multicnet.py
def weight_variable(self, shape, stddev = 0.01):
        """
        Initialize weight with slight amount of noise to
        break symmetry and prevent zero gradients
        """
        initial = tf.truncated_normal(shape, stddev = stddev)
        return tf.Variable(initial)

        Initialize weight with slight amount of noise to
        break symmetry and prevent zero gradients
        
Initialize weight with slight amount of noise to
break symmetry and prevent zero gradients
Initialize weight with slight amount of noise to break symmetry and prevent zero gradients
def weight_variable(self, shape, stddev = 0.01):
        initial = tf.truncated_normal(shape, stddev = stddev)
        return tf.Variable(initial)
def weight_variable ( self , shape , stddev = 0.01 ) : initial = tf . truncated_normal ( shape , stddev = stddev ) return tf . Variable ( initial )
Initialize weight with slight amount of noise to
break symmetry and prevent zero gradients
Initialize weight with slight amount of noise to break symmetry and prevent zero gradients
"""
        Initialize weight with slight amount of noise to
        break symmetry and prevent zero gradients
        """
self
shape
stddev