Descriptor for a vanilla RNN forward propagation primitive. More...
#include <dnnl.hpp>
Public Member Functions | |
desc (prop_kind aprop_kind, algorithm activation, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, rnn_flags flags=rnn_flags::undef, float alpha=0.0f, float beta=0.0f) | |
Constructs a descriptor for a vanilla RNN forward propagation primitive. More... | |
Descriptor for a vanilla RNN forward propagation primitive.
|
inline |
Constructs a descriptor for a vanilla RNN forward propagation primitive.
The following arguments may point to a zero memory descriptor:
src_iter_desc
,bias_desc
,dst_iter_desc
.This would then indicate that the RNN forward propagation primitive should not use them and should default to zero values instead.
src_iter_desc
can be initialized with an dnnl::memory::format_tag::any value of format_tag
.aprop_kind | Propagation kind. Possible values are dnnl::prop_kind::forward_training, and dnnl::prop_kind::forward_inference. |
activation | Activation kind. Possible values are dnnl::algorithm::eltwise_relu, dnnl::algorithm::eltwise_tanh, or dnnl::algorithm::eltwise_logistic. |
direction | RNN direction. See dnnl::rnn_direction for more info. |
src_layer_desc | Memory descriptor for the input vector. |
src_iter_desc | Memory descriptor for the input recurrent hidden state vector. |
weights_layer_desc | Memory descriptor for the weights applied to the layer input. |
weights_iter_desc | Memory descriptor for the weights applied to the recurrent input. |
bias_desc | Bias memory descriptor. |
dst_layer_desc | Memory descriptor for the output vector. |
dst_iter_desc | Memory descriptor for the output recurrent hidden state vector. |
flags | Unused. |
alpha | Negative slope if activation is dnnl::algorithm::eltwise_relu. |
beta | Unused. |