models/dense_net.py
def weight_variable_msra(self, shape, name):
        """
        Creates weights for a fully-connected layer, using an initialization
        method which does not scale the variance.

        Args:
            shape: `list` of `int`, shape of the weight matrix;
            name: `str`, a name for identifying the weight matrix.
        """
        # print("CREATING WEIGHT VARIABLE: " + name)
        # print(shape)
        return tf.get_variable(
            name=name,
            shape=shape,
            initializer=tf.contrib.layers.variance_scaling_initializer())

        Creates weights for a fully-connected layer, using an initialization
        method which does not scale the variance.

        Args:
            shape: `list` of `int`, shape of the weight matrix;
            name: `str`, a name for identifying the weight matrix.
        
Creates weights for a fully-connected layer, using an initialization
method which does not scale the variance.
Creates weights for a fully - connected layer using an initialization method which does not scale the variance .
def weight_variable_msra(self, shape, name):
        return tf.get_variable(
            name=name,
            shape=shape,
            initializer=tf.contrib.layers.variance_scaling_initializer())
def weight_variable_msra ( self , shape , name ) : return tf . get_variable ( name = name , shape = shape , initializer = tf . contrib . layers . variance_scaling_initializer ( ) )
Creates weights for a fully-connected layer, using an initialization
method which does not scale the variance.
Creates weights for a fully - connected layer using an initialization method which does not scale the variance .
"""
        Creates weights for a fully-connected layer, using an initialization
        method which does not scale the variance.

        Args:
            shape: `list` of `int`, shape of the weight matrix;
            name: `str`, a name for identifying the weight matrix.
        """ # print("CREATING WEIGHT VARIABLE: " + name) # print(shape)
self
shape
`list` of `int`, shape of the weight matrix.
` list ` of ` int ` shape of the weight matrix .
name
`str`, a name for identifying the weight matrix.
` str ` a name for identifying the weight matrix .