Visible to Intel only — GUID: GUID-297EB1CB-DD17-42B1-8E87-EF04840A8706
Visible to Intel only — GUID: GUID-297EB1CB-DD17-42B1-8E87-EF04840A8706
struct dnnl::deconvolution_backward_weights::primitive_desc
Overview
Primitive descriptor for a deconvolution weights gradient primitive. More…
#include <dnnl.hpp> struct primitive_desc: public dnnl::primitive_desc { // construction primitive_desc(); primitive_desc( const engine& aengine, algorithm aalgorithm, const memory::desc& src_desc, const memory::desc& diff_weights_desc, const memory::desc& diff_bias_desc, const memory::desc& diff_dst_desc, const memory::dims& strides, const memory::dims& padding_l, const memory::dims& padding_r, const deconvolution_forward::primitive_desc& hint_fwd_pd, const primitive_attr& attr = default_attr(), bool allow_empty = false ); primitive_desc( const engine& aengine, algorithm aalgorithm, const memory::desc& src_desc, const memory::desc& diff_weights_desc, const memory::desc& diff_dst_desc, const memory::dims& strides, const memory::dims& padding_l, const memory::dims& padding_r, const deconvolution_forward::primitive_desc& hint_fwd_pd, const primitive_attr& attr = default_attr(), bool allow_empty = false ); primitive_desc( const engine& aengine, algorithm aalgorithm, const memory::desc& src_desc, const memory::desc& diff_weights_desc, const memory::desc& diff_bias_desc, const memory::desc& diff_dst_desc, const memory::dims& strides, const memory::dims& dilates, const memory::dims& padding_l, const memory::dims& padding_r, const deconvolution_forward::primitive_desc& hint_fwd_pd, const primitive_attr& attr = default_attr(), bool allow_empty = false ); primitive_desc( const engine& aengine, algorithm aalgorithm, const memory::desc& src_desc, const memory::desc& diff_weights_desc, const memory::desc& diff_dst_desc, const memory::dims& strides, const memory::dims& dilates, const memory::dims& padding_l, const memory::dims& padding_r, const deconvolution_forward::primitive_desc& hint_fwd_pd, const primitive_attr& attr = default_attr(), bool allow_empty = false ); primitive_desc(dnnl_primitive_desc_t pd); // methods memory::desc src_desc() const; memory::desc diff_weights_desc() const; memory::desc diff_dst_desc() const; memory::desc diff_bias_desc() const; algorithm get_algorithm() const; prop_kind get_prop_kind() const; memory::dims get_strides() const; memory::dims get_dilations() const; memory::dims get_padding_l() const; memory::dims get_padding_r() const; };
Inherited Members
public: // methods handle<T, traits>& operator = (const handle<T, traits>&); handle<T, traits>& operator = (handle<T, traits>&&); void reset(T t, bool weak = false); T get(bool allow_empty = false) const; operator T () const; operator bool () const; bool operator == (const handle<T, traits>& other) const; bool operator != (const handle& other) const; engine get_engine() const; const char* impl_info_str() const; memory::dim query_s64(query what) const; memory::dims get_strides() const; memory::dims get_dilations() const; memory::dims get_padding_l() const; memory::dims get_padding_r() const; float get_epsilon() const; template <typename T = unsigned> T get_flags() const; dnnl::algorithm get_algorithm() const; float get_alpha() const; float get_beta() const; int get_axis() const; memory::dim get_local_size() const; float get_k() const; float get_p() const; std::vector<float> get_factors() const; dnnl::algorithm get_cell_kind() const; dnnl::rnn_direction get_direction() const; dnnl::algorithm get_activation_kind() const; memory::dims get_kernel() const; memory::dim get_group_size() const; dnnl::prop_kind get_prop_kind() const; memory::desc query_md(query what, int idx = 0) const; memory::desc src_desc(int idx) const; memory::desc dst_desc(int idx) const; memory::desc weights_desc(int idx) const; memory::desc diff_src_desc(int idx) const; memory::desc diff_dst_desc(int idx) const; memory::desc diff_weights_desc(int idx) const; memory::desc src_desc() const; memory::desc dst_desc() const; memory::desc weights_desc() const; memory::desc diff_src_desc() const; memory::desc diff_dst_desc() const; memory::desc diff_weights_desc() const; memory::desc workspace_desc() const; memory::desc scratchpad_desc() const; engine scratchpad_engine() const; primitive_attr get_primitive_attr() const; dnnl::primitive::kind get_kind() const; std::vector<uint8_t> get_cache_blob_id() const; bool next_impl(); primitive_desc_base(); primitive_desc_base(dnnl_primitive_desc_t pd, dnnl::primitive::kind prim_kind); primitive_desc_base( dnnl_primitive_desc_t pd, dnnl::primitive::kind prim_kind, dnnl::prop_kind aprop_kind ); primitive_desc_base( dnnl_primitive_desc_t pd, dnnl::primitive::kind prim_kind, dnnl::prop_kind prop_kind1, dnnl::prop_kind prop_kind2 );
Detailed Documentation
Primitive descriptor for a deconvolution weights gradient primitive.
