tf.initializers.lecun_normal
LeCun normal initializer.
tf.initializers.lecun_normal(
seed=None
)
It draws samples from a truncated normal distribution centered on 0 with standard deviation (after truncation) given by stddev = sqrt(1 / fan_in) where fan_in is the number of input units in the weight tensor.
| Arguments | |
|---|---|
seed | A Python integer. Used to seed the random generator. |
| Returns | |
|---|---|
| An initializer. |
References:
- Self-Normalizing Neural Networks, Klambauer et al., 2017
(pdf)
- Efficient Backprop, Lecun et al., 1998
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/initializers/lecun_normal