tf.glorot_uniform_initializer

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

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

The Glorot uniform initializer, also called Xavier uniform initializer.

It draws samples from a uniform distribution within [-limit, limit] where limit is sqrt(6 / (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.