Deconvolution

A primitive to perform 1D, 2D or 3D deconvolution. More...

Classes
struct	dnnl::deconvolution_forward
	Deconvolution forward propagation primitive. More...
struct	dnnl::deconvolution_backward_data
	Deconvolution backward propagation primitive. More...
struct	dnnl::deconvolution_backward_weights
	Deconvolution weights gradient primitive. More...

Typedefs
typedef dnnl_convolution_desc_t	dnnl_deconvolution_desc_t
	A descriptor of a deconvolution operation.

Functions
dnnl_status_t DNNL_API	dnnl_deconvolution_forward_desc_init (dnnl_deconvolution_desc_t *deconv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
	Initializes a descriptor for a deconvolution forward propagation primitive. More...
dnnl_status_t DNNL_API	dnnl_dilated_deconvolution_forward_desc_init (dnnl_deconvolution_desc_t *deconv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
	Initializes a descriptor for a dilated deconvolution forward propagation primitive. More...
dnnl_status_t DNNL_API	dnnl_deconvolution_backward_data_desc_init (dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
	Initializes a descriptor for a deconvolution backward propagation primitive. More...
dnnl_status_t DNNL_API	dnnl_dilated_deconvolution_backward_data_desc_init (dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
	Initializes a descriptor for a dilated deconvolution backward propagation primitive. More...
dnnl_status_t DNNL_API	dnnl_deconvolution_backward_weights_desc_init (dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
	Initializes a descriptor for a deconvolution weights gradient primitive. More...
dnnl_status_t DNNL_API	dnnl_dilated_deconvolution_backward_weights_desc_init (dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
	Initializes a descriptor for a dilated deconvolution weights gradient primitive. More...

Detailed Description

A primitive to perform 1D, 2D or 3D deconvolution.

Supported variants are forward propagation, backward propagation, and weights gradient with or without bias.

Function Documentation

dnnl_deconvolution_forward_desc_init()

dnnl_status_t DNNL_API dnnl_deconvolution_forward_desc_init	(	dnnl_deconvolution_desc_t *	deconv_desc,
		dnnl_prop_kind_t	prop_kind,
		dnnl_alg_kind_t	alg_kind,
		const dnnl_memory_desc_t *	src_desc,
		const dnnl_memory_desc_t *	weights_desc,
		const dnnl_memory_desc_t *	bias_desc,
		const dnnl_memory_desc_t *	dst_desc,
		const dnnl_dims_t	strides,
		const dnnl_dims_t	padding_l,
		const dnnl_dims_t	padding_r
	)

Initializes a descriptor for a deconvolution forward propagation primitive.

Note

Memory descriptors can be initialized with dnnl_format_tag_any or with format_kind set to dnnl_format_kind_any.

Inputs:

• src (dnnl_query_src_md, 0)
• weights (dnnl_query_weights_md, 0)
• bias (dnnl_query_weights_md, 1), if created with bias

Outputs:

• dst (dnnl_query_dst_md, 0)

Parameters

deconv_desc	Output descriptor for a deconvolution primitive.
prop_kind	Propagation kind. Possible values are dnnl_forward_training and dnnl_forward_inference.
alg_kind	Deconvolution algorithm. Possible values are dnnl_deconvolution_direct, dnnl_deconvolution_winograd.
src_desc	Source memory descriptor.
weights_desc	Weights memory descriptor.
bias_desc	Bias memory descriptor. Passing NULL, a zero memory descriptor, or a memory descriptor with format_kind set to dnnl_format_kind_undef disables the bias term.
dst_desc	Destination memory descriptor.
strides	Array of strides for spatial dimension.
padding_l	Array of padding values for low indices for each spatial dimension (front, top, left).
padding_r	Array of padding values for high indices for each spatial dimension (back, bottom, right). Can be NULL in which case padding is considered to be symmetrical.

Returns

dnnl_success on success and a status describing the error otherwise.

dnnl_dilated_deconvolution_forward_desc_init()

dnnl_status_t DNNL_API dnnl_dilated_deconvolution_forward_desc_init	(	dnnl_deconvolution_desc_t *	deconv_desc,
		dnnl_prop_kind_t	prop_kind,
		dnnl_alg_kind_t	alg_kind,
		const dnnl_memory_desc_t *	src_desc,
		const dnnl_memory_desc_t *	weights_desc,
		const dnnl_memory_desc_t *	bias_desc,
		const dnnl_memory_desc_t *	dst_desc,
		const dnnl_dims_t	strides,
		const dnnl_dims_t	dilates,
		const dnnl_dims_t	padding_l,
		const dnnl_dims_t	padding_r
	)

Initializes a descriptor for a dilated deconvolution forward propagation primitive.

