Batch Normalization

Intel® oneAPI Deep Neural Network Developer Guide and Reference

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ID 768875

Date 12/16/2022

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Batch Normalization

Overview

A primitive to perform batch normalization. More…

// structs

struct dnnl::batch_normalization_backward;
struct dnnl::batch_normalization_forward;

// global functions

dnnl_status_t DNNL_API dnnl_batch_normalization_forward_primitive_desc_create(
    dnnl_primitive_desc_t* primitive_desc,
    dnnl_engine_t engine,
    dnnl_prop_kind_t prop_kind,
    const_dnnl_memory_desc_t src_desc,
    const_dnnl_memory_desc_t dst_desc,
    float epsilon,
    unsigned flags,
    const_dnnl_primitive_attr_t attr
    );

dnnl_status_t DNNL_API dnnl_batch_normalization_backward_primitive_desc_create(
    dnnl_primitive_desc_t* primitive_desc,
    dnnl_engine_t engine,
    dnnl_prop_kind_t prop_kind,
    const_dnnl_memory_desc_t diff_src_desc,
    const_dnnl_memory_desc_t diff_dst_desc,
    const_dnnl_memory_desc_t src_desc,
    float epsilon,
    unsigned flags,
    const_dnnl_primitive_desc_t hint_fwd_pd,
    const_dnnl_primitive_attr_t attr
    );

Detailed Documentation

A primitive to perform batch normalization.

Both forward and backward propagation primitives support in-place operation; that is, src and dst can refer to the same memory for forward propagation, and diff_dst and diff_src can refer to the same memory for backward propagation.

The batch normalization primitives computations can be controlled by specifying different dnnl::normalization_flags values. For example, batch normalization forward propagation can be configured to either compute the mean and variance or take them as arguments. It can either perform scaling and shifting using gamma and beta parameters or not. Optionally, it can also perform a fused ReLU, which in case of training would also require a workspace.

See also:

Batch Normalization in developer guide

Global Functions

dnnl_status_t DNNL_API dnnl_batch_normalization_forward_primitive_desc_create(
    dnnl_primitive_desc_t* primitive_desc,
    dnnl_engine_t engine,
    dnnl_prop_kind_t prop_kind,
    const_dnnl_memory_desc_t src_desc,
    const_dnnl_memory_desc_t dst_desc,
    float epsilon,
    unsigned flags,
    const_dnnl_primitive_attr_t attr
    )

Creates a primitive descriptor for a batch normalization forward propagation primitive.

NOTE:

In-place operation is supported: the dst can refer to the same memory as the src.

Parameters:

primitive_desc	Output primitive_descriptor.
engine	Engine to use.
prop_kind	Propagation kind. Possible values are dnnl_forward_training and dnnl_forward_inference.
src_desc	Source memory descriptor.
dst_desc	Destination memory descriptor.
epsilon	Batch normalization epsilon parameter.
flags	Batch normalization flags (dnnl_normalization_flags_t).
attr	Primitive attributes (can be NULL).

Returns:

dnnl_success on success and a status describing the error otherwise.

dnnl_status_t DNNL_API dnnl_batch_normalization_backward_primitive_desc_create(
    dnnl_primitive_desc_t* primitive_desc,
    dnnl_engine_t engine,
    dnnl_prop_kind_t prop_kind,
    const_dnnl_memory_desc_t diff_src_desc,
    const_dnnl_memory_desc_t diff_dst_desc,
    const_dnnl_memory_desc_t src_desc,
    float epsilon,
    unsigned flags,
    const_dnnl_primitive_desc_t hint_fwd_pd,
    const_dnnl_primitive_attr_t attr
    )

Creates a primitive descriptor for a batch normalization backward propagation primitive.

NOTE:

In-place operation is supported: the diff_dst can refer to the same memory as the diff_src.

Parameters:

primitive_desc	Output primitive_descriptor.
engine	Engine to use.
prop_kind	Propagation kind. Possible values are dnnl_backward_data and dnnl_backward (diffs for all parameters are computed in this case).
diff_src_desc	Diff source memory descriptor.
diff_dst_desc	Diff destination memory descriptor.
src_desc	Source memory descriptor.
epsilon	Batch normalization epsilon parameter.
flags	Batch normalization flags (dnnl_normalization_flags_t).
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

Batch Normalization

Overview

Detailed Documentation