WeiTang114/MVCNN-TensorFlow

conflict between code and doc in model.py

youkaichao opened this issue · 0 comments

I'm confused. In model.py, function _variable_with_weight_decay, the doc says

Note that the Variable is initialized with a truncated normal distribution.

and the code is

var = _variable_on_cpu(name, shape,initializer=tf.contrib.layers.xavier_initializer())

but in offical doc of tensorflow https://www.tensorflow.org/api_docs/python/tf/contrib/layers/xavier_initializer

the function prototype is
xavier_initializer(
uniform=True,
seed=None,
dtype=tf.float32
)

and the doc syas

uniform: Whether to use uniform or normal distributed random initialization.

So, xavier_initializer uses uniform distrubution by default.