Glorot

public class Glorot

The Glorot initializer, also called Xavier initializer.

Draws samples from a random distribution.

If the distribution is TRUNCATED_NORMAL, then the distribution is centered on 0 with stddev = Math.sqrt(2. / (fanIn + fanOut)) where fanIn is the number of input units in the weight tensor and fanOut is the number of output units in the weight tensor.

If the distribution is UNIFORM, then samples are drawn from a uniform distribution within [-limit, limit], where limit = sqrt(6 / (fanIn + fanOut)) ( fanIn is the number of input units in the weight tensor and fanOut is the number of output units).

Examples:

Glorot Normal:

     long seed = 1001l;
     Glorot<TFloat32, TFloat32> initializer =
             new org.tensorflow.framework.initializers.Glorot<>(tf,
             Distribution.TRUNCATED_NORMAL, seed);
     Operand<TFloat32> values =
             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
 

Glorot Uniform:

    long seed = 1001l;
    Glorot<TFloat32, TFloat32> initializer =
             new org.tensorflow.framework.initializers.Glorot<>(tf,
             Distribution.UNIFORM, seed);
     Operand<TFloat32> values =
             initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
 

NOTE:

For a GlorotNormal equivalent initializer, use TRUNCATED_NORMAL for the distribution parameter.

For a GlorotUniform equivalent initializer, use UNIFORM for the distribution parameter.

See Also

• VarianceScaling.Distribution
• Glorot et al., 2010

Constants

double

SCALE

Inherited Constants

From class org.tensorflow.framework.initializers.VarianceScaling

double

SCALE_DEFAULT

Inherited Fields

From class org.tensorflow.framework.initializers.VarianceScaling

public static final VarianceScaling.Distribution	DISTRIBUTION_DEFAULT
public static final VarianceScaling.Mode	MODE_DEFAULT

Public Constructors

Glorot(Ops tf, VarianceScaling.Distribution distribution, long seed) Creates a Glorot initializer

Inherited Methods

From class org.tensorflow.framework.initializers.VarianceScaling

Operand<T>

call(Operand<TInt64> dims, Class<T> type)

From class org.tensorflow.framework.initializers.BaseInitializer

Ops	getTF() Gets the TensorFlow Ops

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface org.tensorflow.framework.initializers.Initializer

abstract Operand<T>

call(Operand<TInt64> dims, Class<T> type) Generates the operation used to perform the initialization.

Constants

public static final double SCALE

Constant Value: 1.0

Public Constructors

public Glorot (Ops tf, VarianceScaling.Distribution distribution, long seed)

Creates a Glorot initializer

Parameters

tf	the TensorFlow Ops
distribution	The distribution type for the Glorot initializer.
seed	the seed for random number generation. An initializer created with a given seed will always produce the same random tensor for a given shape and dtype.

See Also

• VarianceScaling.Distribution