Pooling

Intel® oneAPI Deep Neural Network Developer Guide and Reference

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ID 768875

Date 6/20/2024

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Pooling

Overview

A primitive to perform max or average pooling with dilation. More…

// structs

struct dnnl::pooling_backward;
struct dnnl::pooling_forward;

// global functions

dnnl_status_t DNNL_API dnnl_pooling_forward_primitive_desc_create(
    dnnl_primitive_desc_t* primitive_desc,
    dnnl_engine_t engine,
    dnnl_prop_kind_t prop_kind,
    dnnl_alg_kind_t alg_kind,
    const_dnnl_memory_desc_t src_desc,
    const_dnnl_memory_desc_t dst_desc,
    const dnnl_dims_t strides,
    const dnnl_dims_t kernel,
    const dnnl_dims_t dilation,
    const dnnl_dims_t padding_l,
    const dnnl_dims_t padding_r,
    const_dnnl_primitive_attr_t attr
    );

dnnl_status_t DNNL_API dnnl_pooling_backward_primitive_desc_create(
    dnnl_primitive_desc_t* primitive_desc,
    dnnl_engine_t engine,
    dnnl_alg_kind_t alg_kind,
    const_dnnl_memory_desc_t diff_src_desc,
    const_dnnl_memory_desc_t diff_dst_desc,
    const dnnl_dims_t strides,
    const dnnl_dims_t kernel,
    const dnnl_dims_t dilation,
    const dnnl_dims_t padding_l,
    const dnnl_dims_t padding_r,
    const_dnnl_primitive_desc_t hint_fwd_pd,
    const_dnnl_primitive_attr_t attr
    );

Detailed Documentation

A primitive to perform max or average pooling with dilation.

See also:

Pooling in developer guide

Global Functions

dnnl_status_t DNNL_API dnnl_pooling_forward_primitive_desc_create(
    dnnl_primitive_desc_t* primitive_desc,
    dnnl_engine_t engine,
    dnnl_prop_kind_t prop_kind,
    dnnl_alg_kind_t alg_kind,
    const_dnnl_memory_desc_t src_desc,
    const_dnnl_memory_desc_t dst_desc,
    const dnnl_dims_t strides,
    const dnnl_dims_t kernel,
    const dnnl_dims_t dilation,
    const dnnl_dims_t padding_l,
    const dnnl_dims_t padding_r,
    const_dnnl_primitive_attr_t attr
    )

Creates a primitive descriptor for a pooling forward propagation primitive.

Arrays strides, kernel, dilation, 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:

primitive_desc	Output primitive descriptor.
engine	Engine to use.
prop_kind	Propagation kind. Possible values are dnnl_forward_training and dnnl_forward_inference.
alg_kind	Pooling algorithm kind: either dnnl_pooling_max, dnnl_pooling_avg_include_padding, or dnnl_pooling_avg_exclude_padding.
src_desc	Source memory descriptor.
dst_desc	Destination memory descriptor.
strides	Array of strides for spatial dimension.
kernel	Array of kernel spatial dimensions.
dilation	Array of dilations 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.
attr	Primitive attributes (can be NULL).

Returns:

dnnl_success on success and a status describing the error otherwise.

dnnl_status_t DNNL_API dnnl_pooling_backward_primitive_desc_create(
    dnnl_primitive_desc_t* primitive_desc,
    dnnl_engine_t engine,
    dnnl_alg_kind_t alg_kind,
    const_dnnl_memory_desc_t diff_src_desc,
    const_dnnl_memory_desc_t diff_dst_desc,
    const dnnl_dims_t strides,
    const dnnl_dims_t kernel,
    const dnnl_dims_t dilation,
    const dnnl_dims_t padding_l,
    const dnnl_dims_t padding_r,
    const_dnnl_primitive_desc_t hint_fwd_pd,
    const_dnnl_primitive_attr_t attr
    )

Creates a primitive descriptor for a pooling backward propagation primitive.

Parameters:

primitive_desc	Output primitive descriptor.
engine	Engine to use.
alg_kind	Pooling algorithm kind: either dnnl_pooling_max, dnnl_pooling_avg_include_padding, or dnnl_pooling_avg_exclude_padding.
diff_src_desc	Diff source memory descriptor.
diff_dst_desc	Diff destination memory descriptor.
strides	Array of strides for spatial dimension.
kernel	Array of kernel spatial dimensions.
dilation	Array of dilations 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.
hint_fwd_pd	Primitive descriptor for a respective forward propagation primitive.
attr	Primitive attributes (can be NULL).

Returns:

dnnl_success on success and a status describing the error otherwise.

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Intel® oneAPI Deep Neural Network Developer Guide and Reference

Pooling

Overview

Detailed Documentation