Construction
primitive_desc()
Default constructor. Produces an empty object.
primitive_desc( const engine& aengine, algorithm aalgorithm, const memory::desc& src_desc, const memory::desc& diff_weights_desc, const memory::desc& diff_bias_desc, const memory::desc& diff_dst_desc, const memory::dims& strides, const memory::dims& padding_l, const memory::dims& padding_r, const deconvolution_forward::primitive_desc& hint_fwd_pd, const primitive_attr& attr = default_attr(), bool allow_empty = false )
Constructs a primitive descriptor for a deconvolution weights gradient primitive with bias.
Arrays strides, padding_l, and padding_r contain values for spatial dimensions only and hence must have the same number of elements as there are spatial dimensions. The order of values is the same as in the tensor: depth (for 3D tensors), height (for 3D and 2D tensors), and width.
Parameters:
aengine |
Engine to use. |
aalgorithm |
Deconvolution algorithm. Possible values are dnnl::algorithm::deconvolution_direct, and dnnl::algorithm::deconvolution_winograd. |
src_desc |
Source memory descriptor. |
diff_weights_desc |
Diff weights memory descriptor. |
diff_bias_desc |
Diff bias memory descriptor. Passing zero memory descriptor disables the bias term. |
diff_dst_desc |
Diff destination memory descriptor. |
strides |
Strides for each spatial dimension. |
padding_l |
Vector of padding values for low indices for each spatial dimension ([[front,] top,] left). |
padding_r |
Vector of padding values for high indices for each spatial dimension ([[back,] bottom,] right). |
hint_fwd_pd |
Primitive descriptor for a deconvolution forward propagation primitive. It is used as a hint for deciding which memory format to use. |
attr |
Primitive attributes to use. Attributes are optional and default to empty attributes. |
allow_empty |
A flag signifying whether construction is allowed to fail without throwing an exception. In this case an empty object will be produced. This flag is optional and defaults to false. |
primitive_desc( const engine& aengine, algorithm aalgorithm, const memory::desc& src_desc, const memory::desc& diff_weights_desc, const memory::desc& diff_dst_desc, const memory::dims& strides, const memory::dims& padding_l, const memory::dims& padding_r, const deconvolution_forward::primitive_desc& hint_fwd_pd, const primitive_attr& attr = default_attr(), bool allow_empty = false )
Constructs a primitive descriptor for a deconvolution weights gradient primitive without bias.
Arrays strides, padding_l, and padding_r contain values for spatial dimensions only and hence must have the same number of elements as there are spatial dimensions. The order of values is the same as in the tensor: depth (for 3D tensors), height (for 3D and 2D tensors), and width.
Parameters:
aengine |
Engine to use. |
aalgorithm |
Deconvolution algorithm. Possible values are dnnl::algorithm::deconvolution_direct, and dnnl::algorithm::deconvolution_winograd. |
src_desc |
Source memory descriptor. |
diff_weights_desc |
Diff weights memory descriptor. |
diff_dst_desc |
Diff destination memory descriptor. |
strides |
Strides for each spatial dimension. |
padding_l |
Vector of padding values for low indices for each spatial dimension ([[front,] top,] left). |
padding_r |
Vector of padding values for high indices for each spatial dimension ([[back,] bottom,] right). |
hint_fwd_pd |
Primitive descriptor for a deconvolution forward propagation primitive. It is used as a hint for deciding which memory format to use. |
attr |
Primitive attributes to use. Attributes are optional and default to empty attributes. |
allow_empty |
A flag signifying whether construction is allowed to fail without throwing an exception. In this case an empty object will be produced. This flag is optional and defaults to false. |
primitive_desc( const engine& aengine, algorithm aalgorithm, const memory::desc& src_desc, const memory::desc& diff_weights_desc, const memory::desc& diff_bias_desc, const memory::desc& diff_dst_desc, const memory::dims& strides, const memory::dims& dilates, const memory::dims& padding_l, const memory::dims& padding_r, const deconvolution_forward::primitive_desc& hint_fwd_pd, const primitive_attr& attr = default_attr(), bool allow_empty = false )
Constructs a primitive descriptor for a deconvolution weights gradient primitive with bias.
Arrays strides, dilates, padding_l, and padding_r contain values for spatial dimensions only and hence must have the same number of elements as there are spatial dimensions. The order of values is the same as in the tensor: depth (for 3D tensors), height (for 3D and 2D tensors), and width.
