Descriptor for a vanilla RNN backward propagation primitive. More...

#include <dnnl.hpp>

Collaboration diagram for dnnl::vanilla_rnn_backward::desc:

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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, 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

Descriptor for a vanilla RNN backward propagation primitive.

Constructor & Destructor Documentation

dnnl::vanilla_rnn_backward::desc::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,
		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 following arguments 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.

Note: All the memory descriptors may be initialized with the dnnl::memory::format_tag::any value of format_tag.

Parameters

aprop_kind	Propagation kind. Must be dnnl::prop_kind::backward.
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.
diff_src_layer_desc	Memory descriptor for the diff of input vector.
diff_src_iter_desc	Memory descriptor for the diff of input recurrent hidden state vector.
diff_weights_layer_desc	Memory descriptor for the diff of weights applied to the layer input.
diff_weights_iter_desc	Memory descriptor for the diff of weights applied to the recurrent input.
diff_bias_desc	Diff bias memory descriptor.
diff_dst_layer_desc	Memory descriptor for the diff of output vector.
diff_dst_iter_desc	Memory descriptor for the diff of output recurrent hidden state vector.
flags	Unused.
alpha	Negative slope if activation is dnnl::algorithm::eltwise_relu.
beta	Unused.

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