Note

Memory descriptors can be initialized with dnnl_format_tag_any or with format_kind set to dnnl_format_kind_any.

Inputs:

• src (dnnl_query_src_md, 0)
• weights (dnnl_query_weights_md, 0)
• bias (dnnl_query_weights_md, 1), if created with bias

Outputs:

• dst (dnnl_query_dst_md, 0)

Parameters

deconv_desc	Output descriptor for a deconvolution primitive.
prop_kind	Propagation kind. Possible values are dnnl_forward_training and dnnl_forward_inference.
alg_kind	Deconvolution algorithm. Possible values are dnnl_deconvolution_direct, dnnl_deconvolution_winograd.
src_desc	Source memory descriptor.
weights_desc	Weights memory descriptor.
bias_desc	Bias memory descriptor. Passing NULL, a zero memory descriptor, or a memory descriptor with format_kind set to dnnl_format_kind_undef disables the bias term.
dst_desc	Destination memory descriptor.
strides	Array of strides for spatial dimension.
dilates	Array of dilations for spatial dimension. A zero value means no dilation in the corresponding dimension.
padding_l	Array of padding values for low indices for each spatial dimension (front, top, left).
padding_r	Array of padding values for high indices for each spatial dimension (back, bottom, right). Can be NULL in which case padding is considered to be symmetrical.

Returns

dnnl_success on success and a status describing the error otherwise.

dnnl_deconvolution_backward_data_desc_init()

dnnl_status_t DNNL_API dnnl_deconvolution_backward_data_desc_init	(	dnnl_deconvolution_desc_t *	deconv_desc,
		dnnl_alg_kind_t	alg_kind,
		const dnnl_memory_desc_t *	diff_src_desc,
		const dnnl_memory_desc_t *	weights_desc,
		const dnnl_memory_desc_t *	diff_dst_desc,
		const dnnl_dims_t	strides,
		const dnnl_dims_t	padding_l,
		const dnnl_dims_t	padding_r
	)

Initializes a descriptor for a deconvolution backward propagation primitive.

Note

Memory descriptors can be initialized with dnnl_format_tag_any or with format_kind set to dnnl_format_kind_any.

Inputs:

• diff_dst (dnnl_query_diff_dst_md, 0)
• weights (dnnl_query_weights_md, 0)

Outputs:

• diff_src (dnnl_query_diff_src_md, 0)

Parameters

deconv_desc	Output descriptor for a deconvolution primitive.
alg_kind	Deconvolution algorithm. Possible values are dnnl_deconvolution_direct, dnnl_deconvolution_winograd.
diff_src_desc	Diff source memory descriptor.
weights_desc	Weights memory descriptor.
diff_dst_desc	Diff destination memory descriptor.
strides	Array of strides for spatial dimension.
padding_l	Array of padding values for low indices for each spatial dimension (front, top, left).
padding_r	Array of padding values for high indices for each spatial dimension (back, bottom, right). Can be NULL in which case padding is considered to be symmetrical.

Returns

dnnl_success on success and a status describing the error otherwise.

dnnl_dilated_deconvolution_backward_data_desc_init()

dnnl_status_t DNNL_API dnnl_dilated_deconvolution_backward_data_desc_init	(	dnnl_deconvolution_desc_t *	deconv_desc,
		dnnl_alg_kind_t	alg_kind,
		const dnnl_memory_desc_t *	diff_src_desc,
		const dnnl_memory_desc_t *	weights_desc,
		const dnnl_memory_desc_t *	diff_dst_desc,
		const dnnl_dims_t	strides,
		const dnnl_dims_t	dilates,
		const dnnl_dims_t	padding_l,
		const dnnl_dims_t	padding_r
	)

Initializes a descriptor for a dilated deconvolution backward propagation primitive.

Note

Memory descriptors can be initialized with dnnl_format_tag_any or with format_kind set to dnnl_format_kind_any.

Inputs:

• diff_dst (dnnl_query_diff_dst_md, 0)
• weights (dnnl_query_weights_md, 0)

Outputs:

• diff_src (dnnl_query_diff_src_md, 0)

Parameters

deconv_desc	Output descriptor for a deconvolution primitive.
alg_kind	Deconvolution algorithm. Possible values are dnnl_deconvolution_direct, dnnl_deconvolution_winograd.
diff_src_desc	Diff source memory descriptor.
weights_desc	Weights memory descriptor.
diff_dst_desc	Diff destination memory descriptor.
strides	Array of strides for spatial dimension.
dilates	Array of dilations for spatial dimension. A zero value means no dilation in the corresponding dimension.
padding_l	Array of padding values for low indices for each spatial dimension (front, top, left).
padding_r	Array of padding values for high indices for each spatial dimension (back, bottom, right). Can be NULL in which case padding is considered to be symmetrical.

