m_inits.py

import numpy as np
import tensorflow as tf


def init_variable(size, dim, name=None):
    std = np.sqrt(2/dim)
    return tf.Variable(tf.random_uniform([size, dim], -std, std), name=name)


def glorot(shape, name=None):
    """Glorot & Bengio (AISTATS 2010) init."""
    # init_range = np.sqrt(6.0/(shape[0]+shape[1]))
    # initial = tf.random_uniform(shape, minval=-init_range, maxval=init_range, dtype=tf.float32)
    # initial = tf.random_uniform(shape, stddev=0.1)

    # return tf.Variable(tf.random_normal(shape, stddev=1.0))
    return tf.Variable(tf.truncated_normal(shape=shape, stddev=0.1))
    # return tf.Variable(tf.truncated_normal(shape=shape, stddev=np.sqrt(2/shape[0])))


def zeros(shape, name=None):
    """All zeros."""
    initial = tf.zeros(shape, dtype=tf.float32)
    return tf.Variable(initial, name=name)