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.