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tf.glorot_normal_initializer

tf.glorot_normal_initializer(
    seed=None,
    dtype=tf.float32
)

Defined in tensorflow/python/ops/init_ops.py.

The Glorot normal initializer, also called Xavier normal initializer.

It draws samples from a truncated normal distribution centered on 0 with stddev = sqrt(2 / (fan_in + fan_out)) where fan_in is the number of input units in the weight tensor and fan_out is the number of output units in the weight tensor.

Reference: http://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf

Args:

  • seed: A Python integer. Used to create random seeds. See tf.set_random_seed for behavior.
  • dtype: The data type. Only floating point types are supported.

Returns:

An initializer.

© 2018 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/api_docs/python/tf/glorot_normal_initializer