nnlib.py 文件源码

def weight_variable(shape,
                    initializer=None,
                    init_val=None,
                    wd=None,
                    name=None,
                    trainable=True):
  """Initialize weights.
  Args:
    shape: shape of the weights, list of int
    wd: weight decay
  """
  log = logger.get()
  if initializer is None:
    initializer = tf.truncated_normal_initializer(stddev=0.01)
  if init_val is None:
    var = tf.Variable(initializer(shape), name=name, trainable=trainable)
  else:
    var = tf.Variable(init_val, name=name, trainable=trainable)
  if wd:
    weight_decay = tf.mul(tf.nn.l2_loss(var), wd, name='weight_loss')
    tf.add_to_collection('losses', weight_decay)
  return var