LeCun normal initializer.
Draws samples from a random distribution. * *
If the distribution is TRUNCATED_NORMAL, it draws samples from a truncated normal distribution
centered on 0
with
stddev = sqrt(1 / fanIn)
where fanIn
is the number of input units in the
weight tensor.
If the distribution is UNIFORM, itraws samples from a uniform distribution within
[-limit, limit]
, where limit = Math.sqrt(3 / fanIn)
(fanIn
is
the number of input units in the weight tensor)
Examples:
LeCun Normal:
long seed = 1001l; LeCunNormal<TFloat32, TFloat32> initializer = new org.tensorflow.framework.initializers.LeCunNormal<>(tf, Distribution.TRUNCATED_NORMAL, seed); Operand<TFloat32> values = initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
LeCun Uniform:
long seed = 1001l; LeCunNormal<TFloat32, TFloat32> initializer = new org.tensorflow.framework.initializers.LeCunNormal<>(tf, Distribution.UNIFORM, seed); Operand<TFloat32> values = initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);
NOTE: *
For a LeCunNormal equivalent initializer, use TRUNCATED_NORMAL
for the distribution parameter. *
For a LeCunUniform equivalent initializer, use UNIFORM
*
for the distribution parameter. *
Inherited Constants
Inherited Fields
Public Constructors
LeCun(Ops tf, VarianceScaling.Distribution distribution, long seed)
Creates a LeCunNormal Initializer
|
Inherited Methods
Public Constructors
public LeCun (Ops tf, VarianceScaling.Distribution distribution, long seed)
Creates a LeCunNormal 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. |