Returns

dnnl_success on success and a status describing the error otherwise.

dnnl_deconvolution_backward_weights_desc_init()

dnnl_status_t DNNL_API dnnl_deconvolution_backward_weights_desc_init	(	dnnl_deconvolution_desc_t *	deconv_desc,
		dnnl_alg_kind_t	alg_kind,
		const dnnl_memory_desc_t *	src_desc,
		const dnnl_memory_desc_t *	diff_weights_desc,
		const dnnl_memory_desc_t *	diff_bias_desc,
		const dnnl_memory_desc_t *	diff_dst_desc,
		const dnnl_dims_t	strides,
		const dnnl_dims_t	padding_l,
		const dnnl_dims_t	padding_r
	)

Initializes a descriptor for a deconvolution weights gradient primitive.

Note

Memory descriptors can be initialized with dnnl_format_tag_any or with format_kind set to dnnl_format_kind_any.

Inputs:

• src (dnnl_query_src_md, 0)
• diff_dst (dnnl_query_diff_dst_md, 0)

Outputs:

• diff_weights (dnnl_query_diff_weights_md, 0)
• diff_bias (dnnl_query_diff_weights_md, 1), if created with bias

Parameters

deconv_desc	Output descriptor for a deconvolution primitive.
alg_kind	Deconvolution algorithm. Possible values are dnnl_deconvolution_direct, dnnl_deconvolution_winograd.
src_desc	Source memory descriptor.
diff_weights_desc	Diff weights memory descriptor.
diff_bias_desc	Diff bias memory descriptor. Passing NULL, a zero memory descriptor, or a memory descriptor with format_kind set to dnnl_format_kind_undef disables the bias term.
diff_dst_desc	Diff destination memory descriptor.
strides	Array of strides for spatial dimension.
padding_l	Array of padding values for low indices for each spatial dimension (front, top, left).
padding_r	Array of padding values for high indices for each spatial dimension (back, bottom, right). Can be NULL in which case padding is considered to be symmetrical.

Returns

dnnl_success on success and a status describing the error otherwise.

dnnl_dilated_deconvolution_backward_weights_desc_init()

dnnl_status_t DNNL_API dnnl_dilated_deconvolution_backward_weights_desc_init	(	dnnl_deconvolution_desc_t *	deconv_desc,
		dnnl_alg_kind_t	alg_kind,
		const dnnl_memory_desc_t *	src_desc,
		const dnnl_memory_desc_t *	diff_weights_desc,
		const dnnl_memory_desc_t *	diff_bias_desc,
		const dnnl_memory_desc_t *	diff_dst_desc,
		const dnnl_dims_t	strides,
		const dnnl_dims_t	dilates,
		const dnnl_dims_t	padding_l,
		const dnnl_dims_t	padding_r
	)

Initializes a descriptor for a dilated deconvolution weights gradient primitive.

Note

Memory descriptors can be initialized with dnnl_format_tag_any or with format_kind set to dnnl_format_kind_any.

Inputs:

• src (dnnl_query_src_md, 0)
• diff_dst (dnnl_query_diff_dst_md, 0)

Outputs:

• diff_weights (dnnl_query_diff_weights_md, 0)
• diff_bias (dnnl_query_diff_weights_md, 1), if created with bias

Parameters

deconv_desc	Output descriptor for a deconvolution primitive.
alg_kind	Deconvolution algorithm. Possible values are dnnl_deconvolution_direct, dnnl_deconvolution_winograd.
src_desc	Source memory descriptor.
diff_weights_desc	Diff weights memory descriptor.
diff_bias_desc	Diff bias memory descriptor. Passing NULL, a zero memory descriptor, or a memory descriptor with format_kind set to dnnl_format_kind_undef disables the bias term.
diff_dst_desc	Diff destination memory descriptor.
strides	Array of strides for spatial dimension.
dilates	Array of dilations for spatial dimension. A zero value means no dilation in the corresponding dimension.
padding_l	Array of padding values for low indices for each spatial dimension (front, top, left).
padding_r	Array of padding values for high indices for each spatial dimension (back, bottom, right). Can be NULL in which case padding is considered to be symmetrical.

Returns

dnnl_success on success and a status describing the error otherwise.