oneAPI Deep Neural Network Library (oneDNN)  1.4.0
Performance library for Deep Learning
Public Member Functions | List of all members
dnnl::vanilla_rnn_backward::desc Struct Reference

Vanilla RNN descriptor backward propagation primitive. More...

#include <dnnl.hpp>

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Public Member Functions

 desc (prop_kind prop_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, const memory::desc &diff_src_layer_desc, const memory::desc &diff_src_iter_desc, const memory::desc &diff_weights_layer_desc, const memory::desc &diff_weights_iter_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_layer_desc, const memory::desc &diff_dst_iter_desc, rnn_flags flags=rnn_flags::undef, float alpha=0.0f, float beta=0.0f)
 Constructs a descriptor for a vanilla RNN backward propagation primitive. More...
 

Detailed Description

Vanilla RNN descriptor backward propagation primitive.

Constructor & Destructor Documentation

◆ desc()

dnnl::vanilla_rnn_backward::desc::desc ( prop_kind  prop_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,
const memory::desc diff_src_layer_desc,
const memory::desc diff_src_iter_desc,
const memory::desc diff_weights_layer_desc,
const memory::desc diff_weights_iter_desc,
const memory::desc diff_bias_desc,
const memory::desc diff_dst_layer_desc,
const memory::desc diff_dst_iter_desc,
rnn_flags  flags = rnn_flags::undef,
float  alpha = 0.0f,
float  beta = 0.0f 
)
inline

Constructs a descriptor for a vanilla RNN backward propagation primitive.

The src_iter_desc together with diff_src_iter_desc, bias_desc together with diff_bias_desc, and dst_iter_desc together with diff_src_iter_desc, may point to a zero memory descriptor. This would then indicate that the RNN backward propagation primitive should not use the respective data and should use zero values instead.

Inputs:

Outputs:

Note
All the memory descriptors may be initialized with the dnnl::memory::format_tag::any value of format_tag.
Parameters
prop_kindPropagation kind. Must be dnnl::prop_kind::backward.
activationActivation kind. Possible values are dnnl::algorithm::eltwise_relu, dnnl::algorithm::eltwise_tanh, or dnnl::algorithm::eltwise_logistic.
directionRNN direction. See dnnl::rnn_direction for more info.
src_layer_descMemory descriptor for the input vector.
src_iter_descMemory descriptor for the input recurrent hidden state vector.
weights_layer_descMemory descriptor for the weights applied to the layer input.
weights_iter_descMemory descriptor for the weights applied to the recurrent input.
bias_descBias memory descriptor.
dst_layer_descMemory descriptor for the output vector.
dst_iter_descMemory descriptor for the output recurrent hidden state vector.
diff_src_layer_descMemory descriptor for the diff of input vector.
diff_src_iter_descMemory descriptor for the diff of input recurrent hidden state vector.
diff_weights_layer_descMemory descriptor for the diff of weights applied to the layer input.
diff_weights_iter_descMemory descriptor for the diff of weights applied to the recurrent input.
diff_bias_descDiff bias memory descriptor.
diff_dst_layer_descMemory descriptor for the diff of output vector.
diff_dst_iter_descMemory descriptor for the diff of output recurrent hidden state vector.
flagsUnused.
alphaNegative slope if activation is dnnl::algorithm::eltwise_relu.
betaUnused.

The documentation for this struct was generated from the following file: