitive |
| deconvolution_backward_weights | Deconvolution weights gradient primitive |
| lrn_forward | Local response normalization (LRN) forward propagation primitive |
| lrn_backward | Local response normalization (LRN) backward propagation primitive |
| pooling_forward | Pooling forward propagation primitive |
| pooling_backward | Pooling backward propagation primitive |
| eltwise_forward | Elementwise unary operation forward propagation primitive |
| eltwise_backward | Elementwise unary operation backward propagation primitive |
| softmax_forward | Softmax forward propagation primitive |
| softmax_backward | Softmax backward propagation primitive |
| logsoftmax_forward | Logsoftmax forward propagation primitive |
| logsoftmax_backward | Logsoftmax backward propagation primitive |
| batch_normalization_forward | Batch normalization forward propagation primitive |
| batch_normalization_backward | Batch normalization backward propagation primitive |
| layer_normalization_forward | Layer normalization forward propagation primitive |
| layer_normalization_backward | Layer normalization backward propagation primitive |
| inner_product_forward | Inner product forward propagation primitive |
| inner_product_backward_data | Inner product backward propagation primitive |
| inner_product_backward_weights | Inner product weights gradient primitive |
| rnn_primitive_desc_base | Base class for primitive descriptors for RNN primitives |
| vanilla_rnn_forward | Vanilla RNN forward propagation primitive |
| vanilla_rnn_backward | Vanilla RNN backward propagation primitive |
| lstm_forward | LSTM forward propagation primitive |
| lstm_backward | LSTM backward propagation primitive |
| gru_forward | GRU forward propagation primitive |
| gru_backward | GRU backward propagation primitive |
| lbr_gru_forward | LBR GRU forward propagation primitive |
| lbr_gru_backward | LBR GRU backward propagation primitive |
| shuffle_forward | Shuffle forward propagation primitive |
| shuffle_backward | Shuffle backward propagation primitive |
| binary | Elementwise binary operator primitive |
| matmul | Matrix multiplication (matmul) primitive |
| resampling_forward | Resampling forward propagation |
| resampling_backward | Resampling backward propagation primitive |
 threadpool_iface | Abstract threadpool interface |
| dnnl_batch_normalization_desc_t | A descriptor of a Batch Normalization operation |
| dnnl_binary_desc_t | A descriptor of a binary operation |
| dnnl_blocking_desc_t | Generic description of blocked data layout for most memory formats |
| dnnl_convolution_desc_t | A descriptor of a convolution operation |
| dnnl_eltwise_desc_t | A descriptor of a element-wise operation |
| dnnl_engine | An opaque structure to describe an engine |
| dnnl_exec_arg_t | A structure that contains an index and a memory object, and is used to pass arguments to dnnl_primitive_execute() |
| dnnl_inner_product_desc_t | A descriptor of an inner product operation |
| dnnl_layer_normalization_desc_t | A descriptor of a Layer Normalization operation |
| dnnl_lrn_desc_t | A descriptor of a Local Response Normalization (LRN) operation |
| dnnl_matmul_desc_t | A descriptor of a matrix multiplication operation |
| dnnl_memory | An opaque structure to describe a memory |
| dnnl_memory_desc_t | Memory descriptor |
| dnnl_memory_extra_desc_t | Description of extra information stored in memory |
| dnnl_pooling_desc_t | A descriptor of a pooling operation |
| dnnl_post_ops | An opaque structure for a chain of post operations |
| dnnl_primitive | An opaque structure to describe a primitive |
| dnnl_primitive_attr | An opaque structure for primitive descriptor attributes |
| dnnl_primitive_desc | An opaque structure to describe a primitive descriptor |
| dnnl_primitive_desc_iterator | An opaque structure to describe a primitive descriptor iterator |
| dnnl_resampling_desc_t | A descriptor of resampling operation |
| dnnl_rnn_desc_t | A descriptor for an RNN operation |
| dnnl_rnn_packed_desc_t | Description of tensor of packed weights for rnn |
| dnnl_shuffle_desc_t | A descriptor of a shuffle operation |
| dnnl_softmax_desc_t | A descriptor of a Softmax operation |
| dnnl_stream | An opaque structure to describe an execution stream |
| dnnl_version_t | Structure containing version information as per Semantic Versioning |
| dnnl_wino_desc_t | Description of tensor of weights for winograd 2x3 convolution |
