Policy class: Model weight data types for convolutional layers. More...

#include <dcnnelements.hpp>

Inheritance diagram for dcnnasgn::conv_weight_policy< KSP, CSPI, CSPO, PP >:

Public Types
using	channel_in_tag
	Input channel tag.

using	channel_out_tag
	Output channel tag.

Data classes
Each data class is a tagged::tensor_class with statically sized dimensions determined by the sizing-policy arguments of this policy class template. The physical layout (order of indexes) of each tagged::tensor_class is determined by the permutation-policy argument.
using	weights_t = tagged::permute_tensor_class< typename PP::weights, float, kernel_height_tag, kernel_width_tag, tagged::co<channel_in_tag>, channel_out_tag>
	The tensor containing the weights of the convolution.

Public Types inherited from dcnnasgn::conv_weight_size_policy< KSP, CSPI, CSPO >
using	channel_in_tag = typename CSPI::channel_tag
	Input channel tag.

using	channel_out_tag = typename CSPO::channel_tag
	Output channel tag.

Additional Inherited Members
Static Public Attributes inherited from dcnnasgn::conv_weight_size_policy< KSP, CSPI, CSPO >
static constexpr auto	cir = CSPI::cr
	Input channel range.

static constexpr auto	cor = CSPO::cr
	Output channel range.

Detailed Description

template<typename KSP, typename CSPI, typename CSPO, is_policy PP>
struct dcnnasgn::conv_weight_policy< KSP, CSPI, CSPO, PP >

Policy class: Model weight data types for convolutional layers.

Template Parameters

KSP
CSPI
CSPO
PP	Permutation policy

Member Typedef Documentation

◆ weights_t

template<typename KSP, typename CSPI, typename CSPO, is_policy PP>

using dcnnasgn::conv_weight_policy< KSP, CSPI, CSPO, PP >::weights_t = tagged::permute_tensor_class< typename PP::weights, float, kernel_height_tag, kernel_width_tag, tagged::co<channel_in_tag>, channel_out_tag>

The tensor containing the weights of the convolution.

The input channel tag is modified by the tagged::co prefix to distinguish it from the output channel tag (which may be otherwise identical). This co-tagging is also consistent with the meaning of the tensor as a transformation from input channels to output channels.

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

asgn/dcnnelements.hpp

Public Types

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ weights_t