Parameters:
aengine |
Engine to use. |
aalgorithm |
Deconvolution algorithm. Possible values are dnnl::algorithm::deconvolution_direct, and dnnl::algorithm::deconvolution_winograd. |
src_desc |
Source memory descriptor. |
diff_weights_desc |
Diff weights memory descriptor. |
diff_bias_desc |
Diff bias memory descriptor. Passing zero memory descriptor disables the bias term. |
diff_dst_desc |
Diff destination memory descriptor. |
strides |
Strides for each spatial dimension. |
dilates |
Dilations for each spatial dimension. A zero value means no dilation in the corresponding dimension. |
padding_l |
Vector of padding values for low indices for each spatial dimension ([[front,] top,] left). |
padding_r |
Vector of padding values for high indices for each spatial dimension ([[back,] bottom,] right). |
hint_fwd_pd |
Primitive descriptor for a deconvolution forward propagation primitive. It is used as a hint for deciding which memory format to use. |
attr |
Primitive attributes to use. Attributes are optional and default to empty attributes. |
allow_empty |
A flag signifying whether construction is allowed to fail without throwing an exception. In this case an empty object will be produced. This flag is optional and defaults to false. |
primitive_desc( const engine& aengine, algorithm aalgorithm, const memory::desc& src_desc, const memory::desc& diff_weights_desc, const memory::desc& diff_dst_desc, const memory::dims& strides, const memory::dims& dilates, const memory::dims& padding_l, const memory::dims& padding_r, const deconvolution_forward::primitive_desc& hint_fwd_pd, const primitive_attr& attr = default_attr(), bool allow_empty = false )
Constructs a primitive descriptor for a deconvolution weights gradient primitive without bias.
Arrays strides, dilates, padding_l, and padding_r contain values for spatial dimensions only and hence must have the same number of elements as there are spatial dimensions. The order of values is the same as in the tensor: depth (for 3D tensors), height (for 3D and 2D tensors), and width.
Parameters:
aengine |
Engine to use. |
aalgorithm |
Deconvolution algorithm. Possible values are dnnl::algorithm::deconvolution_direct, and dnnl::algorithm::deconvolution_winograd. |
src_desc |
Source memory descriptor. |
diff_weights_desc |
Diff weights memory descriptor. |
diff_dst_desc |
Diff destination memory descriptor. |
strides |
Strides for each spatial dimension. |
dilates |
Dilations for each spatial dimension. A zero value means no dilation in the corresponding dimension. |
padding_l |
Vector of padding values for low indices for each spatial dimension ([[front,] top,] left). |
padding_r |
Vector of padding values for high indices for each spatial dimension ([[back,] bottom,] right). |
hint_fwd_pd |
Primitive descriptor for a deconvolution forward propagation primitive. It is used as a hint for deciding which memory format to use. |
attr |
Primitive attributes to use. Attributes are optional and default to empty attributes. |
allow_empty |
A flag signifying whether construction is allowed to fail without throwing an exception. In this case an empty object will be produced. This flag is optional and defaults to false. |
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a deconvolution weights gradient primitive from a C API primitive descriptor that must have a matching kind.
Parameters:
pd |
C API primitive descriptor for a deconvolution weights gradient primitive. |
Methods
memory::desc src_desc() const
Returns a source memory descriptor.
Returns:
Source memory descriptor.
A zero memory descriptor if the primitive does not have a source parameter.
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Returns:
Diff weights memory descriptor.
A zero memory descriptor if the primitive does not have a diff weights parameter.
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Returns:
Diff destination memory descriptor.
A zero memory descriptor if the primitive does not have a diff destination parameter.
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Returns:
The diff bias memory descriptor.
A zero memory descriptor of the primitive does not have a diff bias parameter.
algorithm get_algorithm() const
Returns an algorithm kind.
Returns:
An algorithm kind.
dnnl::algorithm::undef if the primitive does not have an algorithm parameter.
prop_kind get_prop_kind() const
Returns a propagation kind.
Returns:
A propagation kind.
dnnl::prop_kind::undef if the primitive does not have a propagation parameter.
memory::dims get_strides() const
Returns strides.
Returns:
Strides.
An empty dnnl::memory::dims if the primitive does not have a strides parameter.
memory::dims get_dilations() const
Returns dilations.
Returns:
Dilations.
An empty dnnl::memory::dims if the primitive does not have a dilations parameter.
memory::dims get_padding_l() const
Returns a left padding.
Returns:
A left padding.
An empty dnnl::memory::dims if the primitive does not have a left padding parameter.
memory::dims get_padding_r() const
Returns a right padding.
Returns:
A right padding.
An empty dnnl::memory::dims if the primitive does not have a right padding parameter.