org.bytedeco.dnnl.global

Enum dnnl.normalization_flags

java.lang.Object

java.lang.Enum<dnnl.normalization_flags>

org.bytedeco.dnnl.global.dnnl.normalization_flags

All Implemented Interfaces:

Serializable, Comparable<dnnl.normalization_flags>

Enclosing class:

dnnl

@Namespace(value="dnnl")
public static enum dnnl.normalization_flags
extends Enum<dnnl.normalization_flags>

\} dnnl_api_attributes

\addtogroup dnnl_api_primitives_common \{

Flags for normalization primitives.

Enum Constant Summary

Enum Constants

Enum Constant and Description
fuse_norm_relu Fuse normalization with ReLU.
none Use no normalization flags.
use_global_stats Use global statistics.
use_scale_shift Use scale and shift parameters.

Field Summary

Fields

Modifier and Type	Field and Description
int	value

Method Summary

Modifier and Type	Method and Description
dnnl.normalization_flags	intern()
String	toString()
static dnnl.normalization_flags	valueOf(String name) Returns the enum constant of this type with the specified name.
static dnnl.normalization_flags[]	values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods inherited from class java.lang.Enum

clone, compareTo, equals, finalize, getDeclaringClass, hashCode, name, ordinal, valueOf

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Enum Constant Detail

none

public static final dnnl.normalization_flags none

Use no normalization flags. If specified, the library computes mean and variance on forward propagation for training and inference, outputs them on forward propagation for training, and computes the respective derivatives on backward propagation.

use_global_stats

public static final dnnl.normalization_flags use_global_stats

Use global statistics. If specified, the library uses mean and variance provided by the user as an input on forward propagation and does not compute their derivatives on backward propagation. Otherwise, the library computes mean and variance on forward propagation for training and inference, outputs them on forward propagation for training, and computes the respective derivatives on backward propagation.

use_scale_shift

public static final dnnl.normalization_flags use_scale_shift

Use scale and shift parameters. If specified, the user is expected to pass scale and shift as inputs on forward propagation. On backward propagation of type #dnnl::prop_kind::backward, the library computes their derivatives. If not specified, the scale and shift parameters are not used by the library in any way.

fuse_norm_relu

public static final dnnl.normalization_flags fuse_norm_relu

Fuse normalization with ReLU. On training, normalization will require the workspace to implement backward propagation. On inference, the workspace is not required and behavior is the same as when normalization is fused with ReLU using the post-ops API.

Field Detail

value

public final int value

Method Detail

values

public static dnnl.normalization_flags[] values()

Returns an array containing the constants of this enum type, in the order they are declared. This method may be used to iterate over the constants as follows:

for (dnnl.normalization_flags c : dnnl.normalization_flags.values())
    System.out.println(c);

Returns:

an array containing the constants of this enum type, in the order they are declared

valueOf

public static dnnl.normalization_flags valueOf(String name)

Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)

Parameters:

name - the name of the enum constant to be returned.

Returns:

the enum constant with the specified name

Throws:

IllegalArgumentException - if this enum type has no constant with the specified name

NullPointerException - if the argument is null

intern

public dnnl.normalization_flags intern()

toString

public String toString()

Overrides:

toString in class Enum<dnnl.normalization_flags>